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    "scalar_hash_scan_float32_n32_sorted0_input_x": [0, 6, 12, 18, 24, 30, 5, 11, 17, 23, 29, 4, 10, 16, 22, 28, 3, 9, 15, 21, 27, 2, 8, 14, 20, 26, 1, 7, 13, 19, 25, 0],
    "scalar_hash_scan_float32_n33_sorted0_input_x": [0, 5, 10, 15, 20, 25, 30, 3, 8, 13, 18, 23, 28, 1, 6, 11, 16, 21, 26, 31, 4, 9, 14, 19, 24, 29, 2, 7, 12, 17, 22, 27, 0],
    "scalar_hash_uint32_finite_mask7_axis_sorted1_output_inverse_indices": [4, 0, 3, 1, 4, 2, 4, 0, 3, 1, 4, 2, 4, 0, 3, 1, 4, 2, 4, 0, 3, 1, 4, 2, 4, 0, 3, 1, 4, 2, 4, 0, 3],
    "scalar_hash_uint32_finite_mask7_flat_sorted0_input_x": [4294967295, 0, 2147483648, 7, 4294967295, 2147483647, 4294967295, 0, 2147483648, 7, 4294967295, 2147483647, 4294967295, 0, 2147483648, 7, 4294967295, 2147483647, 4294967295, 0, 2147483648, 7, 4294967295, 2147483647, 4294967295, 0, 2147483648, 7, 4294967295, 2147483647, 4294967295, 0, 2147483648],
    "scalar_hash_uint8_finite_mask7_flat_sorted0_input_x": [255, 0, 128, 7, 255, 127, 255, 0, 128, 7, 255, 127, 255, 0, 128, 7, 255, 127, 255, 0, 128, 7, 255, 127, 255, 0, 128, 7, 255, 127, 255, 0, 128],
    "serial_sorted_dense_duplicates_int32_input_x": [37, -5, 12, 99, -73, 0, 41, 8, -21, 64, 3, -90, 55, 17, -2, 76, 29, -48, 83, 6, -33, 92, 14, -67, 50, 22, -9, 70, 35, -58, 88, 1, -26, 95, 19, -81, 46, 27, -14, 61, 33, -44, 79, 10, -39, 53, 24, -86],
    "single_class_axis1_outer2_inner3_mask0_input_x": [7, 2, 5, 7, 2, 5, 7, 2, 5, 7, 2, 5, 7, 2, 5, 11, 3, 2, 11, 3, 2, 11, 3, 2, 11, 3, 2, 11, 3, 2],
    "flat_global_crossover_int32_n4097_u2049_sorted0_input_x": [2048, 2047, 2046, 2045, 2044, 2043, 2042, 2041, 2040, 2039, 2038, 2037, 2036, 2035, 2034, 2033, 2032, 2031, 2030, 2029, 2028, 2027, 2026, 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004, 2003, 2002, 2001, 2000, 1999, 1998, 1997, 1996, 1995, 1994, 1993, 1992, 1991, 1990, 1989, 1988, 1987, 1986, 1985, 1984, 1983, 1982, 1981, 1980, 1979, 1978, 1977, 1976, 1975, 1974, 1973, 1972, 1971, 1970, 1969, 1968, 1967, 1966, 1965, 1964, 1963, 1962, 1961, 1960, 1959, 1958, 1957, 1956, 1955, 1954, 1953, 1952, 1951, 1950, 1949, 1948, 1947, 1946, 1945, 1944, 1943, 1942, 1941, 1940, 1939, 1938, 1937, 1936, 1935, 1934, 1933, 1932, 1931, 1930, 1929, 1928, 1927, 1926, 1925, 1924, 1923, 1922, 1921, 1920, 1919, 1918, 1917, 1916, 1915, 1914, 1913, 1912, 1911, 1910, 1909, 1908, 1907, 1906, 1905, 1904, 1903, 1902, 1901, 1900, 1899, 1898, 1897, 1896, 1895, 1894, 1893, 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    "output_span_int32_n257_sorted0_input_x": [257, 256, 255, 254, 253, 252, 251, 250, 249, 248, 247, 246, 245, 244, 243, 242, 241, 240, 239, 238, 237, 236, 235, 234, 233, 232, 231, 230, 229, 228, 227, 226, 225, 224, 223, 222, 221, 220, 219, 218, 217, 216, 215, 214, 213, 212, 211, 210, 209, 208, 207, 206, 205, 204, 203, 202, 201, 200, 199, 198, 197, 196, 195, 194, 193, 192, 191, 190, 189, 188, 187, 186, 185, 184, 183, 182, 181, 180, 179, 178, 177, 176, 175, 174, 173, 172, 171, 170, 169, 168, 167, 166, 165, 164, 163, 162, 161, 160, 159, 158, 157, 156, 155, 154, 153, 152, 151, 150, 149, 148, 147, 146, 145, 144, 143, 142, 141, 140, 139, 138, 137, 136, 135, 134, 133, 132, 131, 130, 129, 128, 127, 126, 125, 124, 123, 122, 121, 120, 119, 118, 117, 116, 115, 114, 113, 112, 111, 110, 109, 108, 107, 106, 105, 104, 103, 102, 101, 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, 80, 79, 78, 77, 76, 75, 74, 73, 72, 71, 70, 69, 68, 67, 66, 65, 64, 63, 62, 61, 60, 59, 58, 57, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1],
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    "axis_merge_float32_outer1_u17_tile16_nan_fallback_input_x": [0, 0, 17, -0, -0, 16, 0, 0, 15, -0, -0, 14, 0, 0, 13, -0, -0, 12, 0, 0, 11, -0, -0, 10, 0, 0, 9, -0, -0, 8, 0, 0, 7, -0, -0, 6, 0, 0, 5, -0, -0, 4, 0, 0, 3, -0, -0, 2, 0, 0, 1, -0, -0, 17, 0, 0, 16, -0, -0, 15, 0, 0, 14, -0, -0, 13, 0, 0, 12, -0, -0, 11, 0, 0, 10, -0, -0, 9, 0, 0, 8, -0, -0, 7, 0, 0, 6, -0, -0, 5, 0, 0, 4, -0, -0, 3, 0, 0, 2, -0, -0, 1, 0, 0, 17, -0, -0, 16, 0, 0, 15, -0, -0, 14, 0, 0, 13, -0, -0, 12, 0, 0, 11, -0, -0, 10, 0, 0, 9, -0, -0, 8, 0, 0, 7, -0, -0, 6, 0, 0, 5, -0, -0, 4, 0, 0, 3, -0, -0, 2, 0, 0, 1, -0, -0, 17, 0, 0, 16, -0, -0, 15, 0, 0, 14, -0, -0, 13, 0, 0, 12, -0, -0, 11, 0, 0, 10, -0, -0, 9, 0, 0, 8, -0, -0, 7, 0, 0, 6, -0, -0, 5, 0, 0, 4, -0, -0, 3, "NaN", 0, 1]
  },
  "cases": [
    {
      "name": "sorted_int32",
      "inputs": {
        "x": { "dtype": "int32", "shape": [8], "data": { "kind": "values", "values": [3, 1, 3, 2, 1, -1, 2, 4] } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [5] } }
    },
    {
      "name": "first_seen_uint8_overflow",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "uint8", "shape": [7], "data": { "kind": "values", "values": [5, 6, 5, 7, 8, 9, 10] } }
      },
      "outputs": { "y": { "dtype": "uint8", "shape": [6] } }
    },
    {
      "name": "sorted_f32",
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [2.5, -1.0, 2.5, 0.0, -1.0, 4.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4] } }
    },
    {
      "name": "f32_subnormal_distinct_from_zero",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Unsorted",
        "notes": "Subnormal finite values are distinct from zero and preserve first-seen order when sorted=0."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [5],
          "data": { "kind": "values", "values": [0.0, 1e-40, 0.0, -1e-40, 1e-40] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1e-40, -1e-40] }
        }
      }
    },
    {
      "name": "f32_sorted_subnormal_distinct_from_zero",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Sorted",
        "notes": "Sorted Unique must keep negative subnormal, zero, and positive subnormal as distinct ordered buckets."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [5],
          "data": { "kind": "values", "values": [0.0, 1e-40, -1e-40, 0.0, 1e-40] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-1e-40, 0.0, 1e-40] }
        }
      }
    },
    {
      "name": "ort_unsorted_nan_equivalence",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Unsorted",
        "notes": "Additional case checked against ONNX Runtime's CPU provider: ordered-map lower_bound makes NaN comparator-equivalent to its candidate bucket at insertion, so later finite values still deduplicate normally."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [2.0, "NaN", 2.0, "NaN", 3.0] } }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [2.0, 3.0] } }
      }
    },
    {
      "name": "ort_backend_unsorted_first_seen_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Unsorted_MatchOnnxTest"
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 0 } }
    },
    {
      "name": "ort_flatten_unsorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Unsorted"
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [1.0, 4.0, 1.0, 2.0, 2.0, 0.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 0 } }
    },
    {
      "name": "ort_flatten_sorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Sorted"
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [1.0, 4.0, 1.0, 2.0, 2.0, 0.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 0 } }
    },
    {
      "name": "ort_empty_input_f32",
      "provenance": { "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc", "test": "Unique.EmptyInput" },
      "inputs": { "x": { "dtype": "float32", "shape": [0], "data": { "kind": "values", "values": [] } } },
      "outputs": { "y": { "dtype": "float32", "shape": [0], "tolerance": 0 } }
    },
    {
      "name": "length1_f32_backend",
      "inputs": { "x": { "dtype": "float32", "shape": [1], "data": { "kind": "values", "values": [0.0] } } },
      "outputs": { "y": { "dtype": "float32", "shape": [1], "tolerance": 0 } }
    },
    {
      "name": "all_duplicates_exact_output",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [5],
          "data": { "kind": "values", "values": [-7.0, -7.0, -7.0, -7.0, -7.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1], "tolerance": 0 } }
    },
    {
      "name": "int8_signed_sorted_order",
      "inputs": {
        "x": {
          "dtype": "int8",
          "shape": [8],
          "data": { "kind": "values", "values": [3, -1, -128, 3, 127, -1, 0, -128] }
        }
      },
      "outputs": { "y": { "dtype": "int8", "shape": [5], "tolerance": 0 } }
    },
    {
      "name": "ort_no_optional_output_int8_sorted",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.NoOptionalOutput",
        "notes": "The fixture requests only Y, the standard required output, with its exact data-dependent shape."
      },
      "inputs": {
        "x": { "dtype": "int8", "shape": [8], "data": { "kind": "values", "values": [1, 4, -1, 2, 2, 0, -1, 4] } }
      },
      "outputs": { "y": { "dtype": "int8", "shape": [5], "tolerance": 0 } }
    },
    {
      "name": "ort_axis0_unsorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Axis0_Unsorted",
        "notes": "The fixture supplies the exact data-dependent Y shape and requests no optional metadata outputs."
      },
      "attrs": { "axis": 0, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 2],
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 0.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 1.0, 1.0, 0.0] }
        }
      }
    },
    {
      "name": "ort_axis0_sorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Axis0_Sorted",
        "notes": "The fixture supplies the exact data-dependent Y shape and requests no optional metadata outputs."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 2],
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 0.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 0.0, 1.0, 1.0] }
        }
      }
    },
    {
      "name": "ort_axis1_unsorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Axis1_Unsorted",
        "notes": "The fixture supplies the exact data-dependent Y shape and requests no optional metadata outputs."
      },
      "attrs": { "axis": 1, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 4, 2],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_axis1_unsorted_f32_input_x" } }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 1.0, 0.0, 1.0, 2.0, 1.0, 1.0, 1.0, 0.0, 1.0, 2.0, 1.0] }
        }
      }
    },
    {
      "name": "ort_axis1_sorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Axis1_Sorted",
        "notes": "The fixture supplies the exact data-dependent Y shape and requests no optional metadata outputs."
      },
      "attrs": { "axis": 1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 4, 2],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_axis1_unsorted_f32_input_x" } }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 1.0, 2.0, 1.0, 0.0, 1.0, 1.0, 1.0, 2.0, 1.0] }
        }
      }
    },
    {
      "name": "ort_axis2_unsorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Axis2_Unsorted",
        "notes": "The fixture supplies the exact data-dependent Y shape and requests no optional metadata outputs."
      },
      "attrs": { "axis": 2, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 2, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_axis1_unsorted_f32_input_x" } }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 2, 3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 1.0, 0.0, 2.0, 1.0, 0.0, 1.0, 1.0, 0.0, 2.0, 1.0, 0.0] }
        }
      }
    },
    {
      "name": "ort_axis2_sorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Axis2_Sorted",
        "notes": "The fixture supplies the exact data-dependent Y shape and requests no optional metadata outputs."
      },
      "attrs": { "axis": 2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 2, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_axis1_unsorted_f32_input_x" } }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 2, 3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 0.0, 1.0, 2.0, 0.0, 1.0, 1.0, 0.0, 1.0, 2.0] }
        }
      }
    },
    {
      "name": "ort_negative_axis_last_sorted_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Axis2_Sorted",
        "notes": "Same semantic case as ORT's positive axis=2 coverage, expressed with the ONNX-valid negative last-axis spelling and an exact data-dependent Y shape."
      },
      "attrs": { "axis": -1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 2, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_axis1_unsorted_f32_input_x" } }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 2, 3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 0.0, 1.0, 2.0, 0.0, 1.0, 1.0, 0.0, 1.0, 2.0] }
        }
      }
    },
    {
      "name": "onnx_backend_unique_length_1",
      "attrs": { "sorted": 1 },
      "inputs": { "x": { "dtype": "int32", "shape": [1], "data": { "kind": "values", "values": [0] } } },
      "outputs": { "y": { "dtype": "int32", "shape": [1] } },
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_unique_length_1",
        "notes": "The fixture supplies the exact data-dependent Y shape. Optional ONNX int64 metadata outputs are omitted here; requested metadata is represented as uint32 where values are representable."
      }
    },
    {
      "name": "onnx_backend_unique_not_sorted_without_axis",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4] } },
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_unique_not_sorted_without_axis",
        "notes": "The fixture supplies the exact data-dependent Y shape. Optional ONNX int64 metadata outputs are omitted here; requested metadata is represented as uint32 where values are representable."
      }
    },
    {
      "name": "onnx_backend_unique_sorted_without_axis",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4] } },
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_unique_sorted_without_axis",
        "notes": "The fixture supplies the exact data-dependent Y shape. Optional ONNX int64 metadata outputs are omitted here; requested metadata is represented as uint32 where values are representable."
      }
    },
    {
      "name": "serial_sorted_dense_duplicates_int32",
      "provenance": {
        "notes": "2048 elements cycling 48 distinct values exercise the deduplication early exit and sorted exchange sort with an exact 48-element result."
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [2048],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/serial_sorted_dense_duplicates_int32_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [48], "tolerance": 0 } }
    },
    {
      "name": "serial_first_seen_order_f32_1024",
      "attrs": { "sorted": 0 },
      "provenance": {
        "notes": "First-seen order is preserved over 1024 elements with 32 distinct values and an exact 32-element result."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1024],
          "data": {
            "kind": "cycle",
            "values": [0.5, -1.25, 3.0, 7.75, -0.5, 2.25, 9.0, -4.5, 1.5, 6.25, -8.0, 0.25, 5.5, -2.75, 4.0, 8.5, -6.25, 1.75, 7.25, -3.5, 2.5, 9.75, -0.75, 5.25, -7.5, 3.25, 6.75, -1.5, 4.75, 8.25, -5.75, 0.75]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [32], "tolerance": 0 } }
    },
    {
      "name": "serial_f32_subnormal_distinct_from_zero",
      "attrs": { "sorted": 0 },
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Unsorted",
        "notes": "A 4,096-element cycle of zero and signed subnormal values verifies that the serial float comparator keeps finite subnormals distinct from zero and emits three first-seen buckets."
      },
      "inputs": {
        "x": { "dtype": "float32", "shape": [4096], "data": { "kind": "cycle", "values": [0.0, 1e-40, 0.0, -1e-40] } }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1e-40, -1e-40] }
        }
      }
    },
    {
      "name": "serial_sorted_f32_32k_subnormal",
      "attrs": { "sorted": 1 },
      "provenance": {
        "notes": "32768 f32 elements cycling six distinct values, including positive and negative subnormals, exercise the exact ordered-map float path at scale. Subnormals remain bit-distinct from zero and from each other, and sorted output uses the IEEE total-order key."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": [0.0, 1e-40, -1e-40, 2.5, -3.5, 7.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [6], "tolerance": 0 } }
    },
    {
      "name": "serial_unsorted_first_seen_f32_32k_subnormal",
      "attrs": { "sorted": 0 },
      "provenance": {
        "notes": "A 32,768-element subnormal cycle verifies that the serial float path orders output buckets by representative input index when sorted is disabled."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": [0.0, 1e-40, -1e-40, 2.5, -3.5, 7.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [6], "tolerance": 0 } }
    },
    {
      "name": "serial_f32_32k_nan_lower_bound",
      "attrs": { "sorted": 0 },
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/tensor/unique_op_test.cc",
        "test": "Unique.Flatten_Unsorted",
        "notes": "NaN equivalence on the exact ordered-map float path at large input size: each NaN resolves to the lower-bound bucket headed by 2 and forms no new bucket."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": [2.0, "NaN", 3.0, "NaN", 5.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [2.0, 3.0, 5.0] }
        }
      }
    },
    {
      "name": "hash_sorted_int32_32k",
      "attrs": { "sorted": 1 },
      "provenance": {
        "notes": "A 32,768-element int32 input cycling 48 distinct values exercises sorted parallel hash deduplication with an exact integer result."
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/serial_sorted_dense_duplicates_int32_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [48], "tolerance": 0 } }
    },
    {
      "name": "hash_unsorted_first_seen_int32_32k",
      "attrs": { "sorted": 0 },
      "provenance": {
        "notes": "32768 int32 elements cycling 48 distinct values, first-seen order: the hash dedup folds in atomicMin(index), so the compacted order matches the appearance order of the parallel/serial paths exactly."
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/serial_sorted_dense_duplicates_int32_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [48], "tolerance": 0 } }
    },
    {
      "name": "hash_sentinel_value_minus_one_int32_64k",
      "attrs": { "sorted": 1 },
      "provenance": {
        "notes": "65536 int32 elements whose distinct set includes -1 (bitcast<u32> == 0xffffffff, the hash table's EMPTY sentinel). Exercises the dedicated `special` min-index slot the hash dedup uses for the one value that cannot be a hash key."
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [65536],
          "data": {
            "kind": "cycle",
            "values": [-1, 7, -1, 3, 100, -50, -1, 42, 7, 3, -2147483648, 2147483647, 0, -1, 13, 100]
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [10], "tolerance": 0 } }
    },
    {
      "name": "hash_uint8_sorted_32k",
      "attrs": { "sorted": 1 },
      "provenance": {
        "notes": "32768 uint8 elements cycling 12 distinct values: exercises the hash dedup's unsigned-key path (dtypes.T == u32 carried width) at the >= 32768 floor."
      },
      "inputs": {
        "x": {
          "dtype": "uint8",
          "shape": [32768],
          "data": { "kind": "cycle", "values": [5, 200, 17, 5, 255, 0, 128, 17, 64, 200, 3, 250, 0, 5] }
        }
      },
      "outputs": { "y": { "dtype": "uint8", "shape": [9], "tolerance": 0 } }
    },
    {
      "name": "hash_uint32_few_distinct_64k",
      "attrs": { "sorted": 1 },
      "provenance": {
        "notes": "65536 uint32 elements with only 6 distinct values (heavy duplicates) including 0xffffffff (the EMPTY sentinel): few-distinct stress for the hash dedup atomicMin contention plus the unsigned special-slot path."
      },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [65536],
          "data": { "kind": "cycle", "values": [4294967295, 0, 7, 4294967295, 1000000, 42, 7, 0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [5], "tolerance": 0 } }
    },
    {
      "name": "axis0_f32_subnormal_collapse_unsorted",
      "attrs": { "axis": 0, "sorted": 0 },
      "provenance": {
        "notes": "Spec-valid axis-mode deduplication over a [N,2] tensor. Raw-bit float comparisons keep finite subnormals distinct from zero even on FTZ GPUs; the pinned output is cross-checked with ORT."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [5, 2],
          "data": { "kind": "values", "values": [0.0, 5.0, 1e-40, 5.0, -1e-40, 5.0, 0.0, 5.0, 2.0, 7.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [4, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 5.0, 1e-40, 5.0, -1e-40, 5.0, 2.0, 7.0] }
        }
      }
    },
    {
      "name": "axis0_f32_subnormal_collapse_sorted",
      "attrs": { "axis": 0, "sorted": 1 },
      "provenance": {
        "notes": "Raw-bit equality and total-order keys preserve -1e-40 < 0 < 1e-40 when arithmetic operations flush subnormals to zero."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [5, 2],
          "data": { "kind": "values", "values": [0.0, 5.0, 1e-40, 5.0, -1e-40, 5.0, 0.0, 5.0, 2.0, 7.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [4, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-1e-40, 5.0, 0.0, 5.0, 1e-40, 5.0, 2.0, 7.0] }
        }
      }
    },
    {
      "name": "hash_int8_signed_negatives_32k",
      "attrs": { "sorted": 1 },
      "provenance": {
        "notes": "Hash deduplication over 32,768 int8 elements must sort 12 distinct values, including -128, 127, and other negatives. Expected values follow the operator's sorting rule."
      },
      "inputs": {
        "x": {
          "dtype": "int8",
          "shape": [32768],
          "data": { "kind": "cycle", "values": [5, -1, -128, 3, 127, -1, 0, -128, 42, -64, 100, -100, 7, 17] }
        }
      },
      "outputs": { "y": { "dtype": "int8", "shape": [12], "tolerance": 0 } }
    },
    {
      "name": "parallel_uint32_sentinel_first_seen_4k",
      "attrs": { "sorted": 0 },
      "provenance": {
        "notes": "Parallel deduplication over 4,096 uint32 elements must preserve first-seen order, including 0xffffffff. Expected values follow the operator's ordering rule."
      },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [4096],
          "data": { "kind": "cycle", "values": [4294967295, 0, 7, 1000000, 4294967295, 42, 0, 13, 7, 999] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [7], "tolerance": 0 } }
    },
    {
      "name": "flat_f32_all_distinct_4096",
      "provenance": {
        "notes": "4096 fully distinct values exercise the exact large-output serial float path and its ordered representative set."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [4096], "data": { "kind": "linspace", "start": -4096.0, "end": 4095.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4096], "tolerance": 0 } }
    },
    {
      "name": "axis0_f32_all_distinct_2500",
      "provenance": {
        "notes": "2500 fully distinct scalar rows exercise exact axis-mode output and bit-preserving slice comparison at a large axis size."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2500, 1], "data": { "kind": "linspace", "start": -5000.0, "end": 4999.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [2500, 1], "tolerance": 0 } }
    },
    {
      "name": "serial_f32_32k_signed_zero_single_bucket",
      "provenance": {
        "notes": "32768 f32 elements containing both +0.0 and -0.0 plus finite values verify that exact serial equality canonicalizes signed zero into one bucket."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": [0.0, 0.0, 2.5, -3.5, 7.0, 0.0, 0.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 0 } }
    },
    {
      "name": "large_y_int32_sorted_2501_distinct",
      "provenance": {
        "notes": "6000 int32 values deduplicate to an exact 2501-element sorted result, exercising the large-output global-scratch sort and signed integer order across zero."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [6000], "data": { "kind": "linspace", "start": -1200, "end": 1300 } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2501] } }
    },
    {
      "name": "large_y_int32_unsorted_8192_distinct",
      "provenance": {
        "notes": "8192 distinct int32 values exercise the large-output unsorted compaction path without allocating or touching bitonic-sort scratch."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [8192], "data": { "kind": "linspace", "start": -4096, "end": 4095 } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [8192] } }
    },
    {
      "name": "f32_sorted_padding_heavy",
      "provenance": {
        "notes": "A padding-heavy sorted float case with about 40 distinct values verifies max-key padding and raw-bit float ordering, including negatives and signed zero."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [400],
          "data": {
            "kind": "cycle",
            "values": [3.5, -1.0, 0.0, 2.5, -7.25, 100.0, -100.0, 0.5, -0.5, 42.0, -42.0, 1.0, -1.5, 88.75, -88.75, 6.0, -6.0, 13.5, -13.5, 21.0, -21.0, 7.0, -7.0, 55.5, -55.5, 9.0, -9.0, 64.25, -64.25, 4.0, -4.0, 17.0, -17.0, 30.0, -30.0, 2.0, -2.0, 11.0, -11.0, 99.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [40] } }
    },
    {
      "name": "uint32_sorted_unsigned_order",
      "provenance": {
        "notes": "The exact 30-element result spans values above 2^31 through 0xffffffff and verifies unsigned ordering rather than a signed interpretation of raw bits."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [300],
          "data": {
            "kind": "cycle",
            "values": [10, 4000000000, 5, 2147483648, 0, 3000000000, 100, 2147483647, 42, 4294967295, 7, 1, 2500000000, 99, 2147483649, 3, 500, 4000000001, 8, 2, 123456, 4294967294, 55, 2147483650, 9, 777, 3500000000, 6, 4, 1000000]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [30] } }
    },
    {
      "name": "int32_unsorted_first_occurrence",
      "provenance": {
        "notes": "The exact 30-element unsorted result preserves first-occurrence order while round-tripping signed int32 values through raw-bit scratch."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [300],
          "data": {
            "kind": "cycle",
            "values": [37, -5, 12, 99, -73, 0, 41, 8, -21, 64, 3, -90, 55, 17, -2, 76, 29, -48, 83, 6, -33, 92, 14, -67, 50, 22, -9, 70, 35, -58]
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [30] } }
    },
    {
      "name": "axis0_large_y_f32_sorted_2200_distinct",
      "provenance": {
        "notes": "The exact serial float axis path handles 2200 distinct scalar slices with its representative order in global storage. This keeps float behavior aligned with ORT's non-transitive NaN comparator without exceeding workgroup-storage limits."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2200, 1], "data": { "kind": "linspace", "start": -500.0, "end": 500.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [2200, 1] } }
    },
    {
      "name": "axis0_large_y_int32_unsorted_2100_distinct",
      "provenance": {
        "notes": "An axis length of 2,100 with sorted=0 requires multi-chunk parallel compaction without a sort network. Because each slice has one element, the distinct values must be emitted in first-occurrence order."
      },
      "attrs": { "axis": 0, "sorted": 0 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [2100, 1], "data": { "kind": "linspace", "start": -4000, "end": 4000 } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2100, 1] } }
    },
    {
      "name": "axis_hash_split_scatter_sorted_all_distinct",
      "provenance": {
        "notes": "The hash-backed axis path compacts, sorts, and scatters all 4096 distinct scalar rows into the exact output shape."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [4096, 1], "data": { "kind": "linspace", "start": -2048, "end": 2047 } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [4096, 1], "tolerance": 0 } }
    },
    {
      "name": "axis_hash_split_scatter_unsorted_four_distinct",
      "provenance": {
        "notes": "Four distinct scalar rows exercise grid-parallel axis scatter and must be emitted in first-occurrence order into an exact four-row output."
      },
      "attrs": { "axis": 0, "sorted": 0 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [2048, 1], "data": { "kind": "cycle", "values": [9, -2, 7, 9, 42, -2] } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [4, 1], "tolerance": 0 } }
    },
    {
      "name": "axis_hash_int32_inner2_duplicate_rows_sorted",
      "provenance": {
        "notes": "An axis length of 2,048 exercises exact hash deduplication for two-element rows. Repeated rows must share a bucket, first-occurrence representatives must survive, and sorted output must be lexicographic over complete rows."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [2048, 2], "data": { "kind": "cycle", "values": [2, 1, 0, 3, 2, 1, -1, 4] } }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-1, 4, 0, 3, 2, 1] }
        }
      }
    },
    {
      "name": "hash_int32_sorted_16_distinct",
      "provenance": {
        "notes": "A 32768-element input with 16 distinct signed values exercises hash-backed compaction and sorting with an exact result."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": [37, -5, 12, 99, -73, 0, 41, 8, -21, 64, 3, -90, 55, 17, -2, 76] }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [16] } }
    },
    {
      "name": "hash_int32_sorted_16k_4096_distinct",
      "provenance": {
        "notes": "A 16K-element input with exactly 4096 distinct integers exercises the narrow int32 large-output hash threshold and signed sorting."
      },
      "attrs": { "sorted": 1 },
      "inputs": { "x": { "dtype": "int32", "shape": [16384], "data": { "kind": "linspace", "start": 0, "end": 4095 } } },
      "outputs": { "y": { "dtype": "int32", "shape": [4096] } }
    },
    {
      "name": "hash_int32_sorted_262k_2049_distinct_variable_subgroup",
      "provenance": {
        "notes": "Large repeated integer input with output just above the local-sort capacity checks exact sorted results on both the parallel and key-only hash-collect device tiers."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [262144], "data": { "kind": "linspace", "start": 0, "end": 2048 } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2049], "tolerance": 0 } }
    },
    {
      "name": "exact_output_33_unsorted_f32_serial",
      "provenance": {
        "notes": "Thirty-three distinct float values exercise exact-output first-occurrence ordering on the serial float path."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [33], "data": { "kind": "linspace", "start": -16.0, "end": 16.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [33], "tolerance": 0 } }
    },
    {
      "name": "rank7_axis_last",
      "attrs": { "axis": 6, "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [1, 2, 1, 2, 1, 2, 4], "data": { "kind": "constant", "value": 3.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1, 2, 1, 2, 1, 2, 1], "tolerance": 0 } }
    },
    {
      "name": "axis0_y1025_storage_order_serial",
      "provenance": {
        "notes": "A 1025-row exact float output exercises axis_serial with storage-backed representative order, so its capacity is independent of maxComputeWorkgroupStorageSize."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [1025, 1], "data": { "kind": "linspace", "start": -1024.0, "end": 1024.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1025, 1], "tolerance": 0 } }
    },
    {
      "name": "axis0_rows65537_above_hash_ceiling",
      "provenance": {
        "notes": "A 65,537-row input cycling 2,049 distinct values exercises large-axis hash deduplication and sorted output."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [65537, 1], "data": { "kind": "linspace", "start": 0, "end": 2048 } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2049, 1], "tolerance": 0 } }
    },
    {
      "name": "rank8_axis_last",
      "attrs": { "axis": 7, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 2, 1, 2, 1, 2, 2, 4],
          "data": { "kind": "cycle", "values": [1.0, 2.0, 3.0, 1.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1, 2, 1, 2, 1, 2, 2, 3], "tolerance": 0 } }
    },
    {
      "name": "axis0_uint32_sorted_order",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises unsigned slice ordering through the bounded parallel axis compaction path, including values above int32 range."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [6, 1],
          "data": { "kind": "values", "values": [4000000000, 5, 2147483648, 5, 0, 4000000000] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint32",
          "shape": [4, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 5, 2147483648, 4000000000] }
        }
      }
    },
    {
      "name": "axis_empty_y_only",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "An empty selected axis has zero unique slices and therefore a legal zero-sized Y axis."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": { "x": { "dtype": "int32", "shape": [0, 2], "data": { "kind": "values", "values": [] } } },
      "outputs": { "y": { "dtype": "int32", "shape": [0, 2], "tolerance": 0 } }
    },
    {
      "name": "axis_empty_all_metadata",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Zero-length axis mode requests every standard optional metadata output with its exact empty shape."
      },
      "attrs": { "axis": 1, "sorted": 0 },
      "inputs": { "x": { "dtype": "int32", "shape": [2, 0, 3], "data": { "kind": "values", "values": [] } } },
      "outputs": {
        "y": { "dtype": "int32", "shape": [2, 0, 3], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [0], "tolerance": 0, "data": { "kind": "values", "values": [] } },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [0],
          "tolerance": 0,
          "data": { "kind": "values", "values": [] }
        },
        "counts": { "dtype": "uint32", "shape": [0], "tolerance": 0, "data": { "kind": "values", "values": [] } }
      }
    },
    {
      "name": "axis_nan_ordered_map_unsorted_all_metadata",
      "provenance": {
        "source": "onnxruntime/core/providers/cpu/tensor/unique.cc",
        "notes": "ORT's ordered slice comparator stops at the first unequal coordinate. A NaN there makes the key equivalent to the lower-bound bucket and ignores the remaining suffix."
      },
      "attrs": { "axis": 0, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 2],
          "data": { "kind": "values", "values": [5.0, 0.0, 1.0, 0.0, "NaN", 9.0, 3.0, 0.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 0.0, 1.0, 0.0, 3.0, 0.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 3] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 1, 2] }
        },
        "counts": { "dtype": "uint32", "shape": [3], "tolerance": 0, "data": { "kind": "values", "values": [1, 2, 1] } }
      }
    },
    {
      "name": "axis_nan_ordered_map_sorted_all_metadata",
      "provenance": {
        "source": "onnxruntime/core/providers/cpu/tensor/unique.cc",
        "notes": "The same NaN lower-bound equivalence is retained while sorted output follows the ordered map's comparator order."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 2],
          "data": { "kind": "values", "values": [5.0, 0.0, 1.0, 0.0, "NaN", 9.0, 3.0, 0.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 0.0, 3.0, 0.0, 5.0, 0.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1, 3, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [2, 0, 0, 1] }
        },
        "counts": { "dtype": "uint32", "shape": [3], "tolerance": 0, "data": { "kind": "values", "values": [2, 1, 1] } }
      }
    },
    {
      "name": "flat_nan_ordered_map_unsorted_all_metadata",
      "provenance": {
        "source": "onnxruntime/core/providers/cpu/tensor/unique.cc",
        "notes": "Flat Unique uses the same stateful lower_bound rule: NaN maps to the smallest bucket present at its insertion point, not unconditionally to output bucket zero."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [5.0, 1.0, "NaN", 3.0] } }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0, 3.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 3] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 1, 2] }
        },
        "counts": { "dtype": "uint32", "shape": [3], "tolerance": 0, "data": { "kind": "values", "values": [1, 2, 1] } }
      }
    },
    {
      "name": "flat_nan_ordered_map_sorted_all_metadata",
      "provenance": {
        "source": "onnxruntime/core/providers/cpu/tensor/unique.cc",
        "notes": "Sorted flat output keeps the ordered-map bucket accounting while emitting comparator order."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [5.0, 1.0, "NaN", 3.0] } }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 3.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1, 3, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [2, 0, 0, 1] }
        },
        "counts": { "dtype": "uint32", "shape": [3], "tolerance": 0, "data": { "kind": "values", "values": [2, 1, 1] } }
      }
    },
    {
      "name": "flat_nan_ordered_map_insertion_state_all_metadata",
      "provenance": {
        "source": "onnxruntime/core/providers/cpu/tensor/unique.cc",
        "notes": "With NaN inserted before the later minimum, lower_bound associates it with 5 rather than retroactively moving it to the later 1 bucket."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [5.0, "NaN", 1.0, 3.0] } }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0, 3.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 2, 3] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 0, 1, 2] }
        },
        "counts": { "dtype": "uint32", "shape": [3], "tolerance": 0, "data": { "kind": "values", "values": [2, 1, 1] } }
      }
    },
    {
      "name": "metadata_flat_all_int32",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises every optional output on the non-float flattened comparator path."
      },
      "attrs": { "sorted": 1 },
      "inputs": { "x": { "dtype": "int32", "shape": [5], "data": { "kind": "values", "values": [3, 1, 3, 2, 1] } } },
      "outputs": {
        "y": { "dtype": "int32", "shape": [3], "tolerance": 0, "data": { "kind": "values", "values": [1, 2, 3] } },
        "indices": {
          "dtype": "uint32",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1, 3, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [2, 0, 2, 1, 0] }
        },
        "counts": { "dtype": "uint32", "shape": [3], "tolerance": 0, "data": { "kind": "values", "values": [2, 1, 2] } }
      }
    },
    {
      "name": "metadata_flat_indices_nd_input",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination while flattening an N-D input."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [4] },
        "indices": { "dtype": "uint32", "shape": [4], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_axis_negative_indices",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination and normalizes axis=-2 to axis 0 for a rank-2 input."
      },
      "attrs": { "axis": -2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 3],
          "data": { "kind": "values", "values": [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 2.0, 3.0, 4.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2, 3] },
        "indices": { "dtype": "uint32", "shape": [2], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_flat_inverse_nd_input",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination while flattening an N-D input."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [4] },
        "inverse_indices": { "dtype": "uint32", "shape": [6], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_axis_negative_inverse",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination and normalizes axis=-2 to axis 0 for a rank-2 input."
      },
      "attrs": { "axis": -2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 3],
          "data": { "kind": "values", "values": [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 2.0, 3.0, 4.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2, 3] },
        "inverse_indices": { "dtype": "uint32", "shape": [3], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_flat_counts_nd_input",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination while flattening an N-D input."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [4] },
        "counts": { "dtype": "uint32", "shape": [4], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_axis_negative_counts",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination and normalizes axis=-2 to axis 0 for a rank-2 input."
      },
      "attrs": { "axis": -2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 3],
          "data": { "kind": "values", "values": [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 2.0, 3.0, 4.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2, 3] },
        "counts": { "dtype": "uint32", "shape": [2], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_flat_indices_inverse_nd_input",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination while flattening an N-D input."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [4] },
        "indices": { "dtype": "uint32", "shape": [4], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [6], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_axis_negative_indices_inverse",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination and normalizes axis=-2 to axis 0 for a rank-2 input."
      },
      "attrs": { "axis": -2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 3],
          "data": { "kind": "values", "values": [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 2.0, 3.0, 4.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2, 3] },
        "indices": { "dtype": "uint32", "shape": [2], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [3], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_flat_indices_counts_nd_input",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination while flattening an N-D input."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [4] },
        "indices": { "dtype": "uint32", "shape": [4], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [4], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_axis_negative_indices_counts",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination and normalizes axis=-2 to axis 0 for a rank-2 input."
      },
      "attrs": { "axis": -2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 3],
          "data": { "kind": "values", "values": [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 2.0, 3.0, 4.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2, 3] },
        "indices": { "dtype": "uint32", "shape": [2], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [2], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_flat_inverse_counts_nd_input",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination while flattening an N-D input."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [4] },
        "inverse_indices": { "dtype": "uint32", "shape": [6], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [4], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_axis_negative_inverse_counts",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination and normalizes axis=-2 to axis 0 for a rank-2 input."
      },
      "attrs": { "axis": -2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 3],
          "data": { "kind": "values", "values": [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 2.0, 3.0, 4.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2, 3] },
        "inverse_indices": { "dtype": "uint32", "shape": [3], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [2], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_flat_all_nd_input",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination while flattening an N-D input."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 4.0, 3.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [4] },
        "indices": { "dtype": "uint32", "shape": [4], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [6], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [4], "tolerance": 0 }
      }
    },
    {
      "name": "metadata_axis_negative_all",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises the requested standard optional output combination and normalizes axis=-2 to axis 0 for a rank-2 input."
      },
      "attrs": { "axis": -2, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 3],
          "data": { "kind": "values", "values": [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 2.0, 3.0, 4.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2, 3] },
        "indices": { "dtype": "uint32", "shape": [2], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [3], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [2], "tolerance": 0 }
      }
    },
    {
      "name": "float16_sorted_subnormal_and_signed_zero",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Covers the standard float16 type with bit-preserving subnormal ordering and signed-zero equality."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [5],
          "data": { "kind": "values", "values": [0.0, -0.0, 5.960464477539063e-8, -5.960464477539063e-8, 0.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-5.960464477539063e-8, 0.0, 5.960464477539063e-8] }
        }
      }
    },
    {
      "name": "float16_nan_ordered_map_all_metadata",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Exercises float16 NaN lower-bound equivalence and every standard optional metadata output."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float16", "shape": [4], "data": { "kind": "values", "values": [5.0, "NaN", 1.0, 3.0] } }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [3], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [3], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [4], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [3], "tolerance": 0 }
      }
    },
    {
      "name": "float16_axis_unsorted_duplicate_rows",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Covers standard float16 axis-mode deduplication and first-occurrence output order."
      },
      "attrs": { "axis": 0, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [3, 2],
          "data": { "kind": "values", "values": [2.0, 1.0, 1.0, 3.0, 2.0, 1.0] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [2, 2], "tolerance": 0 } }
    },
    {
      "name": "int16_sorted_extremes",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Covers the standard int16 type at both representable extremes."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int16",
          "shape": [6],
          "data": { "kind": "values", "values": [32767, -32768, -1, 0, 32767, -32768] }
        }
      },
      "outputs": { "y": { "dtype": "int16", "shape": [4], "tolerance": 0 } }
    },
    {
      "name": "bool_unsorted_all_metadata",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__Unique.html",
        "notes": "Covers the standard bool type, first-occurrence order, and every optional metadata output."
      },
      "attrs": { "sorted": 0 },
      "inputs": { "x": { "dtype": "bool", "shape": [5], "data": { "kind": "values", "values": [1, 0, 1, 1, 0] } } },
      "outputs": {
        "y": { "dtype": "bool", "shape": [2], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [2], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [5], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [2], "tolerance": 0 }
      }
    },
    {
      "name": "axis0_f32_hash_sorted_duplicate_rows",
      "provenance": {
        "notes": "Float rows on the parallel axis hash route: 2560 rows cycling 64 distinct two-element patterns, deduplicated and lexicographically sorted through the canonical-bit comparators."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2560, 2],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_f32_hash_sorted_duplicate_rows_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [64, 2], "tolerance": 0 } }
    },
    {
      "name": "axis0_f32_hash_unsorted_first_occurrence",
      "provenance": {
        "notes": "A 2,560-row float input cycling 64 distinct two-element rows must emit them in first-occurrence order through the hash compaction scan."
      },
      "attrs": { "axis": 0, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2560, 2],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_f32_hash_sorted_duplicate_rows_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [64, 2], "tolerance": 0 } }
    },
    {
      "name": "axis0_f32_hash_sorted_zero_collapse_floor2048",
      "provenance": {
        "notes": "A [2048, 1] float32 tensor with axis=0 cycles a 32-value pattern 64 times; -0.0 (first) and 0.0 (later in the pattern) collapse to one signed-zero entry among 31 distinct values, sorted ascending."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2048, 1],
          "data": {
            "kind": "cycle",
            "values": [-0.0, -14.5125, -3.325, -4.6375, 10.4875, -5.95, 0.3, 16.7375, 4.2375, -10.8875, 12.8, 18.05, 7.8625, 14.1125, 5.55, -15.825, -8.2625, 6.55, -6.95, 0.0, -13.2, 2.925, -18.45, -9.575, -0.7, 1.6125, -2.0125, 9.175, -17.1375, -12.2, 11.8, 15.425]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [31, 1], "tolerance": 0 } }
    },
    {
      "name": "float16_axis0_hash_sorted",
      "provenance": {
        "notes": "f16 on the float axis hash route: 48 half-exact scalars exercise the 16-bit canonical key (vec2 pack, 16-bit sign fold) through hash, sort, and scatter."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [2560, 1],
          "data": {
            "kind": "cycle",
            "values": [-3.0, 1.75, -3.5, 0.5, 1.25, -2.75, -5.0, 1.0, -3.25, -4.25, 0.75, -4.5, -1.75, -1.0, -0.75, -5.25, 2.0, 5.75, 2.75, 2.5, 3.75, -5.75, -0.5, 3.5, -4.0, -2.0, -1.25, -5.5, 5.0, -2.25, 2.25, 4.75, 3.0, -6.0, -4.75, 5.5, 4.0, 1.5, -3.75, 4.25, 3.25, -0.25, 5.25, -1.5, -2.5, 0.25, 0.0, 4.5]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [48, 1], "tolerance": 0 } }
    },
    {
      "name": "axis1_f32_hash_sorted_outer2",
      "provenance": {
        "notes": "outer > 1 on the float axis hash route: axis 1 of a [2, 2560] tensor makes every slice span two strided elements, exercising the outer loop of the canonical slice comparators."
      },
      "attrs": { "axis": 1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 2560],
          "data": {
            "kind": "cycle",
            "values": [-50.0, 5.5, 25.0, -47.0, -36.5, 43.0, 46.0, -5.0, 35.5, 31.0, -20.0, 8.5, -2.0, -12.5, -29.0, 38.5, -39.5, 47.5, -14.0, 16.0, -32.0, 20.5, 13.0, -42.5, -24.5, -35.0, -9.5, 1.0, -44.0, -21.5, 32.5, 10.0, 17.5, -27.5, 23.5, 2.5, -6.5, 40.0, 28.0, -17.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [2, 40], "tolerance": 0 } }
    },
    {
      "name": "parallel_metadata_indices_int32_sorted",
      "provenance": {
        "notes": "A scrambled 65-value cycle over 512 elements gives uneven counts and makes first-occurrence order differ from sorted order. This case requests first indices from the parallel integer-dedup route."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [512],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "parallel_metadata_inverse_int32_unsorted",
      "provenance": {
        "notes": "A scrambled 65-value cycle over 512 elements gives uneven counts and makes first-occurrence order differ from sorted order. This case requests the inverse map from the parallel integer-dedup route."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [512],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [512] }
      }
    },
    {
      "name": "parallel_metadata_counts_int32_sorted",
      "provenance": {
        "notes": "A scrambled 65-value cycle over 512 elements gives uneven counts and makes first-occurrence order differ from sorted order. This case requests counts from the parallel integer-dedup route."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [512],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "parallel_metadata_indices_inverse_int32_unsorted",
      "provenance": {
        "notes": "A scrambled 65-value cycle over 512 elements gives uneven counts and makes first-occurrence order differ from sorted order. This case requests first indices and the inverse map from the parallel integer-dedup route."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [512],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] },
        "inverse_indices": { "dtype": "uint32", "shape": [512] }
      }
    },
    {
      "name": "parallel_metadata_indices_counts_int32_sorted",
      "provenance": {
        "notes": "A scrambled 65-value cycle over 512 elements gives uneven counts and makes first-occurrence order differ from sorted order. This case requests first indices and counts from the parallel integer-dedup route."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [512],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "parallel_metadata_inverse_counts_int32_unsorted",
      "provenance": {
        "notes": "A scrambled 65-value cycle over 512 elements gives uneven counts and makes first-occurrence order differ from sorted order. This case requests the inverse map and counts from the parallel integer-dedup route."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [512],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [512] },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "parallel_metadata_all_int32_sorted",
      "provenance": {
        "notes": "A scrambled 65-value cycle over 512 elements gives uneven counts and makes first-occurrence order differ from sorted order. This case requests first indices, the inverse map, and counts from the parallel integer-dedup route."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [512],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] },
        "inverse_indices": { "dtype": "uint32", "shape": [512] },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "hash_metadata_inverse_int32_unsorted",
      "provenance": {
        "notes": "The smallest hash-route input uses a scrambled 65-value cycle, giving uneven counts and distinct first-occurrence and sorted orders. This case requests the inverse map."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [32768] }
      }
    },
    {
      "name": "hash_metadata_counts_int32_sorted",
      "provenance": {
        "notes": "The smallest hash-route input uses a scrambled 65-value cycle, giving uneven counts and distinct first-occurrence and sorted orders. This case requests counts."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "hash_metadata_all_int32_unsorted",
      "provenance": {
        "notes": "The smallest hash-route input uses a scrambled 65-value cycle, giving uneven counts and distinct first-occurrence and sorted orders. This case requests first indices, the inverse map, and counts."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] },
        "inverse_indices": { "dtype": "uint32", "shape": [32768] },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "hash_metadata_indices_int32_sorted",
      "provenance": {
        "notes": "The smallest hash-route input uses a scrambled 65-value cycle, giving uneven counts and distinct first-occurrence and sorted orders. This case requests first indices."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "hash_metadata_indices_inverse_int32_unsorted",
      "provenance": {
        "notes": "The smallest hash-route input uses a scrambled 65-value cycle, giving uneven counts and distinct first-occurrence and sorted orders. This case requests first indices and the inverse map."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] },
        "inverse_indices": { "dtype": "uint32", "shape": [32768] }
      }
    },
    {
      "name": "hash_metadata_indices_counts_int32_sorted",
      "provenance": {
        "notes": "The smallest hash-route input uses a scrambled 65-value cycle, giving uneven counts and distinct first-occurrence and sorted orders. This case requests first indices and counts."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "indices": { "dtype": "uint32", "shape": [65] },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "hash_metadata_inverse_counts_int32_unsorted",
      "provenance": {
        "notes": "The smallest hash-route input uses a scrambled 65-value cycle, giving uneven counts and distinct first-occurrence and sorted orders. This case requests the inverse map and counts."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [32768],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/metadata_scrambled_cycle65" } }
        }
      },
      "outputs": {
        "y": { "dtype": "int32", "shape": [65], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [32768] },
        "counts": { "dtype": "uint32", "shape": [65] }
      }
    },
    {
      "name": "axis0_f32_rows70000_above_hash_ceiling",
      "provenance": {
        "notes": "A 70,000-row float input cycling eight one-element rows exercises large-axis hash deduplication and lexicographic sorted output."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [70000, 1],
          "data": { "kind": "cycle", "values": [-4.0, -2.5, -1.0, 0.0, 1.5, 2.0, 3.25, 8.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [8, 1], "tolerance": 0 } }
    },
    {
      "name": "flat_i32_70000_distinct_above_ceiling",
      "provenance": {
        "notes": "A flat 70,000-element input with every value distinct exercises large-output parallel deduplication and sorted emission."
      },
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [70000], "data": { "kind": "linspace", "start": -35000, "end": 34999 } }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [70000], "tolerance": 0 } }
    },
    {
      "name": "flat_i32_above_input_length_ceiling",
      "provenance": {
        "notes": "A 1,049,600-element class-label stream cycling six values exercises large-input parallel deduplication and first-occurrence output."
      },
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [1049600],
          "data": { "kind": "cycle", "values": [7, -3, 0, 11, -3, 42, 7, 5] }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [6], "tolerance": 0 } }
    },
    {
      "name": "hash_float32_sorted0_leading_nan_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["NaN", 5.0, 1.0, "NaN", "-Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1], "tolerance": 0, "allowNaN": true } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles [NaN, 5.0, 1.0, NaN, -Infinity], starting with a NaN; every later element collapses into that leading NaN, leaving a single-element NaN output."
      }
    },
    {
      "name": "hash_float32_sorted0_later_nan_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": [5.0, "NaN", 1.0, 3.0, "NaN", 1.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles [5.0, NaN, 1.0, 3.0, NaN, 1.0]; NaN never starts a new unique value once a real value exists, so the three real values appear in first-occurrence order: 5.0, 1.0, then 3.0."
      }
    },
    {
      "name": "hash_float32_sorted0_negative_zero_first_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": [-0.0, 0.0, 1e-40, -1e-40, "Infinity", "-Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles negative zero, positive zero, a subnormal magnitude (1e-40) and its negation, and both infinities; the two zeros collapse into one entry using the first-seen negative sign, giving five distinct values in first-occurrence order."
      }
    },
    {
      "name": "hash_float32_sorted0_positive_zero_first_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": [0.0, -0.0, -1e-40, 1e-40, "-Infinity", "Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles positive zero, negative zero, a subnormal magnitude (1e-40) and its negation, and both infinities; the two zeros collapse into one entry using the first-seen positive sign, giving five distinct values in first-occurrence order."
      }
    },
    {
      "name": "hash_float32_sorted0_infinity_duplicates_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["Infinity", "-Infinity", 2.0, -3.0, "Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles positive infinity, negative infinity, 2.0, and -3.0, with positive infinity repeated each period; the duplicate infinities collapse into one entry, giving four distinct values in first-occurrence order."
      }
    },
    {
      "name": "hash_float32_sorted1_leading_nan_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["NaN", 5.0, 1.0, "NaN", "-Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1], "tolerance": 0, "allowNaN": true } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles [NaN, 5.0, 1.0, NaN, -Infinity], starting with a NaN; every later element collapses into that leading NaN, leaving a single-element NaN output."
      }
    },
    {
      "name": "hash_float32_sorted1_later_nan_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": [5.0, "NaN", 1.0, 3.0, "NaN", 1.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles [5.0, NaN, 1.0, 3.0, NaN, 1.0]; because NaN never creates a new entry once a real value exists, only the three distinct real values 1.0, 3.0, and 5.0 appear, in ascending order."
      }
    },
    {
      "name": "hash_float32_sorted1_negative_zero_first_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": [-0.0, 0.0, 1e-40, -1e-40, "Infinity", "-Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles negative zero, positive zero, a subnormal magnitude (1e-40) and its negation, and both infinities; the two zeros collapse into one entry using the first-seen negative sign, giving five distinct values in ascending order."
      }
    },
    {
      "name": "hash_float32_sorted1_positive_zero_first_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": [0.0, -0.0, -1e-40, 1e-40, "-Infinity", "Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles positive zero, negative zero, a subnormal magnitude (1e-40) and its negation, and both infinities; the two zeros collapse into one entry using the first-seen positive sign, giving five distinct values in ascending order."
      }
    },
    {
      "name": "hash_float32_sorted1_infinity_duplicates_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["Infinity", "-Infinity", 2.0, -3.0, "Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float32 input cycles positive infinity, negative infinity, 2.0, and -3.0, with positive infinity repeated each period; the duplicate infinities collapse into one entry, giving four distinct values in ascending order."
      }
    },
    {
      "name": "hash_float16_sorted0_leading_nan_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["NaN", 5.0, 1.0, "NaN", "-Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [1], "tolerance": 0, "allowNaN": true } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles [NaN, 5.0, 1.0, NaN, -Infinity], starting with a NaN; every later element collapses into that leading NaN, leaving a single-element NaN output."
      }
    },
    {
      "name": "hash_float16_sorted0_later_nan_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "cycle", "values": [5.0, "NaN", 1.0, 3.0, "NaN", 1.0] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [3], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles [5.0, NaN, 1.0, 3.0, NaN, 1.0]; NaN never starts a new unique value once a real value exists, so the three real values appear in first-occurrence order: 5.0, 1.0, then 3.0."
      }
    },
    {
      "name": "hash_float16_sorted0_negative_zero_first_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "cycle",
            "values": [-0.0, 0.0, 5.960464477539063e-8, -5.960464477539063e-8, "Infinity", "-Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles negative zero, positive zero, the smallest float16 subnormal and its negation, and both infinities; the two zeros collapse into one entry using the first-seen negative sign, giving five distinct values in first-occurrence order."
      }
    },
    {
      "name": "hash_float16_sorted0_positive_zero_first_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "cycle",
            "values": [0.0, -0.0, -5.960464477539063e-8, 5.960464477539063e-8, "-Infinity", "Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles positive zero, negative zero, the smallest float16 subnormal and its negation, and both infinities; the two zeros collapse into one entry using the first-seen positive sign, giving five distinct values in first-occurrence order."
      }
    },
    {
      "name": "hash_float16_sorted0_infinity_duplicates_tail33",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["Infinity", "-Infinity", 2.0, -3.0, "Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [4], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles positive infinity, negative infinity, 2.0, and -3.0, with positive infinity repeated each period; the duplicate infinities collapse into one entry, giving four distinct values in first-occurrence order."
      }
    },
    {
      "name": "hash_float16_sorted1_leading_nan_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["NaN", 5.0, 1.0, "NaN", "-Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [1], "tolerance": 0, "allowNaN": true } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles [NaN, 5.0, 1.0, NaN, -Infinity], starting with a NaN; every later element collapses into that leading NaN, leaving a single-element NaN output."
      }
    },
    {
      "name": "hash_float16_sorted1_later_nan_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "cycle", "values": [5.0, "NaN", 1.0, 3.0, "NaN", 1.0] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [3], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles [5.0, NaN, 1.0, 3.0, NaN, 1.0]; because NaN never creates a new entry once a real value exists, only the three distinct real values 1.0, 3.0, and 5.0 appear, in ascending order."
      }
    },
    {
      "name": "hash_float16_sorted1_negative_zero_first_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "cycle",
            "values": [-0.0, 0.0, 5.960464477539063e-8, -5.960464477539063e-8, "Infinity", "-Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles negative zero, positive zero, the smallest float16 subnormal and its negation, and both infinities; the two zeros collapse into one entry using the first-seen negative sign, giving five distinct values in ascending order."
      }
    },
    {
      "name": "hash_float16_sorted1_positive_zero_first_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "cycle",
            "values": [0.0, -0.0, -5.960464477539063e-8, 5.960464477539063e-8, "-Infinity", "Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [5], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles positive zero, negative zero, the smallest float16 subnormal and its negation, and both infinities; the two zeros collapse into one entry using the first-seen positive sign, giving five distinct values in ascending order."
      }
    },
    {
      "name": "hash_float16_sorted1_infinity_duplicates_tail33",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "cycle", "values": ["Infinity", "-Infinity", 2.0, -3.0, "Infinity"] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [4], "tolerance": 0 } },
      "tunables": { "HASH_MIN_INPUT": 32 },
      "provenance": {
        "notes": "A 33-element float16 input cycles positive infinity, negative infinity, 2.0, and -3.0, with positive infinity repeated each period; the duplicate infinities collapse into one entry, giving four distinct values in ascending order."
      }
    },
    {
      "name": "hash_float32_sorted0_compact_first_chunk_incomplete_tail33",
      "provenance": {
        "notes": "With 32 invocations, the first compact chunk contains only the representative 7. The distinct final -3 must be consumed from the second chunk before sorting or preserving appearance order."
      },
      "attrs": { "sorted": 0 },
      "tunables": { "WORKGROUP_SIZE": 32, "HASH_MIN_INPUT": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/compact_incomplete_first_chunk33" } }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [7.0, -3.0] } }
      }
    },
    {
      "name": "hash_float32_sorted1_compact_first_chunk_incomplete_tail33",
      "provenance": {
        "notes": "With 32 invocations, the first compact chunk contains only the representative 7. The distinct final -3 must be consumed from the second chunk before sorting or preserving appearance order."
      },
      "attrs": { "sorted": 1 },
      "tunables": { "WORKGROUP_SIZE": 32, "HASH_MIN_INPUT": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/compact_incomplete_first_chunk33" } }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [-3.0, 7.0] } }
      }
    },
    {
      "name": "hash_float16_sorted0_compact_first_chunk_incomplete_tail33",
      "provenance": {
        "notes": "With 32 invocations, the first compact chunk contains only the representative 7. The distinct final -3 must be consumed from the second chunk before sorting or preserving appearance order."
      },
      "attrs": { "sorted": 0 },
      "tunables": { "WORKGROUP_SIZE": 32, "HASH_MIN_INPUT": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/compact_incomplete_first_chunk33" } }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [7.0, -3.0] } }
      }
    },
    {
      "name": "hash_float16_sorted1_compact_first_chunk_incomplete_tail33",
      "provenance": {
        "notes": "With 32 invocations, the first compact chunk contains only the representative 7. The distinct final -3 must be consumed from the second chunk before sorting or preserving appearance order."
      },
      "attrs": { "sorted": 1 },
      "tunables": { "WORKGROUP_SIZE": 32, "HASH_MIN_INPUT": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/compact_incomplete_first_chunk33" } }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [-3.0, 7.0] } }
      }
    },
    {
      "name": "hybrid_sort_i32_extremes_sentinel_duplicates",
      "attrs": { "sorted": 1 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [8],
          "data": { "kind": "values", "values": [-1, 2147483647, -2147483648, 9, 0, -1, 9, -2147483648] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [5],
          "data": { "kind": "values", "values": [-2147483648, -1, 0, 9, 2147483647] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "An 8-element int32 input with INT32_MIN, INT32_MAX, and duplicate -1, 9, and INT32_MIN values produces a sorted 5-element unique output whose length equals the unique count, with no padding."
      }
    },
    {
      "name": "hybrid_sort_u32_real_max_before_padding",
      "attrs": { "sorted": 1 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [8],
          "data": { "kind": "values", "values": [4294967295, 0, 2147483648, 4, 1, 4294967295, 0, 4] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint32",
          "shape": [5],
          "data": { "kind": "values", "values": [0, 1, 4, 2147483648, 4294967295] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "An 8-element uint32 input with UINT32_MAX, the int32/uint32 boundary value 2,147,483,648, and duplicate UINT32_MAX, 0, and 4 values produces a sorted 5-element unique output whose length equals the unique count, with no padding."
      }
    },
    {
      "name": "hybrid_sort_i32_underfilled_capacity_zero_tail",
      "attrs": { "sorted": 1 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [12],
          "data": { "kind": "values", "values": [-1, 2147483647, -2147483648, 9, 0, -1, 9, -2147483648, 9, 9, 0, -1] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [7],
          "data": { "kind": "values", "values": [-2147483648, -1, 0, 9, 2147483647, 0, 0] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "A bounded integer input includes duplicate and padded records. Exact integer outputs pin sentinel, padding, and first-occurrence behavior."
      }
    },
    {
      "name": "hash_global_nonpower_tile_i32_extremes_sentinel_duplicates",
      "attrs": { "sorted": 1 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32,
        "GLOBAL_SORT_TILE": 3
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [8],
          "data": { "kind": "values", "values": [-1, 2147483647, -2147483648, 9, 0, -1, 9, -2147483648] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [5],
          "data": { "kind": "values", "values": [-2147483648, -1, 0, 9, 2147483647] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "An 8-element int32 input with INT32_MIN, INT32_MAX, and duplicate -1, 9, and INT32_MIN values produces a sorted 5-element unique output whose length equals the unique count, with no padding."
      }
    },
    {
      "name": "hash_global_nonpower_tile_u32_real_max_before_padding",
      "attrs": { "sorted": 1 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32,
        "GLOBAL_SORT_TILE": 3
      },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [8],
          "data": { "kind": "values", "values": [4294967295, 0, 2147483648, 4, 1, 4294967295, 0, 4] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint32",
          "shape": [5],
          "data": { "kind": "values", "values": [0, 1, 4, 2147483648, 4294967295] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "An 8-element uint32 input with UINT32_MAX, the int32/uint32 boundary value 2,147,483,648, and duplicate UINT32_MAX, 0, and 4 values produces a sorted 5-element unique output whose length equals the unique count, with no padding."
      }
    },
    {
      "name": "hash_global_unsorted_first_seen_sentinel_zero_tail",
      "attrs": { "sorted": 0 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [12],
          "data": { "kind": "values", "values": [-1, 2147483647, -2147483648, 9, 0, -1, 9, -2147483648, 9, 9, 0, -1] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [7],
          "data": { "kind": "values", "values": [-1, 2147483647, -2147483648, 9, 0, 0, 0] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "A bounded integer input includes duplicate and padded records. Exact integer outputs pin sentinel, padding, and first-occurrence behavior. Unsorted output preserves appearance order, not numeric order, and zero-fills excess capacity."
      }
    },
    {
      "name": "hybrid_sort_network_tile1",
      "attrs": { "sorted": 1 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32,
        "GLOBAL_SORT_TILE": 1
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [8],
          "data": { "kind": "values", "values": [-1, 2147483647, -2147483648, 9, 0, -1, 9, -2147483648] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [5],
          "data": { "kind": "values", "values": [-2147483648, -1, 0, 9, 2147483647] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "An 8-element int32 input with INT32_MIN, INT32_MAX, and duplicate -1, 9, and INT32_MIN values produces a sorted 5-element unique output whose length equals the unique count, with no padding."
      }
    },
    {
      "name": "hybrid_sort_network_tile2",
      "attrs": { "sorted": 1 },
      "tunables": {
        "HASH_MIN_INPUT": 1,
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_SORT_MAX_CAPACITY": 1,
        "SORT_WORKGROUP": 32,
        "WORKGROUP_SIZE": 32,
        "GLOBAL_SORT_TILE": 2
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [8],
          "data": { "kind": "values", "values": [-1, 2147483647, -2147483648, 9, 0, -1, 9, -2147483648] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [5],
          "data": { "kind": "values", "values": [-2147483648, -1, 0, 9, 2147483647] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "An 8-element int32 input with INT32_MIN, INT32_MAX, and duplicate -1, 9, and INT32_MIN values produces a sorted 5-element unique output whose length equals the unique count, with no padding."
      }
    },
    {
      "name": "hybrid_sort_default_tile512_sorted513_signed_boundary",
      "attrs": { "sorted": 1 },
      "tunables": { "HASH_MIN_INPUT": 32, "LOCAL_SORT_CROSSOVER": 32, "HASH_SORT_MAX_CAPACITY": 32 },
      "inputs": { "x": { "dtype": "int32", "shape": [513], "data": { "kind": "linspace", "start": 256, "end": -256 } } },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [513],
          "tolerance": 0,
          "data": { "kind": "linspace", "start": -256, "end": 256 }
        }
      },
      "provenance": {
        "notes": "A compact integer input spans a 512-record boundary. 513 distinct descending signed values cross two 512-record padded sort tiles and exercise the final real/padding boundary."
      }
    },
    {
      "name": "axis_scalar_hash_float32_finite_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 7, 1],
          "data": { "kind": "values", "values": [5.0, 1.0, 5.0, 3.0, -2.0, 1.0, 7.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_finite_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 7, 1],
          "data": { "kind": "values", "values": [5.0, 1.0, 5.0, 3.0, -2.0, 1.0, 7.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_later_nan_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 8, 1],
          "data": { "kind": "values", "values": [5.0, "NaN", 1.0, "NaN", 3.0, -2.0, "NaN", 5.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 4, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [8], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_later_nan_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 8, 1],
          "data": { "kind": "values", "values": [5.0, "NaN", 1.0, "NaN", 3.0, -2.0, "NaN", 5.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 4, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [8], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_leading_nan_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "data": { "kind": "values", "values": ["NaN", 5.0, 1.0, "NaN", -2.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 1, 1], "tolerance": 0, "allowNaN": true },
        "inverse_indices": { "dtype": "uint32", "shape": [5], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_leading_nan_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "data": { "kind": "values", "values": ["NaN", 5.0, 1.0, "NaN", -2.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 1, 1], "tolerance": 0, "allowNaN": true },
        "inverse_indices": { "dtype": "uint32", "shape": [5], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_local_sort_below_crossover_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "provenance": {
        "notes": "A [1, 7, 1] float32 tensor's axis=-2 (dimension 1) holds 7 scalar slices with duplicate 5.0 and 1.0 pairs; the 5 unique slices are ascending, and inverse_indices maps every original slice back to its correct entry."
      },
      "tunables": { "LOCAL_SORT_CROSSOVER": 6, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 7, 1],
          "data": { "kind": "values", "values": [5.0, 1.0, 5.0, 3.0, -2.0, 1.0, 7.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_zero_subnormal_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
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          "shape": [1, 9, 1],
          "data": {
            "kind": "values",
            "values": [-0.0, 0.0, 1.401298464324817e-45, -1.401298464324817e-45, 1.401298464324817e-45, "Infinity", "-Infinity", 1.0, -1.0]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 7, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [9], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_zero_subnormal_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 9, 1],
          "data": {
            "kind": "values",
            "values": [-0.0, 0.0, 1.401298464324817e-45, -1.401298464324817e-45, 1.401298464324817e-45, "Infinity", "-Infinity", 1.0, -1.0]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 7, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [9], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_zero_reverse_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 7, 1],
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            "kind": "values",
            "values": [0.0, -0.0, -1.401298464324817e-45, 1.401298464324817e-45, 1.0, -1.0, "NaN"]
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      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float32_zero_reverse_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 7, 1],
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      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_finite_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 7, 1],
          "data": { "kind": "values", "values": [5.0, 1.0, 5.0, 3.0, -2.0, 1.0, 7.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_finite_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 7, 1],
          "data": { "kind": "values", "values": [5.0, 1.0, 5.0, 3.0, -2.0, 1.0, 7.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_later_nan_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 8, 1],
          "data": { "kind": "values", "values": [5.0, "NaN", 1.0, "NaN", 3.0, -2.0, "NaN", 5.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 4, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [8], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_later_nan_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 8, 1],
          "data": { "kind": "values", "values": [5.0, "NaN", 1.0, "NaN", 3.0, -2.0, "NaN", 5.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 4, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [8], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_leading_nan_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "data": { "kind": "values", "values": ["NaN", 5.0, 1.0, "NaN", -2.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 1, 1], "tolerance": 0, "allowNaN": true },
        "inverse_indices": { "dtype": "uint32", "shape": [5], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_leading_nan_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "data": { "kind": "values", "values": ["NaN", 5.0, 1.0, "NaN", -2.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 1, 1], "tolerance": 0, "allowNaN": true },
        "inverse_indices": { "dtype": "uint32", "shape": [5], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_local_sort_below_crossover_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "provenance": {
        "notes": "A [1, 7, 1] float16 tensor's axis=-2 (dimension 1) holds 7 scalar slices with duplicate 5.0 and 1.0 pairs; the 5 unique slices are ascending, and inverse_indices maps every original slice back to its correct entry."
      },
      "tunables": { "LOCAL_SORT_CROSSOVER": 6, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 7, 1],
          "data": { "kind": "values", "values": [5.0, 1.0, 5.0, 3.0, -2.0, 1.0, 7.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_zero_subnormal_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 9, 1],
          "data": {
            "kind": "values",
            "values": [-0.0, 0.0, 5.960464477539063e-8, -5.960464477539063e-8, 5.960464477539063e-8, "Infinity", "-Infinity", 1.0, -1.0]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 7, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [9], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_zero_subnormal_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 9, 1],
          "data": {
            "kind": "values",
            "values": [-0.0, 0.0, 5.960464477539063e-8, -5.960464477539063e-8, 5.960464477539063e-8, "Infinity", "-Infinity", 1.0, -1.0]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 7, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [9], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_zero_reverse_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 7, 1],
          "data": {
            "kind": "values",
            "values": [0.0, -0.0, -5.960464477539063e-8, 5.960464477539063e-8, 1.0, -1.0, "NaN"]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "axis_scalar_hash_float16_zero_reverse_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 7, 1],
          "data": {
            "kind": "values",
            "values": [0.0, -0.0, -5.960464477539063e-8, 5.960464477539063e-8, 1.0, -1.0, "NaN"]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "float16", "shape": [1, 5, 1], "tolerance": 0 },
        "inverse_indices": { "dtype": "uint32", "shape": [7], "tolerance": 0 }
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask0_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask0_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask1_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask1_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask2_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask2_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask3_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask3_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask4_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask4_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask5_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask5_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask6_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask6_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask0_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask0_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask1_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask1_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask2_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask2_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask3_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask3_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask4_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask4_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask5_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask5_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask6_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask6_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, -0.0, 1.0, -3.0, 2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 6] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [10, 9, 5, 5, 4] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask0_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-3.0, -0.0, 1.0, 2.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [3, 1, 2, 6, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_finite_mask2_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 9, 5, 4, 10] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_int32_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int32_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-1, -2147483648, 2147483647, 0, 7] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 5] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int32_finite_mask7_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [11, 6, 6, 5, 5] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_int32_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int32_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-2147483648, -1, 0, 7, 2147483647] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1, 0, 3, 5, 2] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": [1, 0, 4, 2, 1, 3, 1, 0, 4, 2, 1, 3, 1, 0, 4, 2, 1, 3, 1, 0, 4, 2, 1, 3, 1, 0, 4, 2, 1, 3, 1, 0, 4]
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [6, 11, 5, 5, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_uint32_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_uint32_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [4294967295, 0, 2147483648, 7, 2147483647] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 5] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int32_finite_mask7_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [11, 6, 6, 5, 5] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_uint32_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_uint32_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint32",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 7, 2147483647, 2147483648, 4294967295] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1, 3, 5, 2, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_uint32_finite_mask7_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [6, 5, 5, 6, 11] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_int16_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int16_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int16",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-32768, 32767, -1, 0, 7] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 5] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int32_finite_mask7_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [11, 6, 6, 5, 5] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_int16_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int16_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int16",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-32768, -1, 0, 7, 32767] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 2, 3, 5, 1] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int16_finite_mask7_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [11, 6, 5, 5, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_int8_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int8",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int8_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int8",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-128, 127, -1, 0, 7] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 5] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int32_finite_mask7_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [11, 6, 6, 5, 5] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_int8_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "int8",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int8_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "int8",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-128, -1, 0, 7, 127] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 2, 3, 5, 1] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int16_finite_mask7_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [11, 6, 5, 5, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_uint8_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "uint8",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_uint8_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint8",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [255, 0, 128, 7, 127] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 1, 2, 3, 5] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_int32_finite_mask7_flat_sorted0_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [11, 6, 6, 5, 5] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_uint8_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "uint8",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_uint8_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint8",
          "shape": [1, 5, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 7, 127, 128, 255] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1, 3, 5, 2, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_uint32_finite_mask7_axis_sorted1_output_inverse_indices" }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [5],
          "tolerance": 0,
          "data": { "kind": "values", "values": [6, 5, 5, 6, 11] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_bool_finite_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "bool",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_bool_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": { "dtype": "bool", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [1, 0] } },
        "indices": { "dtype": "uint32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [0, 1] } },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": [0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0]
          }
        },
        "counts": { "dtype": "uint32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [22, 11] } }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_bool_finite_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "bool",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_bool_finite_mask7_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": { "dtype": "bool", "shape": [1, 2, 1], "tolerance": 0, "data": { "kind": "values", "values": [0, 1] } },
        "indices": { "dtype": "uint32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [1, 0] } },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_bool_finite_mask7_flat_sorted0_input_x" }
          }
        },
        "counts": { "dtype": "uint32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [11, 22] } }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_later_nan_mask4_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0, 3.0, -2.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [6, 6, 5, 16] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_later_nan_mask4_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 4, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-2.0, 1.0, 3.0, 5.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [16, 6, 5, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_later_nan_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0, 3.0, -2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 2, 4, 5] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask7_flat_sorted0_output_inverse_indices"
            }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [6, 6, 5, 16] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_later_nan_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 4, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-2.0, 1.0, 3.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 2, 4, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask7_axis_sorted1_output_inverse_indices"
            }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [16, 6, 5, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_leading_nan_mask5_axis_sorted0",
      "attrs": { "sorted": 0, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_leading_nan_mask7_axis_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 1, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN"] },
          "allowNaN": true
        },
        "indices": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [0] } },
        "counts": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [33] } }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float32_leading_nan_mask5_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_leading_nan_mask7_axis_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 1, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN"] },
          "allowNaN": true
        },
        "indices": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [0] } },
        "counts": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [33] } }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_later_nan_mask4_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0, 3.0, -2.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [6, 6, 5, 16] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_later_nan_mask4_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 4, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-2.0, 1.0, 3.0, 5.0] }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [16, 6, 5, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_later_nan_mask7_flat_sorted0",
      "attrs": { "sorted": 0 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0, 3.0, -2.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0, 2, 4, 5] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask7_flat_sorted0_output_inverse_indices"
            }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [6, 6, 5, 16] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_later_nan_mask7_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask4_flat_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 4, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [-2.0, 1.0, 3.0, 5.0] }
        },
        "indices": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5, 2, 4, 0] }
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [33],
          "tolerance": 0,
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/scalar_hash_float32_later_nan_mask7_axis_sorted1_output_inverse_indices"
            }
          }
        },
        "counts": {
          "dtype": "uint32",
          "shape": [4],
          "tolerance": 0,
          "data": { "kind": "values", "values": [16, 6, 5, 6] }
        }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_leading_nan_mask5_axis_sorted0",
      "attrs": { "sorted": 0, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_leading_nan_mask7_axis_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 1, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN"] },
          "allowNaN": true
        },
        "indices": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [0] } },
        "counts": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [33] } }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "scalar_hash_float16_leading_nan_mask5_axis_sorted1",
      "attrs": { "sorted": 1, "axis": -2 },
      "tunables": {
        "PARALLEL_SCAN_MIN_CHUNKS": 0,
        "LOCAL_SORT_CROSSOVER": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 4
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 33, 1],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/scalar_hash_float32_leading_nan_mask7_axis_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 1, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN"] },
          "allowNaN": true
        },
        "indices": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [0] } },
        "counts": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [33] } }
      },
      "provenance": {
        "notes": "Exact ordered-insertion expectations for all scalar output masks. Integer -1/max uint32 exercises EMPTY side storage; float signed zero retains its first representative. Leading NaN exercises the exact one-class contract."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_head_later_inner_sorted0",
      "attrs": { "axis": 0, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_head_later_inner_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 0.0, 1.0, 0.0, 3.0, 0.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_suffix_ignored_by_head_inner_sorted0",
      "attrs": { "axis": 0, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_ignored_by_head_inner_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, "NaN", 2.0, 0.0, 3.0, 9.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_suffix_later_outer_sorted0",
      "attrs": { "axis": -1, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_later_outer_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 1.0, 0.0, 5.0, 3.0, 0.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_leading_single_bucket_outer_sorted0",
      "attrs": { "axis": -1, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_leading_single_bucket_outer_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN", 3.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_head_later_inner_sorted1",
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_head_later_inner_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 0.0, 3.0, 0.0, 5.0, 0.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_suffix_ignored_by_head_inner_sorted1",
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_ignored_by_head_inner_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, "NaN", 2.0, 0.0, 3.0, 9.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_suffix_later_outer_sorted1",
      "attrs": { "axis": -1, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_later_outer_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 0.0, 3.0, 5.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float32_nan_leading_single_bucket_outer_sorted1",
      "attrs": { "axis": -1, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_leading_single_bucket_outer_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN", 3.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_head_later_inner_sorted0",
      "attrs": { "axis": 0, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_head_later_inner_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 0.0, 1.0, 0.0, 3.0, 0.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_suffix_ignored_by_head_inner_sorted0",
      "attrs": { "axis": 0, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_ignored_by_head_inner_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, "NaN", 2.0, 0.0, 3.0, 9.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_suffix_later_outer_sorted0",
      "attrs": { "axis": -1, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_later_outer_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [2, 3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 1.0, 0.0, 5.0, 3.0, 0.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_leading_single_bucket_outer_sorted0",
      "attrs": { "axis": -1, "sorted": 0 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_leading_single_bucket_outer_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN", 3.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_head_later_inner_sorted1",
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_head_later_inner_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 0.0, 3.0, 0.0, 5.0, 0.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_suffix_ignored_by_head_inner_sorted1",
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [33, 2],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_ignored_by_head_inner_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [3, 2],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, "NaN", 2.0, 0.0, 3.0, 9.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_suffix_later_outer_sorted1",
      "attrs": { "axis": -1, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_suffix_later_outer_sorted0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [2, 3],
          "tolerance": 0,
          "data": { "kind": "values", "values": [0.0, 1.0, 1.0, 0.0, 3.0, 5.0] }
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "axis_nan_ordered_y_float16_nan_leading_single_bucket_outer_sorted1",
      "attrs": { "axis": -1, "sorted": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [2, 33],
          "data": {
            "kind": "values",
            "values": {
              "$ref": "#/fixtureArrays/axis_nan_ordered_y_float32_nan_leading_single_bucket_outer_sorted0_input_x"
            }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": ["NaN", 3.0] },
          "allowNaN": true
        }
      },
      "provenance": {
        "notes": "Y-only multi-element axis ordered-map reference with NaN at the deciding coordinate, after an earlier decisive coordinate, or in the initial representative. Outer/inner layouts preserve the same lexicographic slice values."
      }
    },
    {
      "name": "scalar_hash_scan_float32_n31_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": {
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_MIN_INPUT": 1,
        "WORKGROUP_SIZE": 32,
        "SORT_WORKGROUP": 32,
        "GLOBAL_SORT_TILE": 512,
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      },
      "provenance": {
        "notes": "A rank-4 float32 tensor of shape [1, 1, 256, 1] holds 256 scalar slices along axis -2: integers 0 through 254 once each, plus a repeated 0, producing 255 unique slices in ascending order."
      }
    },
    {
      "name": "scalar_hash_scan_float32_n257_sorted0",
      "attrs": { "axis": -2, "sorted": 0 },
      "tunables": {
        "LOCAL_SORT_CROSSOVER": 1,
        "HASH_MIN_INPUT": 1,
        "WORKGROUP_SIZE": 256,
        "SORT_WORKGROUP": 256,
        "GLOBAL_SORT_TILE": 512,
        "PARALLEL_SCAN_MIN_CHUNKS": 0
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        "x": {
          "dtype": "float32",
          "shape": [1, 1, 257, 1],
          "data": {
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            "values": { "$ref": "#/fixtureArrays/scalar_hash_scan_float32_n257_sorted0_input_x" }
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      "outputs": {
        "y": {
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          "tolerance": 0,
          "data": {
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      },
      "provenance": {
        "notes": "A rank-4 float32 tensor of shape [1, 1, 257, 1] holds 257 scalar slices along axis -2: integers 0 through 255 once each, plus a repeated 0, producing 256 unique slices in first-occurrence order."
      }
    },
    {
      "name": "scalar_hash_scan_float32_n257_sorted1",
      "attrs": { "axis": -2, "sorted": 1 },
      "tunables": {
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        "PARALLEL_SCAN_MIN_CHUNKS": 0
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            "values": { "$ref": "#/fixtureArrays/scalar_hash_scan_float32_n257_sorted0_input_x" }
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      "outputs": {
        "y": {
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      "provenance": {
        "notes": "A rank-4 float32 tensor of shape [1, 1, 257, 1] holds 257 scalar slices along axis -2: integers 0 through 255 once each, plus a repeated 0, producing 256 unique slices in ascending order."
      }
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    {
      "name": "scalar_hash_prefix_chunks_sparse_heads_n1023_sorted0",
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          "data": { "kind": "values", "values": [5, 3, 7, 1] }
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        "notes": "A rank-4 int32 tensor of shape [1, 1, 1023, 1] holds 1023 axis=-2 scalar slices, all value 5 except singletons 3, 7, and 1 at positions 32, 64, and the final index; the four distinct values yield a 4-element output in first-occurrence order."
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            "values": { "$ref": "#/fixtureArrays/scalar_hash_prefix_chunks_sparse_heads_n1023_sorted0_input_x" }
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          "dtype": "int32",
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          "tolerance": 0,
          "data": { "kind": "values", "values": [1, 3, 5, 7] }
        }
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      "provenance": {
        "notes": "A rank-4 int32 tensor of shape [1, 1, 1023, 1] holds 1023 axis=-2 scalar slices, all value 5 except singletons 3, 7, and 1 at positions 32, 64, and the final index; the four distinct values yield a 4-element output in ascending order."
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            "values": { "$ref": "#/fixtureArrays/scalar_hash_prefix_chunks_sparse_heads_n1024_sorted0_input_x" }
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        "notes": "A rank-4 int32 tensor of shape [1, 1, 1024, 1] holds 1024 axis=-2 scalar slices, all value 5 except singletons 3, 7, and 1 at positions 32, 64, and the final index; the four distinct values yield a 4-element output in first-occurrence order."
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        "notes": "A rank-4 int32 tensor of shape [1, 1, 1024, 1] holds 1024 axis=-2 scalar slices, all value 5 except singletons 3, 7, and 1 at positions 32, 64, and the final index; the four distinct values yield a 4-element output in ascending order."
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        "notes": "A rank-4 int32 tensor of shape [1, 1, 1025, 1] holds 1025 axis=-2 scalar slices, all value 5 except singletons 3, 7, and 1 at positions 32, 64, and the final index; the four distinct values yield a 4-element output in first-occurrence order."
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        "GLOBAL_SORT_TILE": 512,
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            "values": { "$ref": "#/fixtureArrays/scalar_hash_prefix_chunks_sparse_heads_n1025_sorted0_input_x" }
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          "data": { "kind": "values", "values": [1, 3, 5, 7] }
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        "notes": "A rank-4 int32 tensor of shape [1, 1, 1025, 1] holds 1025 axis=-2 scalar slices, all value 5 except singletons 3, 7, and 1 at positions 32, 64, and the final index; the four distinct values yield a 4-element output in ascending order."
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    },
    {
      "name": "scalar_hash_y_float32_axis_scalar_later_nan_sorted0",
      "attrs": { "sorted": 0, "axis": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "HASH_MIN_INPUT": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [1, 3, 1], "data": { "kind": "values", "values": [5.0, "NaN", 1.0] } }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0] }
        }
      },
      "provenance": {
        "notes": "A [1, 3, 1] float32 tensor's axis=1 holds scalar slices 5.0, NaN, 1.0; the NaN does not introduce a new unique value, leaving a 2-slice first-occurrence output of [5.0, 1.0]."
      }
    },
    {
      "name": "scalar_hash_y_float32_axis_scalar_later_nan_sorted1",
      "attrs": { "sorted": 1, "axis": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "HASH_MIN_INPUT": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [1, 3, 1], "data": { "kind": "values", "values": [5.0, "NaN", 1.0] } }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [1, 2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 5.0] }
        }
      },
      "provenance": {
        "notes": "A [1, 3, 1] float32 tensor's axis=1 holds scalar slices 5.0, NaN, 1.0; the NaN does not introduce a new unique value, leaving a 2-slice ascending output of [1.0, 5.0]."
      }
    },
    {
      "name": "scalar_hash_y_float16_axis_scalar_later_nan_sorted0",
      "attrs": { "sorted": 0, "axis": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "HASH_MIN_INPUT": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": { "dtype": "float16", "shape": [1, 3, 1], "data": { "kind": "values", "values": [5.0, "NaN", 1.0] } }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [5.0, 1.0] }
        }
      },
      "provenance": {
        "notes": "A [1, 3, 1] float16 tensor's axis=1 holds scalar slices 5.0, NaN, 1.0; the NaN does not introduce a new unique value, leaving a 2-slice first-occurrence output of [5.0, 1.0]."
      }
    },
    {
      "name": "scalar_hash_y_float16_axis_scalar_later_nan_sorted1",
      "attrs": { "sorted": 1, "axis": 1 },
      "tunables": { "LOCAL_SORT_CROSSOVER": 1, "HASH_MIN_INPUT": 1, "WORKGROUP_SIZE": 32, "SORT_WORKGROUP": 32 },
      "inputs": {
        "x": { "dtype": "float16", "shape": [1, 3, 1], "data": { "kind": "values", "values": [5.0, "NaN", 1.0] } }
      },
      "outputs": {
        "y": {
          "dtype": "float16",
          "shape": [1, 2, 1],
          "tolerance": 0,
          "data": { "kind": "values", "values": [1.0, 5.0] }
        }
      },
      "provenance": {
        "notes": "A [1, 3, 1] float16 tensor's axis=1 holds scalar slices 5.0, NaN, 1.0; the NaN does not introduce a new unique value, leaving a 2-slice ascending output of [1.0, 5.0]."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask0",
      "attrs": { "axis": 1, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 5, 3],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/single_class_axis1_outer2_inner3_mask0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask1",
      "attrs": { "axis": 1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 5, 3],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/single_class_axis1_outer2_inner3_mask0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        },
        "indices": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [0] }, "tolerance": 0 }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask2",
      "attrs": { "axis": 1, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [1],
          "data": { "kind": "values", "values": [0] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask3",
      "attrs": { "axis": 1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        },
        "indices": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [0] }, "tolerance": 0 },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [1],
          "data": { "kind": "values", "values": [0] },
          "tolerance": 0
        }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask4",
      "attrs": { "axis": 1, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 5, 3],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/single_class_axis1_outer2_inner3_mask0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        },
        "counts": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [5] }, "tolerance": 0 }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask5",
      "attrs": { "axis": 1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 5, 3],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/single_class_axis1_outer2_inner3_mask0_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        },
        "indices": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [0] }, "tolerance": 0 },
        "counts": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [5] }, "tolerance": 0 }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask6",
      "attrs": { "axis": 1, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [1],
          "data": { "kind": "values", "values": [0] },
          "tolerance": 0
        },
        "counts": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [1] }, "tolerance": 0 }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "single_class_axis1_outer2_inner3_mask7",
      "attrs": { "axis": 1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] }
        }
      },
      "outputs": {
        "y": {
          "dtype": "float32",
          "shape": [2, 1, 3],
          "data": { "kind": "values", "values": [7.0, 2.0, 5.0, 11.0, 3.0, 2.0] },
          "tolerance": 0
        },
        "indices": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [0] }, "tolerance": 0 },
        "inverse_indices": {
          "dtype": "uint32",
          "shape": [1],
          "data": { "kind": "values", "values": [0] },
          "tolerance": 0
        },
        "counts": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [1] }, "tolerance": 0 }
      },
      "provenance": {
        "notes": "The required one-class output extent proves every full axis slice belongs to its first representative; nonuniform coordinates check outer/inner copy indexing."
      }
    },
    {
      "name": "scalar_f32_metadata_mask7_sorted0_n16385_u13",
      "attrs": { "axis": 1, "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 16385, 1],
          "data": { "kind": "cycle", "values": [5.0, 2.0, 7.0, 1.0, 3.0, 11.0, 0.0, 4.0, 6.0, 8.0, 9.0, 10.0, 12.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 13, 1] },
        "indices": { "dtype": "uint32", "shape": [13] },
        "inverse_indices": { "dtype": "uint32", "shape": [16385] },
        "counts": { "dtype": "uint32", "shape": [13] }
      },
      "provenance": {
        "notes": "A [1, 16385, 1] float32 tensor's axis=1 holds 16,385 scalar slices cycling the 13 integers 0 through 12 in shuffled order; the indices, inverse_indices and counts outputs are checked for the resulting 13-slice first-occurrence output."
      }
    },
    {
      "name": "scalar_f32_metadata_mask7_sorted1_n16385_u13",
      "attrs": { "axis": 1, "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 16385, 1],
          "data": { "kind": "cycle", "values": [5.0, 2.0, 7.0, 1.0, 3.0, 11.0, 0.0, 4.0, 6.0, 8.0, 9.0, 10.0, 12.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1, 13, 1] },
        "indices": { "dtype": "uint32", "shape": [13] },
        "inverse_indices": { "dtype": "uint32", "shape": [16385] },
        "counts": { "dtype": "uint32", "shape": [13] }
      },
      "provenance": {
        "notes": "A [1, 16385, 1] float32 tensor's axis=1 holds 16,385 scalar slices cycling the 13 integers 0 through 12 in shuffled order; the indices, inverse_indices and counts outputs are checked for the resulting 13-slice ascending output."
      }
    },
    {
      "name": "single_class_f32_n65537_mask7",
      "inputs": { "x": { "dtype": "float32", "shape": [65537], "data": { "kind": "constant", "value": 3.0 } } },
      "outputs": {
        "y": { "dtype": "float32", "shape": [1] },
        "indices": { "dtype": "uint32", "shape": [1] },
        "inverse_indices": { "dtype": "uint32", "shape": [65537] },
        "counts": { "dtype": "uint32", "shape": [1] }
      },
      "provenance": {
        "notes": "A 65,537-element float32 input is entirely the constant 3.0, collapsing to a single unique value; indices, inverse_indices, and counts outputs all reflect that one class of 65,537 occurrences."
      }
    },
    {
      "name": "flat_global_crossover_i32_n2049_u2049_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [2049],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/flat_global_crossover_int32_n4097_u2049_sorted0_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2049], "tolerance": 0 } },
      "provenance": {
        "notes": "A 2,049-element int32 input is a descending permutation of integers 0 through 2,048 with no duplicates; the first-occurrence output reproduces that same descending order across all 2,049 values."
      }
    },
    {
      "name": "flat_global_crossover_i32_n2049_u2049_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [2049],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/flat_global_crossover_int32_n4097_u2049_sorted0_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2049], "tolerance": 0 } },
      "provenance": {
        "notes": "A 2,049-element int32 input is a descending permutation of integers 0 through 2,048 with no duplicates; the ascending output reorders the same 2,049 distinct values from 0 to 2,048."
      }
    },
    {
      "name": "flat_global_crossover_int32_n4097_u2049_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [4097],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/flat_global_crossover_int32_n4097_u2049_sorted0_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2049], "tolerance": 0 } },
      "provenance": {
        "notes": "A 4,097-element int32 input repeats a descending 0-to-2,048 permutation, then repeats its first 2,048 values again; value 0 appears once and the other 2,048 values appear twice, giving a 2,049-value first-occurrence output in the original descending order."
      }
    },
    {
      "name": "flat_global_crossover_int32_n4097_u2049_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [4097],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/flat_global_crossover_int32_n4097_u2049_sorted0_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2049], "tolerance": 0 } },
      "provenance": {
        "notes": "A 4,097-element int32 input repeats a descending 0-to-2,048 permutation, then repeats its first 2,048 values again; value 0 appears once and the other 2,048 values appear twice, giving a 2,049-value ascending output from 0 to 2,048."
      }
    },
    {
      "name": "output_span_int32_n257_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [257],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n257_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [257], "tolerance": 0 } },
      "provenance": {
        "notes": "A 257-element int32 input is a descending permutation of 1 through 257 with no duplicates; the first-occurrence output reproduces the same 257 values in that descending order."
      }
    },
    {
      "name": "output_span_int32_n257_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [257],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n257_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [257], "tolerance": 0 } },
      "provenance": {
        "notes": "A 257-element int32 input is a descending permutation of 1 through 257 with no duplicates; the ascending output reorders the same 257 values from 1 to 257."
      }
    },
    {
      "name": "output_span_float32_n257_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [257],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n257_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [257], "tolerance": 0 } },
      "provenance": {
        "notes": "A 257-element float32 input is a descending permutation of 1 through 257 with no duplicates; the first-occurrence output reproduces the same 257 values in that descending order."
      }
    },
    {
      "name": "output_span_float32_n257_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [257],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n257_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [257], "tolerance": 0 } },
      "provenance": {
        "notes": "A 257-element float32 input is a descending permutation of 1 through 257 with no duplicates; the ascending output reorders the same 257 values from 1 to 257."
      }
    },
    {
      "name": "output_span_int32_n1025_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [1025],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n1025_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [1025], "tolerance": 0 } },
      "provenance": {
        "notes": "A 1025-element int32 input is a descending permutation of 1 through 1025 with no duplicates; the first-occurrence output reproduces the same 1025 values in that descending order."
      }
    },
    {
      "name": "output_span_int32_n1025_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [1025],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n1025_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [1025], "tolerance": 0 } },
      "provenance": {
        "notes": "A 1025-element int32 input is a descending permutation of 1 through 1025 with no duplicates; the ascending output reorders the same 1025 values from 1 to 1025."
      }
    },
    {
      "name": "output_span_float32_n1025_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1025],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n1025_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1025], "tolerance": 0 } },
      "provenance": {
        "notes": "A 1025-element float32 input is a descending permutation of 1 through 1025 with no duplicates; the first-occurrence output reproduces the same 1025 values in that descending order."
      }
    },
    {
      "name": "output_span_float32_n1025_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1025],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n1025_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [1025], "tolerance": 0 } },
      "provenance": {
        "notes": "A 1025-element float32 input is a descending permutation of 1 through 1025 with no duplicates; the ascending output reorders the same 1025 values from 1 to 1025."
      }
    },
    {
      "name": "output_span_int32_n2048_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [2048],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n2048_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2048], "tolerance": 0 } },
      "provenance": {
        "notes": "A 2048-element int32 input is a descending permutation of 1 through 2048 with no duplicates; the first-occurrence output reproduces the same 2048 values in that descending order."
      }
    },
    {
      "name": "output_span_int32_n2048_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [2048],
          "data": { "kind": "cycle", "values": { "$ref": "#/fixtureArrays/output_span_int32_n2048_sorted0_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [2048], "tolerance": 0 } },
      "provenance": {
        "notes": "A 2048-element int32 input is a descending permutation of 1 through 2048 with no duplicates; the ascending output reorders the same 2048 values from 1 to 2048."
      }
    },
    {
      "name": "float_hash_work_boundary_float32_n15_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [15], "data": { "kind": "linspace", "start": 14.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [15], "tolerance": 0 } },
      "provenance": {
        "notes": "15 distinct float32 values descending from 14 to 0; sorted=0 must keep their descending first-occurrence order."
      }
    },
    {
      "name": "float_hash_work_boundary_float32_n15_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [15], "data": { "kind": "linspace", "start": 14.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [15], "tolerance": 0 } },
      "provenance": {
        "notes": "15 distinct float32 values descending from 14 to 0; sorted=1 must return them in ascending order."
      }
    },
    {
      "name": "float_hash_work_boundary_float32_n16_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [16], "data": { "kind": "linspace", "start": 15.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [16], "tolerance": 0 } },
      "provenance": {
        "notes": "16 distinct float32 values descending from 15 to 0; sorted=0 must keep their descending first-occurrence order."
      }
    },
    {
      "name": "float_hash_work_boundary_float32_n16_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [16], "data": { "kind": "linspace", "start": 15.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [16], "tolerance": 0 } },
      "provenance": {
        "notes": "16 distinct float32 values descending from 15 to 0; sorted=1 must return them in ascending order."
      }
    },
    {
      "name": "float_hash_work_boundary_float16_n15_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float16", "shape": [15], "data": { "kind": "linspace", "start": 14.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [15], "tolerance": 0 } },
      "provenance": {
        "notes": "15 distinct float16 values descending from 14 to 0; sorted=0 must keep their descending first-occurrence order."
      }
    },
    {
      "name": "float_hash_work_boundary_float16_n15_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float16", "shape": [15], "data": { "kind": "linspace", "start": 14.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [15], "tolerance": 0 } },
      "provenance": {
        "notes": "15 distinct float16 values descending from 14 to 0; sorted=1 must return them in ascending order."
      }
    },
    {
      "name": "float_hash_work_boundary_float16_n16_sorted0",
      "attrs": { "sorted": 0 },
      "inputs": {
        "x": { "dtype": "float16", "shape": [16], "data": { "kind": "linspace", "start": 15.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [16], "tolerance": 0 } },
      "provenance": {
        "notes": "16 distinct float16 values descending from 15 to 0; sorted=0 must keep their descending first-occurrence order."
      }
    },
    {
      "name": "float_hash_work_boundary_float16_n16_sorted1",
      "attrs": { "sorted": 1 },
      "inputs": {
        "x": { "dtype": "float16", "shape": [16], "data": { "kind": "linspace", "start": 15.0, "end": 0.0 } }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [16], "tolerance": 0 } },
      "provenance": {
        "notes": "16 distinct float16 values descending from 15 to 0; sorted=1 must return them in ascending order."
      }
    },
    {
      "name": "axis_merge_float32_outer1_u15_tile16_tied_prefix",
      "provenance": {
        "notes": "Exact tied-prefix ordering with duplicate rows, padding and non-power-of-two dimensions. Odd and even merge counts and the single-tile case are covered. Floating rows include signed zero."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "GLOBAL_SORT_TILE": 16, "LOCAL_SORT_CROSSOVER": 64, "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [67, 3],
          "data": {
            "kind": "values",
            "values": [0.0, 0.0, 15.0, -0.0, -0.0, 14.0, 0.0, 0.0, 13.0, -0.0, -0.0, 12.0, 0.0, 0.0, 11.0, -0.0, -0.0, 10.0, 0.0, 0.0, 9.0, -0.0, -0.0, 8.0, 0.0, 0.0, 7.0, -0.0, -0.0, 6.0, 0.0, 0.0, 5.0, -0.0, -0.0, 4.0, 0.0, 0.0, 3.0, -0.0, -0.0, 2.0, 0.0, 0.0, 1.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 15.0, -0.0, -0.0, 14.0, 0.0, 0.0, 13.0, -0.0, -0.0, 12.0, 0.0, 0.0, 11.0, -0.0, -0.0, 10.0, 0.0, 0.0, 9.0, -0.0, -0.0, 8.0, 0.0, 0.0, 7.0, -0.0, -0.0, 6.0, 0.0, 0.0, 5.0, -0.0, -0.0, 4.0, 0.0, 0.0, 3.0, -0.0, -0.0, 2.0, 0.0, 0.0, 1.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 15.0, -0.0, -0.0, 14.0, 0.0, 0.0, 13.0, -0.0, -0.0, 12.0, 0.0, 0.0, 11.0, -0.0, -0.0, 10.0, 0.0, 0.0, 9.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [15, 3], "tolerance": 0, "relTolerance": 0 } }
    },
    {
      "name": "axis_merge_float32_outer1_u16_tile16_tied_prefix",
      "provenance": {
        "notes": "Exact tied-prefix ordering with duplicate rows, padding and non-power-of-two dimensions. Odd and even merge counts and the single-tile case are covered. Floating rows include signed zero."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "GLOBAL_SORT_TILE": 16, "LOCAL_SORT_CROSSOVER": 64, "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [67, 3],
          "data": {
            "kind": "values",
            "values": [0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [16, 3], "tolerance": 0, "relTolerance": 0 } }
    },
    {
      "name": "axis_merge_float32_outer1_u17_tile16_tied_prefix",
      "provenance": {
        "notes": "Exact tied-prefix ordering with duplicate rows, padding and non-power-of-two dimensions. Odd and even merge counts and the single-tile case are covered. Floating rows include signed zero."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "GLOBAL_SORT_TILE": 16, "LOCAL_SORT_CROSSOVER": 64, "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [67, 3],
          "data": {
            "kind": "values",
            "values": [0.0, 0.0, 17.0, -0.0, -0.0, 16.0, 0.0, 0.0, 15.0, -0.0, -0.0, 14.0, 0.0, 0.0, 13.0, -0.0, -0.0, 12.0, 0.0, 0.0, 11.0, -0.0, -0.0, 10.0, 0.0, 0.0, 9.0, -0.0, -0.0, 8.0, 0.0, 0.0, 7.0, -0.0, -0.0, 6.0, 0.0, 0.0, 5.0, -0.0, -0.0, 4.0, 0.0, 0.0, 3.0, -0.0, -0.0, 2.0, 0.0, 0.0, 1.0, -0.0, -0.0, 17.0, 0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 17.0, -0.0, -0.0, 16.0, 0.0, 0.0, 15.0, -0.0, -0.0, 14.0, 0.0, 0.0, 13.0, -0.0, -0.0, 12.0, 0.0, 0.0, 11.0, -0.0, -0.0, 10.0, 0.0, 0.0, 9.0, -0.0, -0.0, 8.0, 0.0, 0.0, 7.0, -0.0, -0.0, 6.0, 0.0, 0.0, 5.0, -0.0, -0.0, 4.0, 0.0, 0.0, 3.0, -0.0, -0.0, 2.0, 0.0, 0.0, 1.0, -0.0, -0.0, 17.0, 0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [17, 3], "tolerance": 0, "relTolerance": 0 } }
    },
    {
      "name": "axis_merge_float16_outer1_u33_tile16_tied_prefix",
      "provenance": {
        "notes": "Exact tied-prefix ordering with duplicate rows, padding and non-power-of-two dimensions. Odd and even merge counts and the single-tile case are covered. Floating rows include signed zero."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "GLOBAL_SORT_TILE": 16, "LOCAL_SORT_CROSSOVER": 64, "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [67, 3],
          "data": {
            "kind": "values",
            "values": [0.0, 0.0, 33.0, -0.0, -0.0, 32.0, 0.0, 0.0, 31.0, -0.0, -0.0, 30.0, 0.0, 0.0, 29.0, -0.0, -0.0, 28.0, 0.0, 0.0, 27.0, -0.0, -0.0, 26.0, 0.0, 0.0, 25.0, -0.0, -0.0, 24.0, 0.0, 0.0, 23.0, -0.0, -0.0, 22.0, 0.0, 0.0, 21.0, -0.0, -0.0, 20.0, 0.0, 0.0, 19.0, -0.0, -0.0, 18.0, 0.0, 0.0, 17.0, -0.0, -0.0, 16.0, 0.0, 0.0, 15.0, -0.0, -0.0, 14.0, 0.0, 0.0, 13.0, -0.0, -0.0, 12.0, 0.0, 0.0, 11.0, -0.0, -0.0, 10.0, 0.0, 0.0, 9.0, -0.0, -0.0, 8.0, 0.0, 0.0, 7.0, -0.0, -0.0, 6.0, 0.0, 0.0, 5.0, -0.0, -0.0, 4.0, 0.0, 0.0, 3.0, -0.0, -0.0, 2.0, 0.0, 0.0, 1.0, -0.0, -0.0, 33.0, 0.0, 0.0, 32.0, -0.0, -0.0, 31.0, 0.0, 0.0, 30.0, -0.0, -0.0, 29.0, 0.0, 0.0, 28.0, -0.0, -0.0, 27.0, 0.0, 0.0, 26.0, -0.0, -0.0, 25.0, 0.0, 0.0, 24.0, -0.0, -0.0, 23.0, 0.0, 0.0, 22.0, -0.0, -0.0, 21.0, 0.0, 0.0, 20.0, -0.0, -0.0, 19.0, 0.0, 0.0, 18.0, -0.0, -0.0, 17.0, 0.0, 0.0, 16.0, -0.0, -0.0, 15.0, 0.0, 0.0, 14.0, -0.0, -0.0, 13.0, 0.0, 0.0, 12.0, -0.0, -0.0, 11.0, 0.0, 0.0, 10.0, -0.0, -0.0, 9.0, 0.0, 0.0, 8.0, -0.0, -0.0, 7.0, 0.0, 0.0, 6.0, -0.0, -0.0, 5.0, 0.0, 0.0, 4.0, -0.0, -0.0, 3.0, 0.0, 0.0, 2.0, -0.0, -0.0, 1.0, 0.0, 0.0, 33.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [33, 3], "tolerance": 0, "relTolerance": 0 } }
    },
    {
      "name": "axis_merge_int32_outer1_u33_tile16_tied_prefix",
      "provenance": {
        "notes": "Exact tied-prefix ordering with duplicate rows, padding and non-power-of-two dimensions. Odd and even merge counts and the single-tile case are covered. Floating rows include signed zero."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "GLOBAL_SORT_TILE": 16, "LOCAL_SORT_CROSSOVER": 64, "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [67, 3],
          "data": {
            "kind": "values",
            "values": [0, 0, 33, 0, 0, 32, 0, 0, 31, 0, 0, 30, 0, 0, 29, 0, 0, 28, 0, 0, 27, 0, 0, 26, 0, 0, 25, 0, 0, 24, 0, 0, 23, 0, 0, 22, 0, 0, 21, 0, 0, 20, 0, 0, 19, 0, 0, 18, 0, 0, 17, 0, 0, 16, 0, 0, 15, 0, 0, 14, 0, 0, 13, 0, 0, 12, 0, 0, 11, 0, 0, 10, 0, 0, 9, 0, 0, 8, 0, 0, 7, 0, 0, 6, 0, 0, 5, 0, 0, 4, 0, 0, 3, 0, 0, 2, 0, 0, 1, 0, 0, 33, 0, 0, 32, 0, 0, 31, 0, 0, 30, 0, 0, 29, 0, 0, 28, 0, 0, 27, 0, 0, 26, 0, 0, 25, 0, 0, 24, 0, 0, 23, 0, 0, 22, 0, 0, 21, 0, 0, 20, 0, 0, 19, 0, 0, 18, 0, 0, 17, 0, 0, 16, 0, 0, 15, 0, 0, 14, 0, 0, 13, 0, 0, 12, 0, 0, 11, 0, 0, 10, 0, 0, 9, 0, 0, 8, 0, 0, 7, 0, 0, 6, 0, 0, 5, 0, 0, 4, 0, 0, 3, 0, 0, 2, 0, 0, 1, 0, 0, 33]
          }
        }
      },
      "outputs": { "y": { "dtype": "int32", "shape": [33, 3], "tolerance": 0, "relTolerance": 0 } }
    },
    {
      "name": "axis_merge_uint32_outer1_u65_tile16_tied_prefix",
      "provenance": {
        "notes": "Exact tied-prefix ordering with duplicate rows, padding and non-power-of-two dimensions. Odd and even merge counts and the single-tile case are covered. Floating rows include signed zero."
      },
      "attrs": { "axis": 0, "sorted": 1 },
      "tunables": { "GLOBAL_SORT_TILE": 16, "LOCAL_SORT_CROSSOVER": 64, "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [67, 3],
          "data": {
            "kind": "values",
            "values": [0, 0, 65, 0, 0, 64, 0, 0, 63, 0, 0, 62, 0, 0, 61, 0, 0, 60, 0, 0, 59, 0, 0, 58, 0, 0, 57, 0, 0, 56, 0, 0, 55, 0, 0, 54, 0, 0, 53, 0, 0, 52, 0, 0, 51, 0, 0, 50, 0, 0, 49, 0, 0, 48, 0, 0, 47, 0, 0, 46, 0, 0, 45, 0, 0, 44, 0, 0, 43, 0, 0, 42, 0, 0, 41, 0, 0, 40, 0, 0, 39, 0, 0, 38, 0, 0, 37, 0, 0, 36, 0, 0, 35, 0, 0, 34, 0, 0, 33, 0, 0, 32, 0, 0, 31, 0, 0, 30, 0, 0, 29, 0, 0, 28, 0, 0, 27, 0, 0, 26, 0, 0, 25, 0, 0, 24, 0, 0, 23, 0, 0, 22, 0, 0, 21, 0, 0, 20, 0, 0, 19, 0, 0, 18, 0, 0, 17, 0, 0, 16, 0, 0, 15, 0, 0, 14, 0, 0, 13, 0, 0, 12, 0, 0, 11, 0, 0, 10, 0, 0, 9, 0, 0, 8, 0, 0, 7, 0, 0, 6, 0, 0, 5, 0, 0, 4, 0, 0, 3, 0, 0, 2, 0, 0, 1, 0, 0, 65, 0, 0, 64]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [65, 3], "tolerance": 0, "relTolerance": 0 } }
    },
    {
      "name": "axis_merge_float32_outer3_u33_tile16_tied_prefix",
      "provenance": {
        "notes": "Exact tied-prefix ordering with duplicate rows, padding and non-power-of-two dimensions. Odd and even merge counts and the single-tile case are covered. Floating rows include signed zero."
      },
      "attrs": { "axis": 1, "sorted": 1 },
      "tunables": { "GLOBAL_SORT_TILE": 16, "LOCAL_SORT_CROSSOVER": 64, "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 67, 5],
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