{
  "fixtureArrays": {
    "onnx_backend_argmin_input_x": [0.9762700796127319, 4.3037872314453125, 2.055267572402954, 0.8976636528968811, -1.5269039869308472, 2.917882204055786, -1.248255729675293, 7.835460186004639, 9.273255348205566, -2.331169605255127, 5.834500789642334, 0.577898383140564, 1.3608912229537964, 8.511932373046875, -8.579278945922852, -8.257413864135742, -9.59563159942627, 6.6523966789245605, 5.563135147094727, 7.400242805480957, 9.572366714477539, 5.983171463012695, -0.7704127430915833, 5.610583305358887],
    "axis0_splitk_8192x32_ties_first_index_input_x": [2, -3, -3, 1, 2, -3, -3, 1, 2, -3, -3, 1, 2, -3, -3, 1, 2, -3, -3, 1, 2, -3, -3, 1, 2, -3, -3, 1, 2, -3, -3, 1, 2],
    "subgroup_vec4_ties_first_index_input_x": [1, 5, 0, 2, 5, 0, 1, 4, 7, 7, 7, 7, 7, 7, 7, 7],
    "axis0_splitk_i32_8192x16_precision_min_input_x": [16777217, 16777217, 16777217, 16777217, 16777217, 16777217, 16777217, 16777217, 16777216, 16777216, 16777216, 16777216, 16777216, 16777216, 16777216, 16777216, 16777216],
    "adjacent_scalar_f32_special_first_input_x": ["Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", "Infinity", 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", -2, "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", "NaN", -2, 0, "-Infinity", 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, "-Infinity", "NaN"]
  },
  "cases": [
    {
      "name": "int16_last_axis_vec4_boundaries",
      "attrs": { "axis": -1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int16",
          "shape": [2, 4],
          "data": { "kind": "values", "values": [-32768, -1, 32767, 0, 32767, -32768, 32767, 1] }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [2], "tolerance": 0, "data": { "kind": "values", "values": [0, 1] } }
      }
    },
    {
      "name": "onnx_default_axis0_omitted",
      "provenance": {
        "source": "https://onnx.ai/onnx/operators/onnx__ArgMin.html",
        "test": "ArgMin axis default",
        "notes": "Omitting axis must reduce the leading dimension (ONNX default 0), not axis 1. The rank-2 output shape and per-column indices distinguish the two semantics. Representable ONNX int64 indices are stored in uint32 slots."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3],
          "data": { "kind": "values", "values": [1.0, 9.0, 3.0, 4.0, 2.0, 8.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [1, 3], "tolerance": 0, "data": { "kind": "values", "values": [0, 1, 0] } }
      }
    },
    {
      "name": "f32_negative_subnormal_beats_zero_gpu_gap",
      "skipGpu": {
        "category": "permanent",
        "reason": "Portable WGSL floating-point semantics do not guarantee preservation of the subnormal values required by this fixture. Backend evidence: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU."
      },
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ArgMin",
        "notes": "A negative subnormal is strictly less than zero; index selection must not treat it as a tie with zero."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [1, 3], "data": { "kind": "values", "values": [1e-40, 0.0, -1e-40] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1], "tolerance": 0 } }
    },
    {
      "name": "f32_negative_subnormal_beats_zero_select_last_gpu_gap",
      "skipGpu": {
        "category": "permanent",
        "reason": "Portable WGSL floating-point semantics do not guarantee preservation of the subnormal values required by this fixture. Backend evidence: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU."
      },
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ArgMin_do_not_keepdims_2_select_last",
        "notes": "select_last_index must only apply to true ties; a negative subnormal at index 0 is less than following zeros."
      },
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [1, 3], "data": { "kind": "values", "values": [-1e-40, 0.0, 0.0] } }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [1], "tolerance": 0, "data": { "kind": "values", "values": [0] } }
      }
    },
    {
      "name": "f32_negative_subnormal_beats_zero_axis0_gpu_gap",
      "skipGpu": {
        "category": "permanent",
        "reason": "Portable WGSL floating-point semantics do not guarantee preservation of the subnormal values required by this fixture. Backend evidence: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU."
      },
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ArgMin",
        "notes": "Along axis 0, a negative subnormal is strictly less than zero and must not be tie-broken as though it were flushed to zero."
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [3, 1], "data": { "kind": "values", "values": [1e-40, 0.0, -1e-40] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1], "tolerance": 0 } }
    },
    {
      "name": "dispatch_cliff_axis1_16777216x1",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": { "x": { "dtype": "float32", "shape": [16777216, 1], "data": { "kind": "constant", "value": 1.0 } } },
      "outputs": { "y": { "dtype": "uint32", "shape": [16777216], "tolerance": 0 } }
    },
    {
      "name": "axis0",
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 4],
          "data": { "kind": "values", "values": [1.0, 9.0, 3.0, 4.0, -1.0, 2.0, 7.0, 8.0, 0.0, 5.0, -3.0, 6.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [4] } }
    },
    {
      "name": "axis0_splitk_8192x32_ties_first_index",
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8192, 32],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_8192x32_ties_first_index_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32], "tolerance": 0 } }
    },
    {
      "name": "axis0_splitk_8192x32_ties_select_last_index",
      "attrs": { "axis": 0, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8192, 32],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_8192x32_ties_first_index_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32], "tolerance": 0 } }
    },
    {
      "name": "axis0_splitk_8192x48_keepdims",
      "attrs": { "axis": 0, "keepdims": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8192, 48],
          "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29, "scale": 0.2 }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 48], "tolerance": 0 } }
    },
    {
      "name": "axis0_tiled_64x32_ties_first_index",
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [64, 32],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_8192x32_ties_first_index_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32], "tolerance": 0 } }
    },
    {
      "name": "axis0_tiled_64x32_ties_select_last_index",
      "attrs": { "axis": 0, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [64, 32],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_8192x32_ties_first_index_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32], "tolerance": 0 } }
    },
    {
      "name": "axis1_tie_first_index",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 5],
          "data": { "kind": "values", "values": [1.0, -3.0, -3.0, 2.0, -3.0, 1.0, 1.0, 2.0, 1.0, 3.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2] } }
    },
    {
      "name": "ort_axis1_nan_first_incumbent_gpu_gap",
      "skipGpu": {
        "category": "todo",
        "reason": "The parallel reduction routes do not preserve first-element NaN incumbent semantics. Explicit NaN and index tracking is implementable in WGSL."
      },
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin",
        "notes": "NaN extension: ArgMin seeds the reduction from the first reduced element, so a leading NaN remains the selected incumbent while later NaNs are ignored after a finite incumbent."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 4],
          "data": {
            "kind": "values",
            "values": ["NaN", 1.0, -2.0, 0.0, 1.0, "NaN", -2.0, 0.0, 1.0, -2.0, "NaN", 0.0, "NaN", "NaN", "NaN", "NaN"]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [4], "tolerance": 0 } }
    },
    {
      "name": "ort_axis1_nan_select_last_index_gpu_gap",
      "skipGpu": {
        "category": "todo",
        "reason": "The parallel reduction routes do not preserve first-element NaN incumbent semantics. Explicit NaN and index tracking is implementable in WGSL."
      },
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_int32_last_index_dups",
        "notes": "NaN extension: select_last_index only changes equal finite ties. A leading NaN remains the incumbent because finite values are not less than NaN."
      },
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 4],
          "data": {
            "kind": "values",
            "values": ["NaN", 1.0, -2.0, 0.0, 1.0, "NaN", -3.0, -3.0, 1.0, 2.0, "NaN", 3.0, "NaN", "NaN", "NaN", "NaN"]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [4], "data": { "kind": "values", "values": [0, 3, 0, 0] }, "tolerance": 0 }
      }
    },
    {
      "name": "axis1_f16",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [3, 4],
          "data": { "kind": "values", "values": [1.0, 9.0, 3.0, 4.0, -1.0, 2.0, 7.0, 8.0, 0.0, 5.0, -3.0, 6.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [3] } }
    },
    {
      "name": "axis1_select_last_index_ties",
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 5],
          "data": { "kind": "values", "values": [1.0, -3.0, -3.0, 2.0, -3.0, 1.0, 1.0, 2.0, 1.0, 3.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2] } }
    },
    {
      "name": "axis1_select_last_all_positive_infinity",
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 4],
          "data": {
            "kind": "values",
            "values": ["Infinity", "Infinity", "Infinity", "Infinity", 5.0, 5.0, "Infinity", "Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "tolerance": 0 } }
    },
    {
      "name": "axis_minus_one",
      "attrs": { "axis": -1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 4],
          "data": { "kind": "values", "values": [1.0, -2.0, 9.0, 4.0, 5.0, 8.0, -7.0, 6.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2] } }
    },
    {
      "name": "axis1_keepdims",
      "attrs": { "axis": 1, "keepdims": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 4],
          "data": { "kind": "values", "values": [4.0, -3.0, -3.0, 1.0, 2.0, 2.0, -5.0, -5.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1] } }
    },
    {
      "name": "rank3_axis0",
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 2, 3],
          "data": { "kind": "values", "values": [4.0, -3.0, 5.0, 1.0, 2.0, -5.0, 3.0, -4.0, 6.0, 0.0, 3.0, -6.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 3], "tolerance": 0 } }
    },
    {
      "name": "rank4_axis1_channel_select_last_ties",
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 3, 2, 2],
          "data": { "kind": "values", "values": [1.0, -5.0, 3.0, -5.0, -2.0, -5.0, 3.0, -7.0, -2.0, -4.0, 0.0, -7.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 2, 2], "tolerance": 0 } }
    },
    {
      "name": "rank4_axis2_spatial_keepdims_select_last_ties",
      "attrs": { "axis": 2, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 2, 3, 2],
          "data": { "kind": "values", "values": [1.0, -4.0, -3.0, -4.0, -3.0, -2.0, 1.0, -5.0, 0.0, -5.0, 0.0, -3.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 2, 1, 2], "tolerance": 0 } }
    },
    {
      "name": "rank4_last_axis_nhwc_keepdims_select_last",
      "attrs": { "axis": -1, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [1, 2, 2, 3],
          "data": { "kind": "values", "values": [1.0, -3.0, -3.0, 5.0, 4.0, -7.0, -3.0, -3.0, 0.0, 5.0, -7.0, -7.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 2, 2, 1], "tolerance": 0 } }
    },
    {
      "name": "rank1_axis0_keepdims_select_last",
      "attrs": { "axis": 0, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [4.0, -8.0, 2.0, -8.0, 0.0, -1.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1], "tolerance": 0 } }
    },
    {
      "name": "ort_uint8_axis0_no_keepdims",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_uint8"
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "uint8",
          "shape": [3, 2, 2],
          "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2], "tolerance": 0 } }
    },
    {
      "name": "ort_int8_axis0_no_keepdims",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_int8"
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int8",
          "shape": [3, 2, 2],
          "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2], "tolerance": 0 } }
    },
    {
      "name": "ort_int32_axis0_select_last_dups",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_int32_select_last"
      },
      "attrs": { "axis": 0, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [3, 2, 2],
          "data": { "kind": "values", "values": [1, 2, 3, 4, 1, 6, 7, 8, 9, 10, 11, 12] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2], "tolerance": 0 } }
    },
    {
      "name": "ort_int32_axis0_no_keepdims",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_int32"
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [3, 2, 2],
          "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2], "tolerance": 0 } }
    },
    {
      "name": "ort_axis0_keepdims_rank3_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin"
      },
      "attrs": { "axis": 0, "keepdims": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 2, 2],
          "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 2, 2], "tolerance": 0 } }
    },
    {
      "name": "ort_axis0_no_keepdims_rank3_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_do_not_keepdims"
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 2, 2],
          "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2], "tolerance": 0 } }
    },
    {
      "name": "ort_axis0_no_keepdims_rank1_scalar_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_do_not_keepdims_2"
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1.0, 2.0, 3.0] } } },
      "outputs": { "y": { "dtype": "uint32", "shape": [], "tolerance": 0 } }
    },
    {
      "name": "ort_axis0_no_keepdims_rank1_scalar_select_last_f32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_do_not_keepdims_2_select_last"
      },
      "attrs": { "axis": 0, "keepdims": 0, "select_last_index": 1 },
      "inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1.0, 2.0, 3.0] } } },
      "outputs": { "y": { "dtype": "uint32", "shape": [], "tolerance": 0 } }
    },
    {
      "name": "ort_float_first_index_negative_infinity_deterministic",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_float_first_index_random",
        "notes": "Deterministic compact projection of ORT's random negative-infinity first-index test."
      },
      "attrs": { "axis": 0, "keepdims": 1, "select_last_index": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [16],
          "data": {
            "kind": "values",
            "values": [0.0, 1.0, "-Infinity", -5.0, "-Infinity", 3.0, -2.0, "-Infinity", -4.0, 1.0, -3.0, "-Infinity", 0.0, -2.0, -1.0, 0.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1], "tolerance": 0 } }
    },
    {
      "name": "ort_negative_axis_int32_no_keepdims",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_int32_neg_axis"
      },
      "attrs": { "axis": -3, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [3, 2, 2],
          "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2], "tolerance": 0 } }
    },
    {
      "name": "int32_axis1_exact_above_float24",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [2, 4],
          "data": { "kind": "values", "values": [16777217, 16777216, 5, 9, -16777216, -16777217, 0, 3] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_default_axis_example",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_default_axis_example",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "keepdims": 1, "axis": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 1.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 2], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_default_axis_example_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_default_axis_example_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "keepdims": 1, "select_last_index": 1, "axis": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 2.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 2], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_default_axis_random",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_default_axis_random",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "keepdims": 1, "axis": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 3, 4], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_default_axis_random_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_default_axis_random_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "keepdims": 1, "select_last_index": 1, "axis": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 3, 4], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_keepdims_example",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_keepdims_example",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 1.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_keepdims_example_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_keepdims_example_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 2.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_keepdims_random",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_keepdims_random",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1, 4], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_keepdims_random_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_keepdims_random_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1, 4], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_negative_axis_keepdims_example",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_negative_axis_keepdims_example",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": -1, "keepdims": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 1.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_negative_axis_keepdims_example_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_negative_axis_keepdims_example_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": -1, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 2.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_negative_axis_keepdims_random",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_negative_axis_keepdims_random",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": -1, "keepdims": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 3, 1], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_negative_axis_keepdims_random_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_negative_axis_keepdims_random_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": -1, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 3, 1], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_no_keepdims_example",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_no_keepdims_example",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 1.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_no_keepdims_example_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_no_keepdims_example_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [2.0, 2.0, 3.0, 10.0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_no_keepdims_random",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_no_keepdims_random",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 4], "tolerance": 0 } }
    },
    {
      "name": "onnx_backend_argmin_no_keepdims_random_select_last_index",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_no_keepdims_random_select_last_index",
        "notes": "ONNX arg-reduction outputs use int64 indices; this WebGPU package stores representable indices in uint32 slots."
      },
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 3, 4],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_argmin_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 4], "tolerance": 0 } }
    },
    {
      "name": "subgroup_vec4_ties_first_index",
      "attrs": { "axis": -1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 8],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/subgroup_vec4_ties_first_index_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [2, 0] } } }
    },
    {
      "name": "subgroup_vec4_ties_select_last_index",
      "attrs": { "axis": -1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 8],
          "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/subgroup_vec4_ties_first_index_input_x" } }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [5, 7] } } }
    },
    {
      "name": "subgroup_scalar_f16_2x5",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [2, 5],
          "data": { "kind": "values", "values": [1.5, 2.5, 2.5, 0.5, 1.0, -1.0, -2.0, -0.5, -0.5, -3.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [3, 4] } } }
    },
    {
      "name": "subgroup_vec4_uint8_full_range",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": { "dtype": "uint8", "shape": [2, 4], "data": { "kind": "values", "values": [255, 0, 254, 1, 2, 2, 1, 0] } }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [1, 3] } } }
    },
    {
      "name": "subgroup_vec4_long_row_2x256",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 256],
          "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29 }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2] } }
    },
    {
      "name": "subgroup_min_vec4_rows128x256_ties_last",
      "provenance": { "notes": "Aligned 256-element rows with equal minima verify last-index tie ordering." },
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": { "x": { "dtype": "float32", "shape": [128, 256], "data": { "kind": "constant", "value": -7.0 } } },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [128], "data": { "kind": "constant", "value": 255 }, "tolerance": 0 }
      }
    },
    {
      "name": "subgroup_min_scalar_rows128x257_ties_first",
      "provenance": { "notes": "Unaligned 257-element rows with equal minima verify first-index tie ordering." },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": { "x": { "dtype": "float32", "shape": [128, 257], "data": { "kind": "constant", "value": -7.0 } } },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [128], "data": { "kind": "constant", "value": 0 }, "tolerance": 0 }
      }
    },
    {
      "name": "subgroup_scalar_long_row_2x65",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 65],
          "data": { "kind": "fillFloat32", "sinStep": 0.23, "cosStep": 0.11 }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2] } }
    },
    {
      "name": "empty_zero_dim",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": { "x": { "dtype": "float32", "shape": [0, 4], "data": { "kind": "values", "values": [] } } },
      "outputs": { "y": { "dtype": "uint32", "shape": [0], "tolerance": 0 } }
    },
    {
      "name": "empty_zero_dim_f16",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": { "x": { "dtype": "float16", "shape": [0, 4], "data": { "kind": "values", "values": [] } } },
      "outputs": { "y": { "dtype": "uint32", "shape": [0], "tolerance": 0 } }
    },
    {
      "name": "empty_zero_dim_int32",
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": { "x": { "dtype": "int32", "shape": [0, 4], "data": { "kind": "values", "values": [] } } },
      "outputs": { "y": { "dtype": "uint32", "shape": [0], "tolerance": 0 } }
    },
    {
      "name": "rank4_axis0_batch_argmin_int32",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_int32 (extended to rank4 batch axis)",
        "notes": "Reduces the leading batch axis of a rank-4 NCHW int32 tensor."
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [3, 2, 2, 2],
          "data": {
            "kind": "values",
            "values": [5, 9, 4, 8, 7, 2, 6, 3, 3, 1, 9, 2, 0, 8, 5, 7, 8, 4, 1, 6, 9, 3, 2, 1]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2, 2], "tolerance": 0 } }
    },
    {
      "name": "rank4_axis0_batch_argmin_f32_keepdims",
      "provenance": {
        "source": "cmake/external/onnx/onnx/backend/test/data/node/test_argmin_keepdims_random (extended to rank4 batch axis)",
        "notes": "A rank-four float32 reduction over batch axis zero with keepdims=1 checks the output rank and minimum indices."
      },
      "attrs": { "axis": 0, "keepdims": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 2, 2, 2],
          "data": {
            "kind": "values",
            "values": [4.0, -3.0, 5.0, 1.0, 2.0, -5.0, 3.0, -4.0, 6.0, 0.0, 3.0, -6.0, -1.0, 7.0, 2.0, 8.0, -9.0, 4.0, 5.0, 1.0, -2.0, 3.0, 0.0, 6.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 2, 2, 2], "tolerance": 0 } }
    },
    {
      "name": "rank4_axis1_channel_int8_nchw",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_int8 (rank4 NCHW channel argmin)",
        "notes": "An int8 channel-axis ArgMin over a rank-4 NCHW tensor exercises integer comparison on the rank-4 axis-1 path."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int8",
          "shape": [2, 4, 3, 3],
          "data": {
            "kind": "values",
            "values": [3, 10, 17, 24, 31, 38, 45, 52, 59, 66, 73, 80, 87, 94, 101, 108, 115, 122, 127, -120, -113, -106, -99, -92, -85, -78, -71, -64, -57, -50, -43, -36, -29, -22, -15, -8, -1, 6, 13, 20, 27, 34, 41, 48, 55, 62, 69, 76, 83, 90, 97, 104, 111, 118, 125, -124, -117, -110, -103, -96, -89, -82, -75, -68, -61, -54, -47, -40, -33, -26, -19, -12]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 3, 3], "tolerance": 0 } }
    },
    {
      "name": "rank3_axis1_f16_keepdims_select_last",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin (rank3 middle-axis f16 select_last)",
        "notes": "A float16 rank-3 middle-axis reduction with keepdims=1 and select_last_index=1 exercises the float16 strided route and last-index tie breaking."
      },
      "attrs": { "axis": 1, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [2, 5, 4],
          "data": {
            "kind": "values",
            "values": [-1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, -1.5, -1.0, -0.5, 0.0, 0.5]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 1, 4], "tolerance": 0 } }
    },
    {
      "name": "axis1_serial_fallback_rows32768_cols5_select_last",
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [32768, 5],
          "data": { "kind": "cycle", "values": [2.0, -3.0, -3.0, 1.0, -3.0, 2.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32768], "tolerance": 0 } }
    },
    {
      "name": "axis1_serial_fallback_rows32768_cols5_first_index",
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [32768, 5],
          "data": { "kind": "cycle", "values": [2.0, -3.0, -3.0, 1.0, -3.0, 2.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32768], "tolerance": 0 } }
    },
    {
      "name": "axis0_fallback_rows4_int32_select_last_ties",
      "attrs": { "axis": 0, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [4, 4],
          "data": { "kind": "values", "values": [5, 1, 3, 2, 5, 7, 3, 2, 4, 7, 9, 2, 4, 1, 9, 8] }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [4], "tolerance": 0, "data": { "kind": "values", "values": [3, 3, 1, 2] } }
      }
    },
    {
      "name": "axis1_int8_serial_fallback_negative_min_select_last",
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "int8",
          "shape": [2, 8],
          "data": {
            "kind": "values",
            "values": [-5, -5, -128, -128, 3, 3, 127, 127, 0, -128, 0, -127, -100, -100, -100, -50]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2], "tolerance": 0 } }
    },
    {
      "name": "axis0_splitk_i32_8192x16_precision_min",
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [8192, 16],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_i32_8192x16_precision_min_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [16], "tolerance": 0 } }
    },
    {
      "name": "axis0_splitk_u32_8192x16_precision_min",
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [8192, 16],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_i32_8192x16_precision_min_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [16], "tolerance": 0 } }
    },
    {
      "name": "axis0_tilecols_i32_64x16_precision_min",
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [64, 16],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_i32_8192x16_precision_min_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [16], "tolerance": 0 } }
    },
    {
      "name": "axis0_tilecols_i32_64x16_precision_select_last_min",
      "attrs": { "axis": 0, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [64, 16],
          "data": {
            "kind": "cycle",
            "values": { "$ref": "#/fixtureArrays/axis0_splitk_i32_8192x16_precision_min_input_x" }
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [16], "tolerance": 0 } }
    },
    {
      "name": "axis0_narrow_splitk_16384x8_f32",
      "provenance": {
        "notes": "A tall, narrow axis-0 reduction with 16,384 rows and eight columns exercises split-and-tiled partial reductions and their combine pass across all columns."
      },
      "attrs": { "axis": 0, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [16384, 8],
          "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29 }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [8], "tolerance": 0 } }
    },
    {
      "name": "last_axis_split_vec4_logits_ties_first",
      "provenance": {
        "notes": "A 32,768-element row has equal minima across distant segments; the result must be the first global index."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": { "dtype": "float32", "shape": [1, 32768], "data": { "kind": "cycle", "values": [-7.0, 3.0, -7.0, 1.0] } }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [1], "data": { "kind": "constant", "value": 0 }, "tolerance": 0 }
      }
    },
    {
      "name": "last_axis_split_scalar_logits_ties_last",
      "provenance": {
        "notes": "An unaligned 32,769-element row exercises scalar split-row reduction and verifies select_last_index across split boundaries."
      },
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": { "x": { "dtype": "float32", "shape": [1, 32769], "data": { "kind": "constant", "value": -5.0 } } },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [1], "data": { "kind": "constant", "value": 32768 }, "tolerance": 0 }
      }
    },
    {
      "name": "last_axis_split_vec4_i32_positive_rows",
      "provenance": {
        "notes": "A [2, 32768] int32 tensor's last axis cycles seven positive values (9, 5, 3, 1, 2, 4, 6), so a zero-initialized accumulator would misreport the minimum. Since 32768 is not a multiple of 7, row 1 begins one step into the cycle, putting its first-occurrence minimum at column 2 versus row 0's column 3."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": { "dtype": "int32", "shape": [2, 32768], "data": { "kind": "cycle", "values": [9, 5, 3, 1, 2, 4, 6] } }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [3, 2] }, "tolerance": 0 }
      }
    },
    {
      "name": "last_axis_split_scalar_u32_above_int32_max",
      "provenance": {
        "notes": "A [2, 32769] uint32 tensor's last axis cycles seven values; six of seven exceed 2^31 (up to 4,294,967,290, near UINT32_MAX), so a signed comparison would misorder them. Since 32769 is not a multiple of 7, row 1 begins two steps into the cycle, moving its minimum's column from 0 (row 0) to 5 (row 1)."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "uint32",
          "shape": [2, 32769],
          "data": {
            "kind": "cycle",
            "values": [2147483000, 4200000000, 3000000000, 4294967290, 2500000000, 3500000000, 4000000000]
          }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [0, 5] }, "tolerance": 0 }
      }
    },
    {
      "name": "last_axis_split_vec4_f16_rows",
      "provenance": {
        "notes": "A rank-3 float16 tensor with 32,768-element rows exercises vec4 split-row reduction. Each component is widened before comparison, all seven cycle values are exactly representable, and ties select the first index."
      },
      "attrs": { "axis": 2, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 2, 32768],
          "data": { "kind": "cycle", "values": [1.5, -2.0, 0.5, 3.5, -1.0, 2.25, -3.75] }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [1, 2], "data": { "kind": "values", "values": [6, 5] }, "tolerance": 0 }
      }
    },
    {
      "name": "last_axis_split_scalar_f16_rows",
      "provenance": {
        "notes": "A rank-3 float16 tensor with 32,769-element rows exercises scalar split-row reduction. Loaded values are widened before comparison, all cycle values are exactly representable, and ties select the first index."
      },
      "attrs": { "axis": 2, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [1, 2, 32769],
          "data": { "kind": "cycle", "values": [1.5, -2.0, 0.5, 3.5, -1.0, 2.25, -3.75] }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [1, 2], "data": { "kind": "values", "values": [6, 4] }, "tolerance": 0 }
      }
    },
    {
      "name": "last_axis_split_vec4_ties_select_last_index",
      "provenance": {
        "notes": "select_last_index on the vec4 split-row route checks the last-index tie rule in both the segment reduction and combine. The minimum -7.0 recurs at cycle offsets 0, 2 and 5, so every segment reports a tie; the two phase-shifted rows must return 32767 and 32766."
      },
      "attrs": { "axis": 1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 32768],
          "data": { "kind": "cycle", "values": [-7.0, -3.0, -7.0, -1.0, -5.0, -7.0, -2.0] }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [32767, 32766] }, "tolerance": 0 }
      }
    },
    {
      "name": "rank5_middle_axis_generic_geometry",
      "provenance": {
        "notes": "A rank-5 middle-axis reduction exercises the rank-independent outer-axis-inner geometry."
      },
      "attrs": { "axis": 2, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 2, 3, 2, 2],
          "data": { "kind": "cycle", "values": [3.0, -5.0, -1.0, -5.0, -2.0, 1.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 2, 2, 2], "tolerance": 0 } }
    },
    {
      "name": "axis0_splitk_select_last_index_ties_8192x16",
      "provenance": {
        "notes": "On the split-tiled route, a 17-value cycle coprime with the 16 columns gives each column an approximately 482-way minimum tie. With select_last_index=1, each column must retain its final matching axis index across lane-local folds."
      },
      "attrs": { "axis": 0, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "int32",
          "shape": [8192, 16],
          "data": { "kind": "cycle", "values": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [16], "tolerance": 0 } }
    },
    {
      "name": "ort_wide_last_axis_3x40000_no_keepdims",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc",
        "test": "ReductionOpTest.ArgMin_float_wide_last_axis",
        "notes": "ArgMin twin of the upstream wide-last-axis case; duplicated minima make the lowest index the required answer."
      },
      "attrs": { "axis": 1, "keepdims": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 40000],
          "data": {
            "kind": "cycle",
            "values": [0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16.0, 16.5, 17.0, 17.5, 18.0, 18.5, 19.0, 19.5, 20.0, 20.5, 21.0, 21.5, 22.0, 22.5, 23.0, 23.5, 24.0, 24.5, 25.0, 25.5, 26.0, 26.5, 27.0, 27.5, 28.0, 28.5, 29.0, 29.5, 30.0, 30.5, 31.0, 31.5, 32.0, 32.5, 33.0, 33.5, 34.0, 34.5, 35.0, 35.5, 36.0, 36.5, 37.0, 37.5, 38.0, 38.5, 39.0, 39.5, 40.0, 40.5, 41.0, 41.5, 42.0, 42.5, 43.0, 43.5, 44.0, 44.5, 45.0, 45.5, 46.0, 46.5, 47.0, 47.5, 48.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [3], "tolerance": 0 } }
    },
    {
      "name": "packed_axis_columns_8192x32_ties_first",
      "provenance": {
        "notes": "A [8192, 32] float32 tensor's axis=-2 cycles a 13-value pattern whose minimum, -9.0, repeats three times per period; every column sees that tie across its 8192 rows, and select_last_index=0 resolves each to the earliest matching row."
      },
      "tunables": { "WORKGROUP_SIZE": 16 },
      "attrs": { "axis": -2, "keepdims": 0, "select_last_index": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8192, 32],
          "data": { "kind": "cycle", "values": [-3.0, 7.0, 7.0, -9.0, 2.0, 8.0, -9.0, 8.0, -1.0, 0.0, 2.0, 7.0, -9.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32], "tolerance": 0 } }
    },
    {
      "name": "packed_axis_columns_8192x32_ties_last",
      "provenance": {
        "notes": "A [8192, 32] float32 tensor's axis=-2 cycles a 13-value pattern whose minimum, -9.0, repeats three times per period; every column sees that tie across its 8192 rows, and select_last_index=1 resolves each to the latest matching row."
      },
      "tunables": { "WORKGROUP_SIZE": 16 },
      "attrs": { "axis": -2, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8192, 32],
          "data": { "kind": "cycle", "values": [-3.0, 7.0, 7.0, -9.0, 2.0, 8.0, -9.0, 8.0, -1.0, 0.0, 2.0, 7.0, -9.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [32], "tolerance": 0 } }
    },
    {
      "name": "packed_axis_columns_8193x28_ties_first",
      "provenance": {
        "notes": "A [8193, 28] float32 tensor's axis=-2 (one row more than the 8192-row case) cycles the same 13-value pattern, whose minimum -9.0 repeats three times per period; keepdims=1 keeps that axis as size 1 in a [1, 28] output, and select_last_index=0 resolves each column's tie to its earliest row."
      },
      "tunables": { "WORKGROUP_SIZE": 8 },
      "attrs": { "axis": -2, "keepdims": 1, "select_last_index": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8193, 28],
          "data": { "kind": "cycle", "values": [-3.0, 7.0, 7.0, -9.0, 2.0, 8.0, -9.0, 8.0, -1.0, 0.0, 2.0, 7.0, -9.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 28], "tolerance": 0 } }
    },
    {
      "name": "packed_axis_columns_8193x28_ties_last",
      "provenance": {
        "notes": "A [8193, 28] float32 tensor's axis=-2 (one row more than the 8192-row case) cycles the same 13-value pattern, whose minimum -9.0 repeats three times per period; keepdims=1 keeps that axis as size 1 in a [1, 28] output, and select_last_index=1 resolves each column's tie to its latest row."
      },
      "tunables": { "WORKGROUP_SIZE": 8 },
      "attrs": { "axis": -2, "keepdims": 1, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8193, 28],
          "data": { "kind": "cycle", "values": [-3.0, 7.0, 7.0, -9.0, 2.0, 8.0, -9.0, 8.0, -1.0, 0.0, 2.0, 7.0, -9.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [1, 28], "tolerance": 0 } }
    },
    {
      "name": "packed_axis_columns_2x8193x12_ties_first",
      "provenance": {
        "notes": "A [2, 8193, 12] float32 tensor's axis=-2 (the 8193-length middle axis) cycles the same 13-value pattern for each of the 2 batches' 12 columns; the minimum -9.0 repeats three times per period, and select_last_index=0 resolves each tie to its earliest row, giving a [2, 12] output."
      },
      "tunables": { "WORKGROUP_SIZE": 8 },
      "attrs": { "axis": -2, "keepdims": 0, "select_last_index": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 8193, 12],
          "data": { "kind": "cycle", "values": [-3.0, 7.0, 7.0, -9.0, 2.0, 8.0, -9.0, 8.0, -1.0, 0.0, 2.0, 7.0, -9.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 12], "tolerance": 0 } }
    },
    {
      "name": "packed_axis_columns_2x8193x12_ties_last",
      "provenance": {
        "notes": "A [2, 8193, 12] float32 tensor's axis=-2 (the 8193-length middle axis) cycles the same 13-value pattern for each of the 2 batches' 12 columns; the minimum -9.0 repeats three times per period, and select_last_index=1 resolves each tie to its latest row, giving a [2, 12] output."
      },
      "tunables": { "WORKGROUP_SIZE": 8 },
      "attrs": { "axis": -2, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [2, 8193, 12],
          "data": { "kind": "cycle", "values": [-3.0, 7.0, 7.0, -9.0, 2.0, 8.0, -9.0, 8.0, -1.0, 0.0, 2.0, 7.0, -9.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [2, 12], "tolerance": 0 } }
    },
    {
      "name": "adjacent_scalar_f32_1025_first",
      "provenance": {
        "notes": "Long scalar-row load ownership: a full four-value workgroup tile, odd row boundaries and repeated minima spanning lane/tile boundaries. Preserve exact first/last-index semantics."
      },
      "attrs": { "axis": -1, "keepdims": 0, "select_last_index": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 1025],
          "data": { "kind": "cycle", "values": [3.0, -7.0, 2.0, -7.0, 4.0, 5.0, 6.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [3], "tolerance": 0 } },
      "tolerance": 0,
      "relTolerance": 0
    },
    {
      "name": "adjacent_scalar_f32_1026_last",
      "provenance": {
        "notes": "Long scalar-row load ownership: a full four-value workgroup tile, odd row boundaries and repeated minima spanning lane/tile boundaries. Preserve exact first/last-index semantics."
      },
      "attrs": { "axis": -1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 1026],
          "data": { "kind": "cycle", "values": [3.0, -7.0, 2.0, -7.0, 4.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [3], "tolerance": 0 } },
      "tolerance": 0,
      "relTolerance": 0
    },
    {
      "name": "adjacent_scalar_f32_1027_first",
      "provenance": {
        "notes": "Long scalar-row load ownership: a full four-value workgroup tile, odd row boundaries and repeated minima spanning lane/tile boundaries. Preserve exact first/last-index semantics."
      },
      "attrs": { "axis": -1, "keepdims": 0, "select_last_index": 0 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 1027],
          "data": { "kind": "cycle", "values": [3.0, -7.0, 2.0, -7.0, 4.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [3], "tolerance": 0 } },
      "tolerance": 0,
      "relTolerance": 0
    },
    {
      "name": "adjacent_scalar_f32_4097_last",
      "provenance": {
        "notes": "Long scalar-row load ownership: a full four-value workgroup tile, odd row boundaries and repeated minima spanning lane/tile boundaries. Preserve exact first/last-index semantics."
      },
      "attrs": { "axis": -1, "keepdims": 0, "select_last_index": 1 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 4097],
          "data": { "kind": "cycle", "values": [3.0, -7.0, 2.0, -7.0, 4.0] }
        }
      },
      "outputs": { "y": { "dtype": "uint32", "shape": [3], "tolerance": 0 } },
      "tolerance": 0,
      "relTolerance": 0
    },
    {
      "name": "adjacent_scalar_f32_special_first",
      "provenance": {
        "notes": "Explicit workgroup32 crosses the adjacent-tile boundary at 129. Rows cover all positive infinity, signed-zero ties, non-leading NaNs, and tied negative infinity."
      },
      "attrs": { "axis": -1, "keepdims": 0, "select_last_index": 0 },
      "tunables": { "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 129],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/adjacent_scalar_f32_special_first_input_x" }
          }
        }
      },
      "outputs": {
        "y": { "dtype": "uint32", "shape": [4], "data": { "kind": "values", "values": [0, 0, 64, 1] }, "tolerance": 0 }
      },
      "tolerance": 0,
      "relTolerance": 0
    },
    {
      "name": "adjacent_scalar_f32_special_last",
      "provenance": {
        "notes": "Explicit workgroup32 crosses the adjacent-tile boundary at 129. Rows cover all positive infinity, signed-zero ties, non-leading NaNs, and tied negative infinity."
      },
      "attrs": { "axis": -1, "keepdims": 0, "select_last_index": 1 },
      "tunables": { "WORKGROUP_SIZE": 32 },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [4, 129],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/adjacent_scalar_f32_special_first_input_x" }
          }
        }
      },
      "outputs": {
        "y": {
          "dtype": "uint32",
          "shape": [4],
          "data": { "kind": "values", "values": [128, 128, 128, 127] },
          "tolerance": 0
        }
      },
      "tolerance": 0,
      "relTolerance": 0
    }
  ]
}