Download build/webgpu/test.json from webgpu-kernels/ai.onnx.Identity: direct link, hf CLI and curl.
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https://huggingface.co/kernels/webgpu-kernels/ai.onnx.Identity/resolve/v1/build/webgpu/test.json
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hf download hf://webgpu-kernels/ai.onnx.Identity@v1/build/webgpu/test.json
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curl -L -o test.json https://huggingface.co/kernels/webgpu-kernels/ai.onnx.Identity/resolve/v1/build/webgpu/test.json
9.74 kB
| { | |
| "cases": [ | |
| { | |
| "name": "int16_copy_boundaries", | |
| "inputs": { | |
| "x": { "dtype": "int16", "shape": [4], "data": { "kind": "values", "values": [-32768, -1, 0, 32767] } } | |
| }, | |
| "outputs": { | |
| "y": { | |
| "dtype": "int16", | |
| "shape": [4], | |
| "tolerance": 0, | |
| "data": { "kind": "values", "values": [-32768, -1, 0, 32767] } | |
| } | |
| } | |
| }, | |
| { | |
| "name": "float32_copy", | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [3, 7], | |
| "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29 } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 7], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "ort_float_2x2", | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/tensor/identity_op_test.cc", | |
| "test": "Identity.FloatType" | |
| }, | |
| "inputs": { | |
| "x": { "dtype": "float32", "shape": [2, 2], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0] } } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 2], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "onnx_backend_nchw_copy", | |
| "provenance": { | |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_identity", | |
| "test": "test_identity" | |
| }, | |
| "inputs": { | |
| "x": { "dtype": "float32", "shape": [1, 1, 2, 2], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0] } } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 1, 2, 2], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "float32_scalar_copy", | |
| "inputs": { "x": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": ["NaN"] } } }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0.000001, "allowNaN": true } } | |
| }, | |
| { | |
| "name": "float16_copy", | |
| "inputs": { | |
| "x": { | |
| "dtype": "float16", | |
| "shape": [2, 3], | |
| "data": { "kind": "values", "values": [-5.0, -1.0, 0.0, 1.0, 5.0, 9.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 3], "tolerance": 0.001 } } | |
| }, | |
| { | |
| "name": "uint32_copy", | |
| "inputs": { | |
| "x": { | |
| "dtype": "uint32", | |
| "shape": [2, 3], | |
| "data": { "kind": "values", "values": [0, 1, 2, 4294967295, 17, 99] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "uint32", "shape": [2, 3], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "bool_exact_copy", | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/tensor/identity_op_test.cc", | |
| "test": "Identity.FloatType", | |
| "notes": "Same tensor-copy behavior as ORT's numeric fixture, using ONNX-valid bool payloads." | |
| }, | |
| "inputs": { | |
| "x": { "dtype": "bool", "shape": [2, 3], "data": { "kind": "values", "values": [0, 1, 1, 0, 1, 0] } } | |
| }, | |
| "outputs": { | |
| "y": { | |
| "dtype": "bool", | |
| "shape": [2, 3], | |
| "data": { "kind": "values", "values": [0, 1, 1, 0, 1, 0] }, | |
| "tolerance": 0 | |
| } | |
| } | |
| }, | |
| { | |
| "name": "ort_int32_copy_dtype_path", | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/tensor/identity_op_test.cc", | |
| "test": "Identity.FloatType", | |
| "notes": "Same tensor-copy behavior as ORT's float fixture, using supported native int32 storage." | |
| }, | |
| "inputs": { | |
| "x": { "dtype": "int32", "shape": [2, 2], "data": { "kind": "values", "values": [-3, 0, 7, 2147483647] } } | |
| }, | |
| "outputs": { "y": { "dtype": "int32", "shape": [2, 2], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "ort_int8_copy_edge_values", | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/tensor/identity_op_test.cc", | |
| "test": "Identity.FloatType", | |
| "notes": "Same tensor-copy behavior as ORT's float fixture, using logical int8 edge values." | |
| }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "int8", | |
| "shape": [2, 4], | |
| "data": { "kind": "values", "values": [-128, -5, -1, 0, 1, 5, 100, 127] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "int8", "shape": [2, 4], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "ort_uint8_copy_edge_values", | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/tensor/identity_op_test.cc", | |
| "test": "Identity.FloatType", | |
| "notes": "Same tensor-copy behavior as ORT's float fixture, using logical uint8 edge values." | |
| }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "uint8", | |
| "shape": [2, 4], | |
| "data": { "kind": "values", "values": [0, 1, 2, 127, 128, 200, 254, 255] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "uint8", "shape": [2, 4], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "ort_float16_copy_nonfinite_values", | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/tensor/identity_op_test.cc", | |
| "test": "Identity.FloatType", | |
| "notes": "Same tensor-copy behavior as ORT's float fixture, using float16 nonfinite payloads." | |
| }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float16", | |
| "shape": [2, 4], | |
| "data": { "kind": "values", "values": ["NaN", "-Infinity", 0.0, 0.0, 1.0, -2.0, 65504.0, "Infinity"] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 4], "tolerance": 0, "allowNaN": true } } | |
| }, | |
| { | |
| "name": "zero_sized_copy", | |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 0, 3], "data": { "kind": "values", "values": [] } } }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 0, 3], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "onnx_backend_clip_default_inbounds_expanded", | |
| "provenance": { | |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_clip_default_inbounds_expanded", | |
| "notes": "The official expanded Clip default-inbounds function lowers to Identity for this node fixture." | |
| }, | |
| "inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1.0, 0.0, 1.0] } } }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "onnx_backend_clip_default_int8_inbounds_expanded", | |
| "provenance": { | |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_clip_default_int8_inbounds_expanded", | |
| "notes": "The official expanded Clip default-inbounds function lowers to Identity for this node fixture." | |
| }, | |
| "inputs": { "x": { "dtype": "int8", "shape": [3], "data": { "kind": "values", "values": [-1, 0, 1] } } }, | |
| "outputs": { "y": { "dtype": "int8", "shape": [3], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "f16_vec4_copy_2x4", | |
| "inputs": { | |
| "x": { | |
| "dtype": "float16", | |
| "shape": [2, 4], | |
| "data": { "kind": "values", "values": [1.0, -2.0, 3.5, -4.5, 5.0, -6.0, 7.25, -8.75] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 4], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "scalar_copy_dispatch_clamp", | |
| "provenance": { | |
| "notes": "An identity copy of 262,141 elements, one more than 65,535 groups of four and past the WebGPU per-dimension workgroup limit; every element must be copied exactly once." | |
| }, | |
| "tunables": { "WORKGROUP_SIZE": 4 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [262141], | |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.31 } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [262141], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "int32_numel2_scalar_copy", | |
| "inputs": { | |
| "x": { "dtype": "int32", "shape": [2], "data": { "kind": "values", "values": [-2147483648, 2147483647] } } | |
| }, | |
| "outputs": { "y": { "dtype": "int32", "shape": [2], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "f16_numel3_scalar_copy_edge_values", | |
| "inputs": { | |
| "x": { | |
| "dtype": "float16", | |
| "shape": [3], | |
| "data": { "kind": "values", "values": ["Infinity", "-Infinity", 65504.0] } | |
| } | |
| }, | |
| "outputs": { | |
| "y": { | |
| "dtype": "float16", | |
| "shape": [3], | |
| "data": { "kind": "values", "values": ["Infinity", "-Infinity", 65504.0] }, | |
| "tolerance": 0, | |
| "allowNaN": false | |
| } | |
| } | |
| }, | |
| { | |
| "name": "empty_zero_in_middle_dim", | |
| "inputs": { "x": { "dtype": "float32", "shape": [3, 0, 5], "data": { "kind": "values", "values": [] } } }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 0, 5], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "int64_full_range_int16_copy_boundaries", | |
| "inputs": { | |
| "x": { | |
| "dtype": "int64", | |
| "shape": [4], | |
| "data": { | |
| "kind": "cycle", | |
| "values": ["0", "4294967296", "8589934593", "-4294967297", "9223372036854775807", "-9223372036854775808", "9223372036854775806", "-1"] | |
| } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "int64", "shape": [4], "tolerance": 0, "relTolerance": 0 } }, | |
| "tolerance": 0, | |
| "relTolerance": 0 | |
| }, | |
| { | |
| "name": "int64_full_range_float32_copy", | |
| "inputs": { | |
| "x": { | |
| "dtype": "int64", | |
| "shape": [3, 7], | |
| "data": { | |
| "kind": "cycle", | |
| "values": ["4294967296", "8589934593", "-4294967297", "9223372036854775807", "-9223372036854775808", "9223372036854775806", "-1", "0"] | |
| } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "int64", "shape": [3, 7], "tolerance": 0, "relTolerance": 0 } }, | |
| "tolerance": 0, | |
| "relTolerance": 0 | |
| } | |
| ] | |
| } | |