Download build/webgpu/test.json from webgpu-kernels/ai.onnx.Swish: direct link, hf CLI and curl.
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https://huggingface.co/kernels/webgpu-kernels/ai.onnx.Swish/resolve/v1/build/webgpu/test.json
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hf download hf://webgpu-kernels/ai.onnx.Swish@v1/build/webgpu/test.json
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curl -L -o test.json https://huggingface.co/kernels/webgpu-kernels/ai.onnx.Swish/resolve/v1/build/webgpu/test.json
9.15 kB
| { | |
| "cases": [ | |
| { | |
| "name": "f32_values", | |
| "attrs": { "alpha": 1.5 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [6], | |
| "data": { "kind": "values", "values": [-3.0, -1.0, 0.0, 0.5, 1.0, 3.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [6], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "f32_alpha_zero_subnormal_half_gate_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 (f32 and f16); the kernel cannot preserve denormal inputs/outputs bit-exactly." | |
| }, | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc", | |
| "test": "ActivationOpTest.Swish", | |
| "notes": "With alpha=0, Swish is exactly x/2, so signed subnormal inputs should not disappear." | |
| }, | |
| "attrs": { "alpha": 0 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [4], | |
| "data": { "kind": "values", "values": [-1e-39, -1e-40, 1e-40, 1e-39] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 0 } } | |
| }, | |
| { | |
| "name": "f32_alpha_zero_subnormal_half_gate_scalar_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 (f32 and f16); the kernel cannot preserve denormal inputs/outputs bit-exactly." | |
| }, | |
| "provenance": { | |
| "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc", | |
| "test": "ActivationOpTest.Swish", | |
| "notes": "On the scalar path with alpha=0, Swish is exactly x/2 for signed subnormal inputs." | |
| }, | |
| "attrs": { "alpha": 0 }, | |
| "inputs": { | |
| "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1e-40, 0.0, 1e-40] } } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 1e-43 } } | |
| }, | |
| { | |
| "name": "f32_extreme_finite_stability", | |
| "attrs": { "alpha": 1 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [9], | |
| "data": { "kind": "values", "values": [-1000.0, -100.0, -20.0, -1.0, 0.0, 1.0, 20.0, 100.0, 1000.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [9], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "f32_alpha_zero_halves_input", | |
| "attrs": { "alpha": 0 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [7], | |
| "data": { "kind": "values", "values": [-100.0, -3.0, -0.5, 0.0, 0.5, 3.0, 100.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [7], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "f32_negative_alpha_extreme_finite_stability", | |
| "attrs": { "alpha": -1 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [9], | |
| "data": { "kind": "values", "values": [-1000.0, -100.0, -20.0, -1.0, 0.0, 1.0, 20.0, 100.0, 1000.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [9], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "f32_nan_input", | |
| "attrs": { "alpha": 0.75 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [5], | |
| "data": { "kind": "values", "values": ["NaN", -4.0, 0.0, 4.0, "NaN"] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.000001, "allowNaN": true } } | |
| }, | |
| { | |
| "name": "f32_nonfinite_endpoints_alpha_one", | |
| "provenance": { | |
| "notes": "Nonfinite edge: -Infinity follows the literal formula into NaN, +Infinity stays +Infinity." | |
| }, | |
| "attrs": { "alpha": 1 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [6], | |
| "data": { "kind": "values", "values": ["-Infinity", -1.0, 0.0, 1.0, "Infinity", "NaN"] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [6], "tolerance": 0.000001, "allowNaN": true } } | |
| }, | |
| { | |
| "name": "rank0_negative_alpha_scalar", | |
| "attrs": { "alpha": -0.5 }, | |
| "inputs": { "x": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [4.0] } } }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "f16_values", | |
| "attrs": { "alpha": 1.25 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float16", | |
| "shape": [7], | |
| "data": { "kind": "values", "values": [-12.0, -4.0, -0.5, 0.0, 0.5, 4.0, 12.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float16", "shape": [7], "tolerance": 0.001 } } | |
| }, | |
| { | |
| "name": "f16_alpha_zero_halves_input", | |
| "attrs": { "alpha": 0 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float16", | |
| "shape": [7], | |
| "data": { "kind": "values", "values": [-16.0, -4.0, -0.5, 0.0, 0.5, 4.0, 16.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float16", "shape": [7], "tolerance": 0.001 } } | |
| }, | |
| { | |
| "name": "onnx_backend_empty_rank4", | |
| "provenance": { | |
| "source": "cmake/external/onnx/onnx/backend/test/case/node/swish.py", | |
| "test": "Swish.export", | |
| "notes": "Elementwise empty tensor edge: preserve a zero inner dimension with no work items." | |
| }, | |
| "attrs": { "alpha": 1 }, | |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 2, 0, 3], "data": { "kind": "values", "values": [] } } }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2, 0, 3] } } | |
| }, | |
| { | |
| "name": "onnx_backend_expanded_alpha_two_rank3", | |
| "provenance": { | |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_swish_expanded", | |
| "test": "test_swish_expanded", | |
| "notes": "Compact rank-3 projection with alpha != 1 to stress the generated formula path." | |
| }, | |
| "attrs": { "alpha": 2 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [1, 2, 4], | |
| "data": { "kind": "values", "values": [-20.0, -2.0, -0.5, 0.0, 0.5, 2.0, 20.0, 40.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2, 4], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "onnx_backend_alpha_one_example", | |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_swish", "test": "test_swish" }, | |
| "attrs": { "alpha": 1 }, | |
| "inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [3.0, 4.0, 5.0] } } }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "vec4_f16_lanes", | |
| "inputs": { | |
| "x": { | |
| "dtype": "float16", | |
| "shape": [16], | |
| "data": { | |
| "kind": "values", | |
| "values": [-6.0, -4.0, -3.0, -2.0, -1.5, -1.0, -0.5, -0.25, 0.0, 0.25, 0.5, 1.0, 1.5, 2.0, 4.0, 6.0] | |
| } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float16", "shape": [16], "tolerance": 0.001, "relTolerance": 0.002 } } | |
| }, | |
| { | |
| "name": "alpha_zero_vec4_path", | |
| "attrs": { "alpha": 0 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [8], | |
| "data": { "kind": "values", "values": [-100.0, -3.0, -0.5, 0.0, 0.5, 3.0, 10.0, 100.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [8], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "nondefault_alpha_vec4_large_negative", | |
| "attrs": { "alpha": -2.5 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [8], | |
| "data": { "kind": "values", "values": [-10.0, -5.0, -1.0, -0.5, 0.0, 0.5, 1.0, 10.0] } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [8], "tolerance": 0.000001 } } | |
| }, | |
| { | |
| "name": "f32_vec4_sustained_4096", | |
| "provenance": { "notes": "A compact aligned float32 payload exercises vectorized Swish." }, | |
| "attrs": { "alpha": 1 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [4096], | |
| "data": { "kind": "fillFloat32", "sinStep": 0.013, "cosStep": 0.019, "scale": 2.0 } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [4096], "tolerance": 0.00001, "relTolerance": 0.00001 } } | |
| }, | |
| { | |
| "name": "f32_scalar_tail_4097", | |
| "provenance": { "notes": "An element count not divisible by four exercises scalar Swish." }, | |
| "attrs": { "alpha": 1 }, | |
| "inputs": { | |
| "x": { | |
| "dtype": "float32", | |
| "shape": [4097], | |
| "data": { "kind": "fillFloat32", "sinStep": 0.017, "cosStep": 0.023, "scale": 2.0 } | |
| } | |
| }, | |
| "outputs": { "y": { "dtype": "float32", "shape": [4097], "tolerance": 0.00001, "relTolerance": 0.00001 } } | |
| } | |
| ] | |
| } | |