| { |
| "op": "ai.onnx.SpaceToDepth", |
| "fixtureArrays": { |
| "onnx_backend_example_1x1x4x6_input_input": [0, 6, 1, 7, 2, 8, 12, 18, 13, 19, 14, 20, 3, 9, 4, 10, 5, 11, 15, 21, 16, 22, 17, 23] |
| }, |
| "cases": [ |
| { |
| "name": "dispatch_cliff_nchw_channel_heavy", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 4194241, 2, 2], |
| "data": { "kind": "linspace", "start": 0.0, "end": 1.0 } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 16776964, 1, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "nchw", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 1, 4, 4], |
| "data": { |
| "kind": "values", |
| "values": [0.0, 10.0, 1.0, 11.0, 20.0, 30.0, 21.0, 31.0, 2.0, 12.0, 3.0, 13.0, 22.0, 32.0, 23.0, 33.0] |
| } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 4, 2, 2] } } |
| }, |
| { |
| "name": "nchw_block3_multichannel", |
| "attrs": { "blocksize": 3 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 2, 6, 3], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.29 } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 18, 2, 1] } } |
| }, |
| { |
| "name": "nchw_f16_batch2_block2", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float16", |
| "shape": [2, 1, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, -1.0, -2.0, -3.0, -4.0] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float16", "shape": [2, 4, 1, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "empty_zero_height_block2", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { "input": { "dtype": "float32", "shape": [1, 1, 0, 4] } }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 4, 0, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "onnx_backend_example_1x1x4x6", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 1, 4, 6], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_example_1x1x4x6_input_input" } } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 4, 2, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_block2_two_channels_wide", |
| "attrs": { "blocksize": 2 }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/space_depth_ops_test.cc", |
| "test": "TensorOpTest.SpaceToDepthTest_1" |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 2, 2, 4], |
| "data": { |
| "kind": "values", |
| "values": [0.0, 0.1, 0.2, 0.3, 1.0, 1.1, 1.2, 1.3, 2.0, 2.1, 2.2, 2.3, 3.0, 3.1, 3.2, 3.3] |
| } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 8, 1, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_block2_two_channels_tall_and_wide", |
| "attrs": { "blocksize": 2 }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/space_depth_ops_test.cc", |
| "test": "TensorOpTest.SpaceToDepthTest_3" |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 2, 4, 8], |
| "data": { |
| "kind": "values", |
| "values": [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 4.0, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7] |
| } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 8, 2, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "f16_block3_single_pixel_output", |
| "attrs": { "blocksize": 3 }, |
| "inputs": { |
| "input": { |
| "dtype": "float16", |
| "shape": [1, 1, 3, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float16", "shape": [1, 9, 1, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_block3_batch2_channels3", |
| "attrs": { "blocksize": 3 }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/space_depth_ops_test.cc", |
| "test": "TensorOpTest.SpaceToDepthTest_2", |
| "notes": "Uses the ORT shape/blocksize; fixture values are generated deterministically." |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 3, 3, 6], |
| "data": { "kind": "fillFloat32", "sinStep": 0.01, "cosStep": 0.0, "scale": 100.0 } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 27, 1, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "onnx_backend_spacetodepth", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 2, 6, 6], |
| "data": { |
| "kind": "values", |
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| } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 8, 3, 3] } }, |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_spacetodepth" } |
| }, |
| { |
| "name": "onnx_backend_spacetodepth_example", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 1, 4, 6], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_example_1x1x4x6_input_input" } } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 4, 2, 3] } }, |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_spacetodepth_example" } |
| }, |
| { |
| "name": "empty_zero_dim", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { "input": { "dtype": "float32", "shape": [0, 1, 4, 4], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "output": { "dtype": "float32", "shape": [0, 4, 2, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "empty_zero_dim_f16", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { "input": { "dtype": "float16", "shape": [0, 1, 4, 4], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "output": { "dtype": "float16", "shape": [0, 4, 2, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "nchw_block4_multichannel", |
| "attrs": { "blocksize": 4 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 3, 8, 16], |
| "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.07 } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 48, 2, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "nchw_block4_f16", |
| "attrs": { "blocksize": 4 }, |
| "inputs": { |
| "input": { |
| "dtype": "float16", |
| "shape": [1, 2, 4, 16], |
| "data": { |
| "kind": "values", |
| "values": [-8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0] |
| } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float16", "shape": [1, 32, 1, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "nchw_block1_identity", |
| "attrs": { "blocksize": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 2, 2, 4], |
| "data": { |
| "kind": "values", |
| "values": [-5.0, -3.5, -2.0, -0.5, 1.0, 2.5, 4.0, 5.5, 7.0, 8.5, 10.0, 11.5, 13.0, 14.5, 16.0, 17.5] |
| } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 2, 2, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "nchw_const_odd_width_block2_addressing", |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 2, 4, 6], |
| "data": { "kind": "fillFloat32", "sinStep": 0.09, "cosStep": 0.21 } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 8, 2, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "nchw_const_block3_odd_width_multichannel", |
| "attrs": { "blocksize": 3 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 2, 6, 15], |
| "data": { "kind": "fillFloat32", "sinStep": 0.05, "cosStep": 0.17 } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 18, 2, 5], "tolerance": 0 } } |
| }, |
| { |
| "name": "nchw_vec4_block3_width_mul4_multichannel", |
| "attrs": { "blocksize": 3 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1, 2, 6, 12], |
| "data": { "kind": "fillFloat32", "sinStep": 0.15, "cosStep": 0.11 } |
| } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1, 18, 2, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_standard_int32_block2_extremes", |
| "provenance": { |
| "source": "onnx/docs/Operators.md#SpaceToDepth", |
| "notes": "ONNX SpaceToDepth-13 permits int32; signed extrema prove the widened i32 route is a bit-exact permutation." |
| }, |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "int32", |
| "shape": [1, 1, 2, 4], |
| "data": { "kind": "values", "values": [-2147483648, 2147483647, -16777217, 16777217, -1, 0, 42, -42] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "int32", "shape": [1, 4, 1, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_standard_int16_block2_extremes", |
| "provenance": { |
| "source": "onnx/docs/Operators.md#SpaceToDepth", |
| "notes": "ONNX SpaceToDepth-13 permits int16; both signed extrema guard the runtime's widened i32 storage route." |
| }, |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "int16", |
| "shape": [1, 1, 2, 4], |
| "data": { "kind": "values", "values": [-32768, 32767, -12345, 12345, -1, 0, 42, -42] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "int16", "shape": [1, 4, 1, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_standard_int8_block2_extremes", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/space_depth_ops_test.cc", |
| "test": "TensorOpTest.SpaceToDepthTest_int_opset13", |
| "notes": "Uses both int8 extrema so the widened i32 storage route cannot hide narrowing or sign loss." |
| }, |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "int8", |
| "shape": [1, 1, 2, 4], |
| "data": { "kind": "values", "values": [-128, 127, -64, 63, -1, 0, 42, -42] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "int8", "shape": [1, 4, 1, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_standard_uint32_block2_extremes", |
| "provenance": { |
| "source": "onnx/docs/Operators.md#SpaceToDepth", |
| "notes": "ONNX SpaceToDepth-13 permits uint32; values across the signed boundary and UINT32_MAX guard exact u32 payload movement." |
| }, |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "uint32", |
| "shape": [1, 1, 2, 4], |
| "data": { "kind": "values", "values": [0, 4294967295, 16777217, 2147483648, 1, 42, 4000000000, 255] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "uint32", "shape": [1, 4, 1, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_standard_uint8_block2_extremes", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/space_depth_ops_test.cc", |
| "test": "TensorOpTest.SpaceToDepthTest_int_opset13", |
| "notes": "Includes UINT8_MAX and values around the signed boundary on the widened u32 storage route." |
| }, |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "uint8", |
| "shape": [1, 1, 2, 4], |
| "data": { "kind": "values", "values": [0, 255, 127, 128, 1, 42, 254, 64] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "uint8", "shape": [1, 4, 1, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_standard_bool_block2_pattern", |
| "provenance": { |
| "source": "onnx/docs/Operators.md#SpaceToDepth", |
| "notes": "ONNX SpaceToDepth-13 permits bool; an asymmetric pattern checks that widened u32 boolean payloads are reordered without conversion." |
| }, |
| "attrs": { "blocksize": 2 }, |
| "inputs": { |
| "input": { |
| "dtype": "bool", |
| "shape": [1, 1, 2, 4], |
| "data": { "kind": "values", "values": [0, 1, 1, 0, 1, 1, 0, 0] } |
| } |
| }, |
| "outputs": { "output": { "dtype": "bool", "shape": [1, 4, 1, 2], "tolerance": 0 } } |
| } |
| ] |
| } |
|
|
