| { |
| "op": "ai.onnx.Compress", |
| "cases": [ |
| { |
| "name": "int16_axis_copy_boundaries", |
| "attrs": { "axis": 0 }, |
| "inputs": { |
| "input": { |
| "dtype": "int16", |
| "shape": [4, 2], |
| "data": { "kind": "values", "values": [-32768, 32767, -1, 0, 1, -2, 32766, -32767] } |
| }, |
| "condition": { "dtype": "bool", "shape": [4], "data": { "kind": "values", "values": [1, 0, 1, 1] } } |
| }, |
| "outputs": { |
| "output": { |
| "dtype": "int16", |
| "shape": [3, 2], |
| "tolerance": 0, |
| "data": { "kind": "values", "values": [-32768, 32767, 1, -2, 32766, -32767] } |
| } |
| } |
| }, |
| { |
| "name": "flatten_vit_token_prune_parallel_threshold", |
| "inputs": { |
| "input": { "dtype": "float32", "shape": [768], "data": { "kind": "linspace", "start": -1.0, "end": 1.0 } }, |
| "condition": { "dtype": "bool", "shape": [768], "data": { "kind": "cycle", "values": [1, 0] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [384], "tolerance": 0 } } |
| }, |
| { |
| "name": "axis0_f32", |
| "attrs": { "axis": 0 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "condition": { "dtype": "bool", "shape": [3], "data": { "kind": "values", "values": [0, 1, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 2] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress0" |
| } |
| }, |
| { |
| "name": "axis1_f32", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [3, 1] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress1" |
| } |
| }, |
| { |
| "name": "axis1_3d_f32", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 2, 3], |
| "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] } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 1, 3] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_3dims" |
| } |
| }, |
| { |
| "name": "ort_axis1_long_condition_parallel_scan_compaction", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_3dims", |
| "notes": "Extends ORT's axis=1 3D case to a long axis with a nontrivial true/false pattern so the WebGPU axis parallel prefix-scan path is exercised." |
| }, |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 1030, 2], |
| "data": { "kind": "linspace", "start": 0.0, "end": 4119.0 } |
| }, |
| "condition": { "dtype": "bool", "shape": [1030], "data": { "kind": "cycle", "values": [1, 0, 1, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 772, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "all_false_zero_axis_dim", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 2, 3], |
| "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] } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 0] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 0, 3] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_condition_all_false" |
| } |
| }, |
| { |
| "name": "extra_condition_ignored", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 2, 3], |
| "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] } |
| }, |
| "condition": { "dtype": "bool", "shape": [3], "data": { "kind": "values", "values": [0, 1, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 1, 3] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_3dims_has_extra_condition" |
| } |
| }, |
| { |
| "name": "short_condition_ignores_extra_input_axis_values", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 3, 3], |
| "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, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0] |
| } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 1, 3] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_3dims_has_extra_input" |
| } |
| }, |
| { |
| "name": "default_axis_flatten_f32", |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "condition": { "dtype": "bool", "shape": [5], "data": { "kind": "values", "values": [0, 1, 0, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_default_axis" |
| } |
| }, |
| { |
| "name": "ort_default_axis_all_true_parallel_scan_over_1024", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_default_axis_issue_9247_cumulative_sum_overflow", |
| "notes": "Extends ORT's >127-element cumulative-sum regression above 1024 elements so the WebGPU parallel prefix-scan path is exercised." |
| }, |
| "inputs": { |
| "input": { "dtype": "float32", "shape": [23, 50], "data": { "kind": "linspace", "start": 0.0, "end": 1149.0 } }, |
| "condition": { "dtype": "bool", "shape": [1150], "data": { "kind": "constant", "value": 1 } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [1150], "tolerance": 0 } } |
| }, |
| { |
| "name": "negative_axis_f32", |
| "attrs": { "axis": -2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 2, 3], |
| "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] } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 1, 3] } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_3dims_neg_axis" |
| } |
| }, |
| { |
| "name": "axis0_uint32", |
| "attrs": { "axis": 0 }, |
| "inputs": { |
| "input": { "dtype": "uint32", "shape": [3, 2], "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6] } }, |
| "condition": { "dtype": "bool", "shape": [3], "data": { "kind": "values", "values": [1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "uint32", "shape": [2, 2] } } |
| }, |
| { |
| "name": "axis1_f16", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float16", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "condition": { "dtype": "bool", "shape": [3], "data": { "kind": "values", "values": [1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float16", "shape": [2, 2] } }, |
| "tolerance": 0.001 |
| }, |
| { |
| "name": "ort_default_axis_issue_9247_all_true_150", |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 75], |
| "data": { "kind": "fillFloat32", "sinStep": 0.07, "cosStep": 0.11, "scale": 1.0 } |
| }, |
| "condition": { "dtype": "bool", "shape": [150], "data": { "kind": "constant", "value": 1 } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [150], "tolerance": 0 } }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_default_axis_issue_9247_cumulative_sum_overflow" |
| } |
| }, |
| { |
| "name": "onnx_backend_compress_negative_axis", |
| "attrs": { "axis": -1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [3, 1] } }, |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_compress_negative_axis" } |
| }, |
| { |
| "name": "parallel_flatten_exact_output_f32", |
| "provenance": { |
| "notes": "262144 flattened elements with an alternating condition exercise the three-pass scan with the exact 131072-element ONNX output extent." |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [512, 512], |
| "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29 } |
| }, |
| "condition": { "dtype": "bool", "shape": [262144], "data": { "kind": "cycle", "values": [1, 0] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [131072], "tolerance": 0 } } |
| }, |
| { |
| "name": "parallel_flatten_condition_shorter_u32", |
| "provenance": { |
| "notes": "Condition shorter than the flattened input: the scan limit is min(inputCount, conditionCount) = 3000 and trailing input elements are dropped." |
| }, |
| "inputs": { |
| "input": { "dtype": "uint32", "shape": [8192], "data": { "kind": "cycle", "values": [5, 7, 11, 2, 9] } }, |
| "condition": { "dtype": "bool", "shape": [3000], "data": { "kind": "cycle", "values": [0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "uint32", "shape": [1500] } } |
| }, |
| { |
| "name": "parallel_axis1_3d_f32", |
| "attrs": { "axis": 1 }, |
| "provenance": { |
| "notes": "Middle-axis parallel compress: the scan runs over 300 axis flags and the scatter covers all 76800 elements in parallel." |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [64, 300, 4], |
| "data": { "kind": "fillFloat32", "sinStep": 0.11, "cosStep": 0.23 } |
| }, |
| "condition": { "dtype": "bool", "shape": [300], "data": { "kind": "cycle", "values": [1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [64, 200, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "parallel_axis_negative_f16", |
| "attrs": { "axis": -2 }, |
| "provenance": { |
| "notes": "Negative axis + f16 payload + condition shorter than the axis (1024 < 2048); axis positions past the condition are dropped." |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float16", |
| "shape": [2, 2048, 4], |
| "data": { "kind": "cycle", "values": [0.5, 1.5, -2.0, 3.0] } |
| }, |
| "condition": { "dtype": "bool", "shape": [1024], "data": { "kind": "cycle", "values": [1, 0, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float16", "shape": [2, 512, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "parallel_axis0_condition_extra_f32", |
| "attrs": { "axis": 0 }, |
| "provenance": { |
| "notes": "Condition longer than the axis (2000 > 1500); extra condition entries are ignored. 900 of 1500 rows selected." |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [1500, 8], |
| "data": { "kind": "fillFloat32", "sinStep": 0.19, "cosStep": 0.41 } |
| }, |
| "condition": { "dtype": "bool", "shape": [2000], "data": { "kind": "cycle", "values": [1, 0, 1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [900, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_bool_exact_condition_default_axis", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_default_axis" |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "condition": { "dtype": "bool", "shape": [5], "data": { "kind": "values", "values": [0, 1, 0, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_bool_exact_condition_negative_axis", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_3dims_neg_axis", |
| "notes": "Exact ORT negative-axis fixture with an ONNX bool condition." |
| }, |
| "attrs": { "axis": -2 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 2, 3], |
| "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] } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 1, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "bool_payload_axis1", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress1", |
| "notes": "Same axis=1 compaction pattern as ORT's fixture, using ONNX-valid bool payload tensors." |
| }, |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { "dtype": "bool", "shape": [2, 3], "data": { "kind": "values", "values": [1, 0, 1, 0, 1, 0] } }, |
| "condition": { "dtype": "bool", "shape": [3], "data": { "kind": "values", "values": [1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "bool", "shape": [2, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "bool_payload_axis1_all_false_zero_dim", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/tensor/compress_op.test.cc", |
| "test": "CompressTest.Compress_condition_all_false", |
| "notes": "All-false axis condition from ORT's zero-output case, using ONNX-valid bool payload tensors." |
| }, |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "bool", |
| "shape": [2, 2, 3], |
| "data": { "kind": "values", "values": [1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1] } |
| }, |
| "condition": { "dtype": "bool", "shape": [2], "data": { "kind": "values", "values": [0, 0] } } |
| }, |
| "outputs": { "output": { "dtype": "bool", "shape": [2, 0, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "int8_payload_axis1_parallel_scatter", |
| "provenance": { |
| "notes": "int8 activation payload through the axis_parallel_scan scatter (numel 12288 > 1024). int8 stores as i32 per scalarType, so the $scalar copy path is exercised with the full s8 range incl -128/127. ORT CPU runs Compress for int8." |
| }, |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "int8", |
| "shape": [16, 96, 8], |
| "data": { "kind": "cycle", "values": [-128, -1, 0, 1, 127, 42, -77, 5] } |
| }, |
| "condition": { "dtype": "bool", "shape": [96], "data": { "kind": "cycle", "values": [1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "int8", "shape": [16, 64, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "uint8_payload_flatten_parallel_scatter", |
| "provenance": { |
| "notes": "uint8 payload through flatten_parallel_scan (numel 4096 > 1024). uint8 widens to u32; covers the full 0..255 range through the 3-pass predicate-scan scatter. ORT CPU runs Compress for uint8." |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "uint8", |
| "shape": [4096], |
| "data": { "kind": "cycle", "values": [0, 1, 127, 128, 200, 255] } |
| }, |
| "condition": { "dtype": "bool", "shape": [4096], "data": { "kind": "cycle", "values": [1, 1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "uint8", "shape": [3072], "tolerance": 0 } } |
| }, |
| { |
| "name": "int32_large_magnitude_above_2pow24_flatten", |
| "provenance": { |
| "notes": "int32 payload with magnitudes above 2^24 (incl ±2e9) through flatten_parallel_scan. Verifies the i32 scatter copy preserves values that would be lossy if carried through f32; comparison uses the int32 dtype so it stays exact. ORT CPU runs Compress for int32." |
| }, |
| "inputs": { |
| "input": { |
| "dtype": "int32", |
| "shape": [4096], |
| "data": { "kind": "cycle", "values": [16777217, 33554433, -100000000, 2000000000, -2000000000, 16777216] } |
| }, |
| "condition": { "dtype": "bool", "shape": [4096], "data": { "kind": "cycle", "values": [1, 0] } } |
| }, |
| "outputs": { "output": { "dtype": "int32", "shape": [2048], "tolerance": 0 } } |
| }, |
| { |
| "name": "int32_axis0_serial_fallback", |
| "provenance": { |
| "notes": "int32 payload, axis=0, and a compact input select the serial axis kernel. Large-magnitude values confirm the single-lane copy is exact for i32; ORT CPU runs Compress for int32." |
| }, |
| "attrs": { "axis": 0 }, |
| "inputs": { |
| "input": { |
| "dtype": "int32", |
| "shape": [16, 8], |
| "data": { "kind": "cycle", "values": [100000000, -100000000, 7, -7] } |
| }, |
| "condition": { "dtype": "bool", "shape": [16], "data": { "kind": "cycle", "values": [1, 0, 1, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "int32", "shape": [12, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "bool_condition_axis0_selectable", |
| "provenance": { "notes": "Bool condition selects the first and last slices along axis 0." }, |
| "attrs": { "axis": 0 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [4, 3], |
| "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] } |
| }, |
| "condition": { "dtype": "bool", "shape": [4], "data": { "kind": "values", "values": [1, 0, 1, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [3, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "bool_payload_flatten_parallel_scan_2048", |
| "inputs": { |
| "input": { "dtype": "bool", "shape": [64, 32], "data": { "kind": "cycle", "values": [1, 0, 1, 1, 0, 1, 0, 0] } }, |
| "condition": { "dtype": "bool", "shape": [2048], "data": { "kind": "cycle", "values": [1, 0] } } |
| }, |
| "outputs": { "output": { "dtype": "bool", "shape": [1024], "tolerance": 0 } } |
| }, |
| { |
| "name": "int32_axis_last_serial", |
| "attrs": { "axis": -1 }, |
| "inputs": { |
| "input": { |
| "dtype": "int32", |
| "shape": [3, 4], |
| "data": { "kind": "values", "values": [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120] } |
| }, |
| "condition": { "dtype": "bool", "shape": [4], "data": { "kind": "values", "values": [1, 0, 1, 0] } } |
| }, |
| "outputs": { "output": { "dtype": "int32", "shape": [3, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "int8_axis1_parallel_condition_shorter_than_axisDim", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "int8", |
| "shape": [4, 96, 4], |
| "data": { "kind": "cycle", "values": [-128, -1, 0, 1, 127, 42, -77, 5] } |
| }, |
| "condition": { "dtype": "bool", "shape": [32], "data": { "kind": "cycle", "values": [1, 0, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "int8", "shape": [4, 16, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "rank8_axis1", |
| "attrs": { "axis": 1 }, |
| "inputs": { |
| "input": { |
| "dtype": "float32", |
| "shape": [2, 3, 1, 1, 1, 1, 2, 2], |
| "data": { "kind": "linspace", "start": 1.0, "end": 48.0 } |
| }, |
| "condition": { "dtype": "bool", "shape": [3], "data": { "kind": "values", "values": [1, 0, 1] } } |
| }, |
| "outputs": { "output": { "dtype": "float32", "shape": [2, 2, 1, 1, 1, 1, 2, 2], "tolerance": 0 } } |
| } |
| ] |
| } |
|
|
