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"op": "ai.onnx.Flatten",
"fixtureArrays": {
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},
"cases": [
{
"name": "int16_copy_boundaries",
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"data": { "kind": "values", "values": [-32768, -1, 0, 32767] }
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{
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"data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29 }
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{
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"shape": [2, 3, 2],
"data": { "kind": "values", "values": [1, 0, 1, 1, 0, 0, 2, 0, 2, 2, 0, 2] }
}
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"outputs": { "output": { "dtype": "uint32", "shape": [6, 2], "tolerance": 0 } }
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{
"name": "backend_axis0",
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"inputs": {
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"shape": [2, 3, 4],
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}
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"outputs": { "output": { "dtype": "float32", "shape": [1, 24], "tolerance": 0.000001 } }
},
{
"name": "backend_axis3",
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"data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29 }
}
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},
{
"name": "negative_axis_minus1",
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"inputs": {
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"shape": [2, 3, 4],
"data": { "kind": "fillFloat32", "sinStep": 0.07, "cosStep": 0.19 }
}
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"outputs": { "output": { "dtype": "float32", "shape": [6, 4], "tolerance": 0.000001 } }
},
{
"name": "f16_axis0",
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"inputs": {
"input": { "dtype": "float16", "shape": [2, 2], "data": { "kind": "values", "values": [1.0, -2.0, 3.0, -4.0] } }
},
"outputs": { "output": { "dtype": "float16", "shape": [1, 4], "tolerance": 0.001 } }
},
{
"name": "scalar_axis0_to_1x1",
"attrs": { "axis": 0 },
"inputs": { "input": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [3.25] } } },
"outputs": { "output": { "dtype": "float32", "shape": [1, 1], "tolerance": 0.000001 } }
},
{
"name": "zero_sized_axis1",
"attrs": { "axis": 1 },
"inputs": { "input": { "dtype": "float32", "shape": [2, 0, 3], "data": { "kind": "values", "values": [] } } },
"outputs": { "output": { "dtype": "float32", "shape": [2, 0], "tolerance": 0.000001 } }
},
{
"name": "zero_sized_negative_axis",
"attrs": { "axis": -1 },
"inputs": { "input": { "dtype": "float16", "shape": [2, 0, 3], "data": { "kind": "values", "values": [] } } },
"outputs": { "output": { "dtype": "float16", "shape": [0, 3], "tolerance": 0.001 } }
},
{
"name": "ort_rank4_default_axis",
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"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_default_axis"
},
"inputs": { "input": { "dtype": "float32", "shape": [2, 3, 4, 5], "data": { "kind": "constant", "value": 1.0 } } },
"outputs": { "output": { "dtype": "float32", "shape": [2, 60], "tolerance": 0.000001 } }
},
{
"name": "ort_rank4_axis0",
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"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_axis0"
},
"attrs": { "axis": 0 },
"inputs": { "input": { "dtype": "float32", "shape": [2, 3, 4, 5], "data": { "kind": "constant", "value": 1.0 } } },
"outputs": { "output": { "dtype": "float32", "shape": [1, 120], "tolerance": 0.000001 } }
},
{
"name": "ort_rank4_axis3",
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"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_axis3"
},
"attrs": { "axis": 3 },
"inputs": { "input": { "dtype": "float32", "shape": [2, 3, 4, 5], "data": { "kind": "constant", "value": 1.0 } } },
"outputs": { "output": { "dtype": "float32", "shape": [24, 5], "tolerance": 0.000001 } }
},
{
"name": "ort_rank4_negative_axis_minus1",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_neg_axis3"
},
"attrs": { "axis": -1 },
"inputs": { "input": { "dtype": "float32", "shape": [2, 3, 4, 5], "data": { "kind": "constant", "value": 1.0 } } },
"outputs": { "output": { "dtype": "float32", "shape": [24, 5], "tolerance": 0.000001 } }
},
{
"name": "ort_rank4_axis4_trailing_unit",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_axis4"
},
"attrs": { "axis": 4 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [1, 2, 4, 2],
"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": [16, 1], "tolerance": 0.000001 } }
},
{
"name": "ort_uint32_bool_like_axis2",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_axis2_bool",
"notes": "Adapts ORT's bool fixture to logical uint32 values because this framework stores bool-like tensors as u32 slots."
},
"attrs": { "axis": 2 },
"inputs": {
"input": {
"dtype": "uint32",
"shape": [2, 2, 2, 3],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_uint32_bool_like_axis2_input_input" } }
}
},
"outputs": { "output": { "dtype": "uint32", "shape": [4, 6], "tolerance": 0 } }
},
{
"name": "ort_bool_axis2",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_axis2_bool",
"notes": "Direct bool version of ORT's axis=2 flatten fixture."
},
"attrs": { "axis": 2 },
"inputs": {
"input": {
"dtype": "bool",
"shape": [2, 2, 2, 3],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_uint32_bool_like_axis2_input_input" } }
}
},
"outputs": {
"output": {
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"shape": [4, 6],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_uint32_bool_like_axis2_input_input" } },
"tolerance": 0
}
}
},
{
"name": "ort_default_axis_int32_dtype_path",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_default_axis",
"notes": "Same default-axis reshape as ORT's float fixture, using supported int32 data storage."
},
"inputs": { "input": { "dtype": "int32", "shape": [2, 3, 4, 5], "data": { "kind": "constant", "value": 1 } } },
"outputs": { "output": { "dtype": "int32", "shape": [2, 60], "tolerance": 0 } }
},
{
"name": "ort_model_projection_rank1_axis0_for_broadcast",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpModelTest.Flatten_broadcast",
"notes": "Node-level projection of the serialized-model regression: Flatten axis=0 turns a rank-1 vector into a [1,N] row tensor used by a following broadcast Mul."
},
"attrs": { "axis": 0 },
"inputs": {
"input": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [0.0, 1.0, 2.0, 3.0] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 4], "tolerance": 0 } }
},
{
"name": "onnx_backend_flatten_axis0",
"attrs": { "axis": 0 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 120] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_axis0" }
},
{
"name": "onnx_backend_flatten_axis1",
"attrs": { "axis": 1 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [2, 60] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_axis1" }
},
{
"name": "onnx_backend_flatten_axis2",
"attrs": { "axis": 2 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [6, 20] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_axis2" }
},
{
"name": "onnx_backend_flatten_axis3",
"attrs": { "axis": 3 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [24, 5] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_axis3" }
},
{
"name": "onnx_backend_flatten_default_axis",
"inputs": {
"input": {
"dtype": "float32",
"shape": [5, 4, 3, 2],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [5, 24] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_default_axis" }
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{
"name": "onnx_backend_flatten_negative_axis1",
"attrs": { "axis": -1 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [24, 5] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_negative_axis1" }
},
{
"name": "onnx_backend_flatten_negative_axis2",
"attrs": { "axis": -2 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [6, 20] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_negative_axis2" }
},
{
"name": "onnx_backend_flatten_negative_axis3",
"attrs": { "axis": -3 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [2, 60] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_negative_axis3" }
},
{
"name": "onnx_backend_flatten_negative_axis4",
"attrs": { "axis": -4 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [2, 3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_flatten_input_input" } }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 120] } },
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_flatten_negative_axis4" }
},
{
"name": "ort_int8_axis0_edge_values",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_axis0",
"notes": "Same axis-0 reshape as ORT's float case, using ONNX-valid signed byte edge values."
},
"attrs": { "axis": 0 },
"inputs": {
"input": { "dtype": "int8", "shape": [2, 3], "data": { "kind": "values", "values": [-128, -1, 0, 1, 42, 127] } }
},
"outputs": { "output": { "dtype": "int8", "shape": [1, 6], "tolerance": 0 } }
},
{
"name": "ort_uint8_negative_axis_edge_values",
"provenance": {
"source": "onnxruntime/test/providers/cpu/nn/flatten_op_test.cc",
"test": "FlattenOpTest.Flatten_neg_axis3",
"notes": "Same negative-axis reshape behavior as ORT's rank-4 case, using ONNX-valid unsigned byte edge values."
},
"attrs": { "axis": -1 },
"inputs": {
"input": {
"dtype": "uint8",
"shape": [1, 2, 2, 2],
"data": { "kind": "values", "values": [0, 1, 127, 128, 200, 250, 254, 255] }
}
},
"outputs": { "output": { "dtype": "uint8", "shape": [4, 2], "tolerance": 0 } }
},
{
"name": "scalar_copy_dispatch_clamp",
"provenance": {
"notes": "Odd numel forces the scalar copy variant; WORKGROUP_SIZE=4 makes ceil(numel/WG)=65536 exceed the 65535 workgroups-per-dimension limit, pinning the min(...,65535) dispatch clamp + grid-stride loop (some threads copy two elements)."
},
"attrs": { "axis": 1 },
"tunables": { "WORKGROUP_SIZE": 4 },
"inputs": {
"input": {
"dtype": "float32",
"shape": [262141],
"data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.31 }
}
},
"outputs": { "output": { "dtype": "float32", "shape": [262141, 1], "tolerance": 0 } }
},
{
"name": "int8_numel2_scalar_copy_path",
"attrs": { "axis": 1 },
"inputs": { "input": { "dtype": "int8", "shape": [2, 1], "data": { "kind": "values", "values": [-128, 127] } } },
"outputs": { "output": { "dtype": "int8", "shape": [2, 1], "tolerance": 0 } }
},
{
"name": "uint8_numel3_scalar_copy_path",
"attrs": { "axis": 1 },
"inputs": {
"input": { "dtype": "uint8", "shape": [3, 1], "data": { "kind": "values", "values": [0, 128, 255] } }
},
"outputs": { "output": { "dtype": "uint8", "shape": [3, 1], "tolerance": 0 } }
},
{
"name": "f16_numel6_scalar_copy_path",
"attrs": { "axis": 1 },
"inputs": {
"input": {
"dtype": "float16",
"shape": [2, 3],
"data": { "kind": "values", "values": [-65504.0, 0.0, 1.0, -1.0, 65504.0, 0.5] }
}
},
"outputs": { "output": { "dtype": "float16", "shape": [2, 3], "tolerance": 0 } }
}
]
}
|