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GregoryComerGregoryComer
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[Backend Tester] Add slice and reshape tests (#12851)
Add tests for a view-type ops, cat, and slice.
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‎backends/test/suite/operators/test_cat.py

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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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# pyre-unsafe
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import torch
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from executorch.backends.test.suite.flow import TestFlow
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from executorch.backends.test.suite.operators import (
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dtype_test,
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operator_test,
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OperatorTest,
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)
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class CatModel(torch.nn.Module):
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def __init__(self, dim: int = 0):
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super().__init__()
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self.dim = dim
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def forward(self, x1, x2, x3):
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return torch.cat([x1, x2, x3], dim=self.dim)
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@operator_test
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class Cat(OperatorTest):
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@dtype_test
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def test_cat_dtype(self, flow: TestFlow, dtype) -> None:
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self._test_op(
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CatModel(),
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(
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torch.rand(8, 32).to(dtype),
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torch.rand(12, 32).to(dtype),
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torch.rand(16, 32).to(dtype),
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),
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flow,
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)
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def test_cat_dimensions(self, flow: TestFlow) -> None:
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self._test_op(
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CatModel(dim=0),
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(
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torch.randn(8, 32),
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torch.randn(12, 32),
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torch.randn(16, 32),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=1),
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(
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torch.randn(16, 8),
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torch.randn(16, 12),
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torch.randn(16, 16),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=2),
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(
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torch.randn(4, 8, 4),
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torch.randn(4, 8, 8),
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torch.randn(4, 8, 12),
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),
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flow,
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)
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def test_cat_negative_dim(self, flow: TestFlow) -> None:
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self._test_op(
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CatModel(dim=-1),
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(
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torch.randn(16, 8),
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torch.randn(16, 12),
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torch.randn(16, 16),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=-2),
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(
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torch.randn(8, 32),
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torch.randn(12, 32),
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torch.randn(16, 32),
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),
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flow,
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)
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def test_cat_different_shapes(self, flow: TestFlow) -> None:
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self._test_op(
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CatModel(),
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(
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torch.randn(128),
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torch.randn(256),
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torch.randn(384),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=0),
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(
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torch.randn(4, 8, 16),
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torch.randn(8, 8, 16),
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torch.randn(12, 8, 16),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=1),
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(
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torch.randn(8, 4, 16),
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torch.randn(8, 8, 16),
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torch.randn(8, 12, 16),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=2),
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(
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torch.randn(8, 12, 4),
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torch.randn(8, 12, 8),
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torch.randn(8, 12, 12),
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),
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flow,
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)
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def test_cat_broadcast(self, flow: TestFlow) -> None:
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self._test_op(
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CatModel(dim=0),
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(
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torch.randn(2, 16, 32),
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torch.randn(4, 16, 32),
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torch.randn(6, 16, 32),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=1),
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(
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torch.randn(8, 8, 16),
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torch.randn(8, 16, 16),
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torch.randn(8, 24, 16),
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),
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flow,
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)
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self._test_op(
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CatModel(dim=2),
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(
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torch.randn(4, 16, 8),
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torch.randn(4, 16, 16),
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torch.randn(4, 16, 24),
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),
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flow,
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)
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def test_cat_same_shapes(self, flow: TestFlow) -> None:
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self._test_op(
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CatModel(),
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(
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torch.randn(8, 32),
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torch.randn(8, 32),
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torch.randn(8, 32),
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),
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flow,
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)

‎backends/test/suite/operators/test_expand.py

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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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# pyre-unsafe
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from typing import List
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import torch
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from executorch.backends.test.suite.flow import TestFlow
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from executorch.backends.test.suite.operators import (
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dtype_test,
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operator_test,
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OperatorTest,
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)
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class ExpandModel(torch.nn.Module):
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def __init__(self, shape: List[int]):
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super().__init__()
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self.shape = shape
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def forward(self, x):
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return x.expand(self.shape)
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@operator_test
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class Expand(OperatorTest):
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@dtype_test
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def test_expand_dtype(self, flow: TestFlow, dtype) -> None:
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self._test_op(
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ExpandModel(shape=[8, 32]),
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(torch.rand(1, 32).to(dtype),),
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flow,
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)
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def test_expand_dimensions(self, flow: TestFlow) -> None:
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self._test_op(
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ExpandModel(shape=[8, 32]),
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(torch.randn(1, 32),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[16, 20]),
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(torch.randn(1, 1),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[4, 1, 32]),
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(torch.randn(1, 32),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[8, 4, 16]),
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(torch.randn(8, 1, 16),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[6, 16, 8]),
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(torch.randn(6, 16, 1),),
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flow,
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)
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def test_expand_keep_original_size(self, flow: TestFlow) -> None:
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self._test_op(
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ExpandModel(shape=[8, -1]),
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(torch.randn(1, 32),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[-1, 32]),
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(torch.randn(4, 1),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[-1, 16, -1]),
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(torch.randn(4, 1, 8),),
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flow,
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)
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def test_expand_rank_increase(self, flow: TestFlow) -> None:
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# Test expanding 2D tensor to 3D
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self._test_op(
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ExpandModel(shape=[6, 8, 16]),
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(torch.randn(8, 16),),
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flow,
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)
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# Test expanding 2D tensor to 4D
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self._test_op(
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ExpandModel(shape=[3, 4, 8, 16]),
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(torch.randn(8, 16),),
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flow,
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)
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def test_expand_singleton_dimensions(self, flow: TestFlow) -> None:
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self._test_op(
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ExpandModel(shape=[512]),
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(torch.randn(1),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[16, 20]),
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(torch.randn(1, 1),),
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flow,
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)
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self._test_op(
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ExpandModel(shape=[8, 32]),
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(torch.randn(32),),
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flow,
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)

‎backends/test/suite/operators/test_reshape.py

Lines changed: 82 additions & 0 deletions
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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7+
# pyre-unsafe
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from typing import List
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import torch
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from executorch.backends.test.suite.flow import TestFlow
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from executorch.backends.test.suite.operators import (
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dtype_test,
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operator_test,
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OperatorTest,
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)
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class ReshapeModel(torch.nn.Module):
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def __init__(self, shape: List[int]):
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super().__init__()
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self.shape = shape
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def forward(self, x):
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return torch.reshape(x, self.shape)
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@operator_test
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class Reshape(OperatorTest):
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@dtype_test
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def test_reshape_dtype(self, flow: TestFlow, dtype) -> None:
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self._test_op(
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ReshapeModel(shape=[3, 5]),
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(torch.rand(15).to(dtype),),
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flow,
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)
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def test_reshape_dimensions(self, flow: TestFlow) -> None:
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self._test_op(
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ReshapeModel(shape=[3, 5]),
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(torch.randn(15),),
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flow,
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)
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self._test_op(
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ReshapeModel(shape=[20]),
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(torch.randn(4, 5),),
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flow,
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)
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self._test_op(
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ReshapeModel(shape=[2, 2, 5]),
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(torch.randn(4, 5),),
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flow,
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)
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self._test_op(
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ReshapeModel(shape=[6, 4]),
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(torch.randn(3, 2, 4),),
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flow,
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)
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def test_reshape_inferred_dimension(self, flow: TestFlow) -> None:
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self._test_op(
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ReshapeModel(shape=[3, -1]),
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(torch.randn(15),),
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flow,
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)
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self._test_op(
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ReshapeModel(shape=[-1, 5]),
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(torch.randn(15),),
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flow,
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)
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self._test_op(
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ReshapeModel(shape=[2, -1, 3]),
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(torch.randn(24),),
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flow,
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)

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