68 lines
2.1 KiB
Python
68 lines
2.1 KiB
Python
# Copyright (C) 2018-2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import pytest
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from pytorch_layer_test_class import PytorchLayerTest
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class TestCopy(PytorchLayerTest):
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def _prepare_input(self):
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import numpy as np
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return (np.random.randn(1, 3, 224, 224).astype(np.float32),)
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def create_model(self, value):
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import torch
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class aten_copy(torch.nn.Module):
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def __init__(self, value):
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super(aten_copy, self).__init__()
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self.value = torch.tensor(value)
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def forward(self, x):
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return x.copy_(self.value)
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ref_net = None
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return aten_copy(value), ref_net, "aten::copy_"
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_fx_backend
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@pytest.mark.parametrize("value", [1, [2.5], range(224)])
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def test_copy_(self, value, ie_device, precision, ir_version):
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self._test(*self.create_model(value), ie_device, precision, ir_version)
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class TestAliasCopy(PytorchLayerTest):
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def _prepare_input(self, out):
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import numpy as np
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if not out:
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return (np.random.randn(1, 3, 224, 224).astype(np.float32),)
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return (np.random.randn(1, 3, 224, 224).astype(np.float32), np.zeros((1, 3, 224, 224), dtype=np.float32))
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def create_model(self, out):
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import torch
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class aten_copy(torch.nn.Module):
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def __init__(self, out):
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super(aten_copy, self).__init__()
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if out:
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self.forward = self.forward_out
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def forward(self, x):
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return torch.alias_copy(x)
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def forward_out(self, x, y):
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return torch.alias_copy(x, out=y), y
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ref_net = None
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return aten_copy(out), ref_net, "aten::alias_copy"
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.parametrize("out", [True, False])
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def test_copy_(self, out, ie_device, precision, ir_version):
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self._test(*self.create_model(out), ie_device, precision, ir_version, kwargs_to_prepare_input={"out": out})
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