Andrey Kashchikhin
eea49f3c9e
* rm full cloning of the OV repo in win and mac workflows * skip tests on mac * increase timeout for win C++ tests; skip more mac tests * rm triggers
48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import platform
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import pytest
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import numpy as np
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from pytorch_layer_test_class import PytorchLayerTest
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class TestLoopWithAlias(PytorchLayerTest):
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def _prepare_input(self):
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return (np.random.randn(*self.shape).astype(np.float32),)
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def create_model(self, n):
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import torch
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class loop_alias_model(torch.nn.Module):
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def __init__(self, n):
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super(loop_alias_model, self).__init__()
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self.n = n
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def forward(self, x):
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N = x.shape[1]
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res = torch.zeros(1, self.n, dtype=torch.long)
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d = torch.ones(1, N) * 1e10
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f = torch.zeros(1, dtype=torch.long)
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for i in range(self.n):
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res[:, i] = f
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_d = torch.sum((x - x[0, f, :]) ** 2, -1)
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m = _d < d
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d[m] = _d[m]
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f = torch.max(d, -1)[1]
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return res
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return loop_alias_model(n), None, ["prim::Loop", "aten::copy_"]
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@pytest.mark.parametrize("s,n", [([1, 1024, 3], 512), ([1, 512, 3], 128)])
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.xfail(condition=platform.system() == 'Darwin' and platform.machine() == 'arm64',
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reason='Ticket - 122715')
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def test_loop_alias(self, s, n, ie_device, precision, ir_version):
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self.shape = s
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self._test(*self.create_model(n), ie_device, precision,
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ir_version, use_convert_model=True)
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