41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
# Copyright (C) 2018-2023 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 TestFlatten(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(2, 3, 4, 5).astype(np.float32),)
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def create_model(self, dim0, dim1):
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import torch
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class aten_flatten(torch.nn.Module):
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def __init__(self, dim0, dim1):
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super(aten_flatten, self).__init__()
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self.dim0 = dim0
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self.dim1 = dim1
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def forward(self, x):
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return torch.flatten(x, self.dim0, self.dim1)
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ref_net = None
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return aten_flatten(dim0, dim1), ref_net, "aten::flatten"
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@pytest.mark.parametrize("dim0,dim1", [[0, 1],
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[0, 2],
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[0, 3],
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[1, 2],
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[1, 3],
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[2, 3]])
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_relu(self, dim0, dim1, ie_device, precision, ir_version):
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self._test(*self.create_model(dim0, dim1),
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ie_device, precision, ir_version)
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