38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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import torch
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from pytorch_layer_test_class import PytorchLayerTest
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@pytest.mark.parametrize('input_dim', list(range(-3, 4)))
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@pytest.mark.parametrize('input_index', list(range(-3, 4)))
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class TestSelect(PytorchLayerTest):
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def _prepare_input(self):
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return (np.random.randn(4, 4, 5, 5).astype(np.float32),)
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def create_model(self, input_dim, input_index):
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class aten_select(torch.nn.Module):
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def __init__(self, input_dim, input_index) -> None:
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super().__init__()
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self.dim = input_dim
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self.index = input_index
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def forward(self, input_tensor):
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return torch.select(input_tensor, int(self.dim), int(self.index))
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ref_net = None
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return aten_select(input_dim, input_index), ref_net, "aten::select"
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_select(self, ie_device, precision, ir_version, input_dim, input_index):
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self._test(*self.create_model(input_dim, input_index),
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ie_device, precision, ir_version)
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