38 lines
1.1 KiB
Python
38 lines
1.1 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 TestNumel(PytorchLayerTest):
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def _prepare_input(self, input_shape=(2)):
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import numpy as np
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return (np.random.randn(*input_shape).astype(np.float32),)
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def create_model(self):
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import torch
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class aten_numel(torch.nn.Module):
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def forward(self, x):
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return torch.numel(x)
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ref_net = None
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return aten_numel(), ref_net, 'aten::numel'
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@pytest.mark.parametrize("kwargs_to_prepare_input", [
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{'input_shape': (1,)},
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{'input_shape': (2,)},
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{'input_shape': (2, 3)},
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{'input_shape': (3, 4, 5)},
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{'input_shape': (1, 2, 3, 4)},
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{'input_shape': (1, 2, 3, 4, 5)}
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])
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_numel(self, kwargs_to_prepare_input, ie_device, precision, ir_version):
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self._test(*self.create_model(), ie_device, precision, ir_version,
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kwargs_to_prepare_input=kwargs_to_prepare_input)
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