40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
# Copyright (C) 2018-2024 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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class TestNarrow(PytorchLayerTest):
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def _prepare_input(self):
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return (np.random.randn(*self.input_shape).astype(np.float32),)
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def create_model(self, dim, start, length):
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class aten_narrow(torch.nn.Module):
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def __init__(self, dim, start, length):
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super().__init__()
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self.dim = dim
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self.start = start
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self.length = length
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def forward(self, input_tensor):
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return torch.narrow(input_tensor, dim=self.dim, start=self.start, length=self.length)
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return aten_narrow(dim, start, length), None, "aten::narrow"
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@pytest.mark.parametrize("input_shape", [
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[3, 3], [3, 4, 5]
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])
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@pytest.mark.parametrize("dim", [0, 1, -1])
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@pytest.mark.parametrize("start", [0, 1])
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@pytest.mark.parametrize("length", [1, 2])
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_narrow(self, input_shape, dim, start, length, ie_device, precision, ir_version):
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self.input_shape = input_shape
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self._test(*self.create_model(dim, start, length), ie_device, precision, ir_version)
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