72 lines
2.4 KiB
Python
72 lines
2.4 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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from pytorch_layer_test_class import PytorchLayerTest
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class TestUnflatten(PytorchLayerTest):
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def _prepare_input(self, dtype):
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return (np.random.uniform(0, 50, (6, 3, 4)).astype(dtype),)
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def create_model(self, dim, shape):
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import torch
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class aten_unflatten(torch.nn.Module):
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def __init__(self, dim, shape):
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super(aten_unflatten, self).__init__()
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self.dim = dim
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self.shape = shape
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def forward(self, x):
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return x.unflatten(self.dim, self.shape)
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ref_net = None
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return aten_unflatten(dim, shape), ref_net, "aten::unflatten"
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@pytest.mark.parametrize(("dim", "shape"), [(0, [2, 1, 3]), (1, [1, 3]), (2, (2, -1)), (-1, (2, 2)), (-2, (-1, 1))])
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@pytest.mark.parametrize("dtype", ["float32", "int32"])
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_torch_export
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def test_unflatten(self, dim, shape, dtype, ie_device, precision, ir_version):
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self._test(*self.create_model(dim, shape), ie_device, precision, ir_version, kwargs_to_prepare_input={"dtype": dtype})
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class TestUnflattenListSizes(PytorchLayerTest):
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def _prepare_input(self, dtype):
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return (np.random.uniform(0, 50, (6, 2, 4)).astype(dtype),)
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def create_model(self, dim):
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import torch
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class aten_unflatten(torch.nn.Module):
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def __init__(self, dim):
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super(aten_unflatten, self).__init__()
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self.dim = dim
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def forward(self, x):
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dim1, dim2, dim3 = x.shape
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if self.dim == 0:
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sizes = [dim1, -1]
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elif self.dim == 1:
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sizes = [dim2 // 2, -1]
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else:
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sizes = [2, dim3 // 2, -1]
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return x.unflatten(self.dim, sizes)
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ref_net = None
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return aten_unflatten(dim), ref_net, "aten::unflatten"
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@pytest.mark.parametrize("dim", [0, 1, 2])
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@pytest.mark.parametrize("dtype", ["float32", "int32"])
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_torch_export
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def test_unflatten(self, dim, dtype, ie_device, precision, ir_version):
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self._test(*self.create_model(dim), ie_device, precision, ir_version, kwargs_to_prepare_input={"dtype": dtype})
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