8d0381b0fe
* [PT FE] Implement custom op for types alignment * Fix code style * Fix inplace ops * Fix layer tests * Remove no longer needed change * Fix ovc tests * Fix fe tests
81 lines
2.6 KiB
Python
81 lines
2.6 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 TestRepeat(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, 10).astype(np.float32),)
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def create_model(self, repeats):
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import torch
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class aten_repeat(torch.nn.Module):
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def __init__(self, repeats):
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super(aten_repeat, self).__init__()
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self.repeats = repeats
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def forward(self, x):
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return x.repeat(self.repeats)
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ref_net = None
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return aten_repeat(repeats), ref_net, "aten::repeat"
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@pytest.mark.parametrize("repeats", [(4, 3), (1, 1), (1, 2, 3), (1, 2, 2, 3)])
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_repeat(self, repeats, ie_device, precision, ir_version):
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self._test(*self.create_model(repeats), ie_device, precision, ir_version)
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class TestRepeatList(PytorchLayerTest):
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def _prepare_input(self, repeats_shape):
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import numpy as np
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return (np.random.randn(2, 10).astype(np.float32), np.random.randn(*repeats_shape).astype(np.float32),)
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def create_model(self):
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import torch
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class aten_repeat(torch.nn.Module):
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def forward(self, x, y):
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y_shape = y.shape
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return x.repeat([y_shape[0], y_shape[1]])
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ref_net = None
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return aten_repeat(), ref_net, ["aten::repeat", "prim::ListConstruct"]
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@pytest.mark.parametrize("repeats", [(4, 3), (1, 1), (1, 3, 3), (1, 2, 2, 3)])
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_repeat(self, repeats, 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={"repeats_shape": repeats})
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class TestRepeatFromFlanT5(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(1, 15).astype(np.float32),)
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def create_model(self):
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import torch
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from transformers.modeling_utils import ModuleUtilsMixin
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class aten_repeat(torch.nn.Module):
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def forward(self, x):
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return ModuleUtilsMixin.create_extended_attention_mask_for_decoder(x.size(), x)
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return aten_repeat(), None, "aten::repeat"
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_repeat_t5(self, ie_device, precision, ir_version):
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self._test(*self.create_model(), ie_device, precision, ir_version, trace_model=True, use_convert_model=True)
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