Andrey Kashchikhin
62f5bd6570
* add arm as a matrix for build job * uncomment * comment * try inside pipeline * check location * another dirs * try to privide correct action path * use corrected action * use newer commit * use newer commit * use newer commit * use newer action commit * add setting * rm from pipeline, adapt action iteslf * add missing deps * enable samples and debian jobs * correct yml * correct image name * correct syntax, use self-hosted option * enable onnx runtime and c++, use newer action * enable Python and CPU Func tests * add missing deps for arm64 * increase timeout for python tests * disable some tests, add more time * skip failing tests * skip speech sample test on arm * dummy chang * skip mxnet mo on arm, run all tests * rm quotes * separate linux x86 and arm64 workflows * rm unused matrix refs, add timeouts * add skips for c++ tests and some Python tests * correct cache keys, extend timeout * skip more python tests * add more skips: for python and CPU func * extend cpu func list with skips * disable cpu func tests and python api 2.0 tests * rm disable job * styling, rm pr trigger, rm always(), rm unnecessary changes * revert * use ifs instead of comments, provide better wording for skips
84 lines
2.7 KiB
Python
84 lines
2.7 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import platform
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import pytest
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from pytorch_layer_test_class import PytorchLayerTest
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class TestArgMinArgMax(PytorchLayerTest):
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def _prepare_input(self, dtype="float32"):
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import numpy as np
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a = np.random.randn(1, 3, 10, 10).astype(dtype)
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return (a.repeat(2).reshape(1, 3, 20, 10),)
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def create_model(self, op_type, axes, keep_dims):
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import torch
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op_types = {
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'max': torch.argmax,
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'min': torch.argmin
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}
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op = op_types[op_type]
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class aten_argmin_argmax(torch.nn.Module):
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def __init__(self, op):
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super(aten_argmin_argmax, self).__init__()
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self.op = op
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def forward(self, x):
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return self.op(x)
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class aten_argmin_argmax_3arg(torch.nn.Module):
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def __init__(self, op, axes, keep_dims):
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super().__init__()
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self.op = op
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self.axes = axes
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self.keep_dims = keep_dims
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def forward(self, x):
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return self.op(x, self.axes, self.keep_dims)
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ref_net = None
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if axes is None and keep_dims is None:
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model_cls = aten_argmin_argmax(op)
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else:
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model_cls = aten_argmin_argmax_3arg(op, axes, keep_dims)
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return model_cls, ref_net, f"aten::arg{op_type}"
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@pytest.mark.parametrize("axes,keep_dims", [
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(None, None),
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(None, False),
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(None, True),
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(0, False),
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(0, True),
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(1, False),
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(1, True),
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(2, False),
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(2, True),
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(3, False),
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(3, True),
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(-3, False),
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(-3, True),
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(-2, False),
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(-2, True),
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(-1, False),
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(-1, True)])
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@pytest.mark.parametrize("op_type", ['max', 'min'])
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@pytest.mark.parametrize("dtype", ["float32", "int32", "int64"])
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.xfail(condition=platform.system() in ('Darwin', 'Linux') and platform.machine() in ('arm', 'armv7l',
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'aarch64',
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'arm64', 'ARM64'),
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reason='Ticket - 122715')
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def test_argmin_argmax(self, axes, keep_dims, op_type, dtype, ie_device, precision, ir_version):
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self._test(*self.create_model(op_type, axes, keep_dims),
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ie_device, precision, ir_version, trace_model=True,
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kwargs_to_prepare_input={"dtype": dtype})
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