994b227b86
* Remove None at outputs of the model, improve types handling in frontend * Fix py code style * Add torch dependency in pybind tests * Fix tests if fe is disabled and add backward type cpnversion * Move decoder tests to layer tests * Fix codestyle * Add comment * Move tests to separate folder * Update .ci/azure/linux.yml
48 lines
1.4 KiB
Python
48 lines
1.4 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 TestLog(PytorchLayerTest):
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def _prepare_input(self, dtype):
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import numpy as np
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return (np.random.uniform(2, 16, (1, 10)).astype(dtype),)
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def create_model(self, op):
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import torch
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ops = {
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"log": torch.log,
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"log_": torch.log_,
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"log2": torch.log2,
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"log2_": torch.log2_
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}
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op_fn = ops[op]
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class aten_log(torch.nn.Module):
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def __init__(self, op):
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super(aten_log, 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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ref_net = None
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return aten_log(op_fn), ref_net, f"aten::{op}"
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.parametrize(("op", "input_dtype"),
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[["log", "float32"],
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["log", "int32"],
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["log_", "float32"],
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["log2", "float32"],
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["log2", "int32"],
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["log2_", "float32"]])
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def test_log(self, op, input_dtype, ie_device, precision, ir_version):
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self._test(*self.create_model(op), ie_device, precision,
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ir_version, kwargs_to_prepare_input={"dtype": input_dtype}) |