Andrey KashchikhinandIlya Lavrenov
b67cff7cd5
* add m1 mac pipelines as a matrix parameter * Update mac.yml disable java_api because of macos arm64 - Java is not available on macOS arm64 runners * Update mac.yml added always condition for all tests * Update mac.yml * Update mac.yml * Update mac.yml * Update setup.py temp commit * Update tools/openvino_dev/setup.py * use matrix for var * add mxnet to extras only for x86_64 * skip failing tests * use xfail for Python tests; add missing filter for transformations tests * skip CPU func tests on x86_64 mac; skip some tests from CPU func tests on arm mac * Update mac.yml * skip tests on mac arm * skip tests on darwin; apply review * add more skips for python and c++ tests * skip tf tests * skip more tf tests; skip more Python UT stages * rm alwayses, rm triggers, add nightly trigger --------- Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
76 lines
3.2 KiB
Python
76 lines
3.2 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 numpy as np
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import pytest
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import tensorflow as tf
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestMaxPoolWithArgmax(CommonTFLayerTest):
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def _prepare_input(self, inputs_info):
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assert 'input' in inputs_info
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input_shape = inputs_info['input']
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inputs_data = {}
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inputs_data['input'] = np.random.randint(-5, 5, input_shape).astype(self.input_type)
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return inputs_data
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def create_max_pool_with_argmax_net(self, input_shape, ksize, strides, input_type, padding, targmax,
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include_batch_in_index, with_second_output):
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self.input_type = input_type
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tf.compat.v1.reset_default_graph()
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# Create the graph and model
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with tf.compat.v1.Session() as sess:
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input = tf.compat.v1.placeholder(input_type, input_shape, 'input')
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max_pool_with_argmax = tf.raw_ops.MaxPoolWithArgmax(input=input, ksize=ksize, strides=strides,
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padding=padding, Targmax=targmax,
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include_batch_in_index=include_batch_in_index
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)
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tf.identity(max_pool_with_argmax[0], name='max_pool')
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if with_second_output:
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tf.identity(max_pool_with_argmax[1], name='output_indices')
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tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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return tf_net, None
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test_data_basic = [
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dict(input_shape=[1, 25, 24, 3],
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ksize=[1, 1, 1, 1], strides=[1, 1, 1, 1]),
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dict(input_shape=[1, 10, 20, 3],
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ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1]),
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]
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@pytest.mark.parametrize("params", test_data_basic)
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@pytest.mark.parametrize("input_type", [
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np.float32, np.int32
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])
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@pytest.mark.parametrize("padding", [
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'VALID', 'SAME'
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])
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@pytest.mark.parametrize("targmax", [
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tf.int32, tf.int64
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])
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@pytest.mark.parametrize("include_batch_in_index", [
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True, False
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])
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@pytest.mark.parametrize("with_second_output", [
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True, False
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])
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@pytest.mark.precommit_tf_fe
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@pytest.mark.nightly
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@pytest.mark.xfail(condition=platform.system() == 'Darwin' and platform.machine() == 'arm64',
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reason='Ticket - 122716')
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def test_max_pool_with_argmax_basic(self, params, input_type, padding, targmax,
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include_batch_in_index, with_second_output,
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ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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self._test(
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*self.create_max_pool_with_argmax_net(**params, input_type=input_type, padding=padding, targmax=targmax,
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include_batch_in_index=include_batch_in_index,
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with_second_output=with_second_output),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, use_old_api=use_old_api)
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