53820c0cf2
* [TF FE]Support Inv operation for TensorFlow models * added test tests/layer_tests/tensorflow_tests/test_tf_Inv.py and src/frontends/tensorflow_common/src/op/inv.cpp * Update tests/layer_tests/tensorflow_tests/test_tf_Inv.py * Update tests/layer_tests/tensorflow_tests/test_tf_Inv.py * Update tests/layer_tests/tensorflow_tests/test_tf_Inv.py --------- Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>
44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
# Copyright (C) 2018-2023 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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import tensorflow as tf
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestInv(CommonTFLayerTest):
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def _prepare_input(self, inputs_info):
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assert 'x' in inputs_info
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x_shape = inputs_info['x']
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inputs_data = {}
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inputs_data['x'] = np.random.choice([-5, -4, -3, -2, -1, 1, 2, 3, 4, 5], x_shape).astype(np.float32)
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return inputs_data
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def create_inv_net(self, input_shape, input_type):
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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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x = tf.compat.v1.placeholder(input_type, input_shape, 'x')
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tf.raw_ops.Inv(x=x)
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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=[], input_type=np.float32),
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dict(input_shape=[10, 20], input_type=np.float32),
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dict(input_shape=[2, 3, 4], input_type=np.float32),
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]
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@pytest.mark.parametrize("params", test_data_basic)
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@pytest.mark.precommit_tf_fe
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@pytest.mark.nightly
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def test_inv_basic(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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self._test(*self.create_inv_net(**params),
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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) |