[TF] Added BroadcastTo layer tests (#15205)
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tests/layer_tests/tensorflow_tests/test_tf_BroadcastTo.py
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tests/layer_tests/tensorflow_tests/test_tf_BroadcastTo.py
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# Copyright (C) 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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from common.tf_layer_test_class import CommonTFLayerTest
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# Testing BroadcastTo operation
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# Documentation: https://www.tensorflow.org/api_docs/python/tf/raw_ops/BroadcastTo
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class TestBroadcastTo(CommonTFLayerTest):
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# input_shape - shape a tensor for a broadcast
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# broadcast_shape - shape of output
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# ir_version - common parameter
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# use_new_frontend - common parameter
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def create_broadcastto_placeholder_const_net(self, input_shape, broadcast_shape, ir_version, use_new_frontend):
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"""
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Tensorflow net IR net
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Placeholder->BroadcastTo => Placeholder->Broadcast
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"""
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import tensorflow as tf
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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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tf_input = tf.compat.v1.placeholder(tf.int32, input_shape, 'Input')
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tf.raw_ops.BroadcastTo(input = tf_input, shape = broadcast_shape)
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tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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ref_net = None
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return tf_net, ref_net
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test_data = [
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dict(input_shape=[3], broadcast_shape=[2, 3]),
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dict(input_shape=[3, 4, 5], broadcast_shape = [4, 3, 3, 4, 5]),
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dict(input_shape=[1, 2, 3, 5], broadcast_shape = [4, 1, 2, 3, 5])
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]
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@pytest.mark.parametrize("params", test_data)
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@pytest.mark.precommit_tf_fe
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@pytest.mark.nightly
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def test_broadcastto_placeholder_const(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_broadcastto_placeholder_const_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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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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