Roman Kazantsev
af6ed211d6
* [TF FE] Support TF2 Object detection models For support of OOB conversion of OD models (Faster RCNN, SSD models) several fixes were done for Select, BroadcastArgs, Slice, and Concat operations. Implement tests for each case Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com> * Switch off Transpose Sinking that breaks some model conversion * Apply code-review feedback: copyright and extra commented out code * Mention that for concat this is workaround Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
38 lines
1.6 KiB
Python
38 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 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 TestSlice(CommonTFLayerTest):
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def create_slice_net(self, input_shape, input_type, begin_value, size_value):
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tf.compat.v1.reset_default_graph()
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with tf.compat.v1.Session() as sess:
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input_x = tf.compat.v1.placeholder(input_type, input_shape, 'input_x')
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begin = tf.constant(begin_value, tf.int32)
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size = tf.constant(size_value, tf.int32)
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tf.raw_ops.Slice(input=input_x, begin=begin, size=size)
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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_basic = [
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dict(input_shape=[6], input_type=tf.float32, begin_value=[2], size_value=[2]),
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dict(input_shape=[2, 5, 3], input_type=tf.int32, begin_value=[0, 1, 0], size_value=[-1, 1, -1]),
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dict(input_shape=[10, 5, 1, 5], input_type=tf.float32, begin_value=[5, 1, 0, 3], size_value=[2, 4, -1, -1]),
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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_slice_basic(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
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use_old_api):
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self._test(*self.create_slice_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)
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