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[TF FE] Workaround for Broadcast/Concat issue with empty tensors (#18140)

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* Added transformation for Concat
* Added test
* CI fix
* Fixed behavior of the "empty tensor list" test
This commit is contained in:
Georgy Krivoruchko
2023-06-20 13:13:55 +04:00
committed by GitHub
parent 691630b68c
commit fd48b0bbdc
4 changed files with 31 additions and 2 deletions
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2
src/frontends/tensorflow/src/frontend.cpp
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@@ -23,6 +23,7 @@
#include "openvino/util/log.hpp"
#include "so_extension.hpp"
#include "tf_framework_node.hpp"
#include "transformations/common_optimizations/remove_concat_zero_dim_input.hpp"
#include "transformations/common_optimizations/reverse_shape_and_type_infer.hpp"
#include "transformations/transpose_sinking/ts_general.hpp"
#include "translate_session.hpp"
@@ -341,6 +342,7 @@ void FrontEnd::normalize(const std::shared_ptr<ov::Model>& model) const {
manager.register_pass<pass::BlockLSTMReplacer>();
manager.register_pass<pass::GRUBlockCellReplacer>();
manager.register_pass<pass::ConstToResultRemover>();
manager.register_pass<ov::pass::RemoveConcatZeroDimInput>();
manager.register_pass<ov::pass::TransposeSinkingGeneral>();
manager.register_pass<ov::pass::ReverseShapeAndTypeInfer>();
manager.run_passes(model);

10
src/frontends/tensorflow/tests/convert_saved_model.cpp
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@@ -114,3 +114,13 @@ TEST_F(TransformationTestsF, SavedModelMultipleTensorNames) {
model_ref = make_shared<Model>(OutputVector{result}, ParameterVector{x});
}
}
TEST_F(TransformationTestsF, SavedModelBroadcastIssue) {
{ model = convert_model("saved_model_broadcast_issue"); }
{
// create a reference graph
auto x = make_shared<Constant>(element::i64, Shape{2, 2}, vector<int64_t>{1, 2, -1, -1});
model_ref = make_shared<Model>(OutputVector{x}, ParameterVector{});
}
}

3
src/frontends/tensorflow/tests/convert_tricky_models.cpp
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@@ -383,8 +383,7 @@ TEST_F(TransformationTestsF, ModelWithEmptyTensorListAndPushBack) {
auto x_flatten = make_shared<Reshape>(x, minus_one_const, false);
auto zero_const = make_shared<Constant>(i32, Shape{1}, 0);
auto x_unsqueeze_flatten = make_shared<Unsqueeze>(x_flatten, zero_const);
auto empty_const = make_shared<Constant>(f32, Shape{0, 30}, vector<float>{});
auto list_push_back = make_shared<Concat>(OutputVector{empty_const, x_unsqueeze_flatten}, 0);
auto list_push_back = make_shared<Concat>(OutputVector{x_unsqueeze_flatten}, 0);
auto list_push_back_shape = make_shared<ShapeOf>(list_push_back, element::i32);
auto start = make_shared<Constant>(i32, Shape{1}, 0);
auto stop = make_shared<Constant>(i32, Shape{1}, 1);

18
src/frontends/tensorflow/tests/test_models/gen_scripts/generate_saved_model_broadcast_issue.py Normal file
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@@ -0,0 +1,18 @@
# Copyright (C) 2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import os
import sys
import tensorflow as tf
import numpy as np
# Create the graph and model
tf.compat.v1.reset_default_graph()
with tf.compat.v1.Session() as sess:
tf_x = tf.constant(np.array([[1, 2]], dtype=np.dtype('i8')))
tf_cast = tf.raw_ops.Cast(x=-1, DstT=tf.int64)
tf_fill = tf.fill([0, 2], tf_cast, name="FillOperation")
tf_fill2 = tf.fill([1, 2], tf_cast, name="FillOperation2")
tf_output = tf.raw_ops.ConcatV2(values=[tf_x, tf_fill, tf_fill2], axis=0, name="ConcatOperation")
tf.compat.v1.saved_model.simple_save(sess, os.path.join(sys.argv[1], "saved_model_broadcast_issue"), inputs={'x':tf_x}, outputs={'output':tf_output})