Merge remote-tracking branch 'upstream/master' into itikhono/transfor…

…mations/ngraph_to_ov_refactoring
itikhono · Sep 25, 2023 · 9aabe1e · 9aabe1e
2 parents 1e96772 + 7d1b7b6
commit 9aabe1e
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Showing 125 changed files with 874 additions and 993 deletions.
diff --git a/src/core/dev_api/shape_util.hpp → ...core/dev_api/openvino/core/shape_util.hpp b/src/core/dev_api/shape_util.hpp → ...core/dev_api/openvino/core/shape_util.hpp
diff --git a/src/core/include/ngraph/op/util/recurrent_sequence.hpp b/src/core/include/ngraph/op/util/recurrent_sequence.hpp
@@ -18,20 +18,12 @@
 
 #include "ngraph/deprecated.hpp"
 #include "ngraph/node.hpp"
+#include "openvino/op/util/recurrent_sequence.hpp"
 
 namespace ngraph {
 namespace op {
 namespace util {
-///
-/// \brief      Validates static rank and dimension for provided input parameters.
-///             Additionally input_size dimension is checked for X and W inputs.
-///             Applies to LSTM, GRU and RNN Sequences.
-///
-///
-/// \param[in]  input        Vector with RNNSequence-like op inputs in following order:
-///                          X, initial_hidden_state, sequence_lengths, W, R and B.
-///
-NGRAPH_API_DEPRECATED void validate_seq_input_rank_dimension(const std::vector<ngraph::PartialShape>& input);
+using ov::op::util::validate_seq_input_rank_dimension;
 }  // namespace util
 }  // namespace op
 }  // namespace ngraph
diff --git a/src/core/include/openvino/op/convert_like.hpp b/src/core/include/openvino/op/convert_like.hpp
@@ -23,7 +23,6 @@ class OPENVINO_API ConvertLike : public Op {
     ConvertLike(const Output<Node>& data, const Output<Node>& like);
 
     void validate_and_infer_types() override;
-    bool visit_attributes(AttributeVisitor& visitor) override;
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 

diff --git a/src/core/include/openvino/op/dft.hpp b/src/core/include/openvino/op/dft.hpp
@@ -45,8 +45,6 @@ class OPENVINO_API DFT : public util::FFTBase {
     /// \param signal_size Signal sizes for 'axes'
     DFT(const Output<Node>& data, const Output<Node>& axes, const Output<Node>& signal_size);
 
-    bool visit_attributes(AttributeVisitor& visitor) override;
-
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 };
 }  // namespace v7

diff --git a/src/core/include/openvino/op/gather.hpp b/src/core/include/openvino/op/gather.hpp
@@ -21,7 +21,6 @@ class OPENVINO_API Gather : public op::util::GatherBase {
     /// \param axis The tensor is a dimension index to gather data from
     Gather(const Output<Node>& params, const Output<Node>& indices, const Output<Node>& axis);
 
-    bool visit_attributes(AttributeVisitor& visitor) override;
     int64_t get_axis() const override;
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;

diff --git a/src/core/include/openvino/op/gather_tree.hpp b/src/core/include/openvino/op/gather_tree.hpp
@@ -29,7 +29,6 @@ class OPENVINO_API GatherTree : public Op {
                const Output<Node>& max_seq_len,
                const Output<Node>& end_token);
 
-    bool visit_attributes(AttributeVisitor& visitor) override;
     void validate_and_infer_types() override;
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;

diff --git a/src/core/include/openvino/op/hard_sigmoid.hpp b/src/core/include/openvino/op/hard_sigmoid.hpp
@@ -27,7 +27,6 @@ class OPENVINO_API HardSigmoid : public Op {
     ///
     HardSigmoid(const Output<Node>& data, const Output<Node>& alpha, const Output<Node>& beta);
 
-    bool visit_attributes(AttributeVisitor& visitor) override;
     void validate_and_infer_types() override;
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 };

diff --git a/src/core/include/openvino/op/idft.hpp b/src/core/include/openvino/op/idft.hpp
@@ -33,8 +33,6 @@ class OPENVINO_API IDFT : public util::FFTBase {
     /// \param signal_size Signal sizes for 'axes'
     IDFT(const Output<Node>& data, const Output<Node>& axes, const Output<Node>& signal_size);
 
-    bool visit_attributes(AttributeVisitor& visitor) override;
-
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 };
 }  // namespace v7

diff --git a/src/core/include/openvino/op/irdft.hpp b/src/core/include/openvino/op/irdft.hpp
@@ -30,7 +30,6 @@ class OPENVINO_API IRDFT : public util::FFTBase {
     IRDFT(const Output<Node>& data, const Output<Node>& axes, const Output<Node>& signal_size);
 
     void validate_and_infer_types() override;
-    bool visit_attributes(AttributeVisitor& visitor) override;
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 };

diff --git a/src/core/include/openvino/op/rdft.hpp b/src/core/include/openvino/op/rdft.hpp
@@ -30,7 +30,6 @@ class OPENVINO_API RDFT : public util::FFTBase {
     RDFT(const Output<Node>& data, const Output<Node>& axes, const Output<Node>& signal_size);
 
     void validate_and_infer_types() override;
-    bool visit_attributes(AttributeVisitor& visitor) override;
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 };

diff --git a/src/core/include/openvino/op/selu.hpp b/src/core/include/openvino/op/selu.hpp
@@ -25,8 +25,6 @@ class OPENVINO_API Selu : public Op {
 
     void validate_and_infer_types() override;
 
-    bool visit_attributes(AttributeVisitor& visitor) override;
-
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 };
 }  // namespace v0

diff --git a/src/core/include/openvino/op/util/recurrent_sequence.hpp b/src/core/include/openvino/op/util/recurrent_sequence.hpp
@@ -0,0 +1,26 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <vector>
+
+#include "openvino/core/partial_shape.hpp"
+
+namespace ov {
+namespace op {
+namespace util {
+///
+/// \brief      Validates static rank and dimension for provided input parameters.
+///             Additionally input_size dimension is checked for X and W inputs.
+///             Applies to LSTM, GRU and RNN Sequences.
+///
+///
+/// \param[in]  input        Vector with RNNSequence-like op inputs in following order:
+///                          X, initial_hidden_state, sequence_lengths, W, R and B.
+///
+OPENVINO_API void validate_seq_input_rank_dimension(const std::vector<ov::PartialShape>& input);
+}  // namespace util
+}  // namespace op
+}  // namespace ov
diff --git a/src/core/reference/include/openvino/reference/reduce_l1.hpp b/src/core/reference/include/openvino/reference/reduce_l1.hpp
@@ -7,10 +7,10 @@
 #include <cmath>
 #include <numeric>
 
+#include "openvino/core/shape_util.hpp"
 #include "openvino/reference/abs.hpp"
 #include "openvino/reference/sum.hpp"
 #include "openvino/reference/utils/type_util.hpp"
-#include "shape_util.hpp"
 
 namespace ov {
 namespace reference {

diff --git a/src/core/reference/include/openvino/reference/reduce_l2.hpp b/src/core/reference/include/openvino/reference/reduce_l2.hpp
@@ -8,8 +8,8 @@
 #include <cmath>
 #include <numeric>
 
+#include "openvino/core/shape_util.hpp"
 #include "openvino/reference/utils/coordinate_transform.hpp"
-#include "shape_util.hpp"
 
 namespace ov {
 namespace reference {

diff --git a/src/core/reference/src/op/function.cpp b/src/core/reference/src/op/function.cpp
@@ -10,8 +10,8 @@
 #include "ngraph/runtime/host_tensor.hpp"
 #include "ngraph/runtime/tensor.hpp"
 #include "openvino/core/deprecated.hpp"
+#include "openvino/core/shape_util.hpp"
 #include "openvino/reference/concat.hpp"
-#include "shape_util.hpp"
 
 namespace ov {
 namespace reference {

diff --git a/src/core/src/bound_evaluate.cpp b/src/core/src/bound_evaluate.cpp
@@ -7,9 +7,9 @@
 #include "ngraph/validation_util.hpp"
 #include "openvino/core/dimension_tracker.hpp"
 #include "openvino/core/rt_info.hpp"
+#include "openvino/core/shape_util.hpp"
 #include "openvino/op/util/symbolic_info.hpp"
 #include "openvino/opsets/opset10.hpp"
-#include "shape_util.hpp"
 #include "tensor_conversion_util.hpp"
 #include "transformations/rt_info/decompression.hpp"
 #include "transformations/rt_info/is_shape_subgraph.hpp"

diff --git a/src/core/src/node.cpp b/src/core/src/node.cpp
@@ -15,9 +15,9 @@
 #include "ngraph/graph_util.hpp"
 #include "openvino/core/descriptor/input.hpp"
 #include "openvino/core/rt_info.hpp"
+#include "openvino/core/shape_util.hpp"
 #include "openvino/pass/constant_folding.hpp"
 #include "openvino/pass/pattern/matcher.hpp"
-#include "shape_util.hpp"
 #include "shape_validation.hpp"
 #include "shared_node_info.hpp"
 #include "tensor_conversion_util.hpp"

diff --git a/src/core/src/op/adaptive_avg_pool.cpp b/src/core/src/op/adaptive_avg_pool.cpp
@@ -7,8 +7,6 @@
 #include "adaptive_avg_pool_shape_inference.hpp"
 #include "itt.hpp"
 
-using namespace std;
-
 namespace ov {
 
 op::v8::AdaptiveAvgPool::AdaptiveAvgPool(const Output<Node>& data, const Output<Node>& output_shape)
@@ -25,10 +23,10 @@ void op::v8::AdaptiveAvgPool::validate_and_infer_types() {
     set_output_type(0, get_input_element_type(0), output_shape);
 }
 
-shared_ptr<Node> op::v8::AdaptiveAvgPool::clone_with_new_inputs(const OutputVector& new_args) const {
+std::shared_ptr<Node> op::v8::AdaptiveAvgPool::clone_with_new_inputs(const OutputVector& new_args) const {
     OV_OP_SCOPE(v8_AdaptiveAvgPool_clone_with_new_inputs);
     check_new_args_count(this, new_args);
-    return make_shared<v8::AdaptiveAvgPool>(new_args.at(0), new_args.at(1));
+    return std::make_shared<v8::AdaptiveAvgPool>(new_args.at(0), new_args.at(1));
 }
 
 }  // namespace ov
diff --git a/src/core/src/op/adaptive_max_pool.cpp b/src/core/src/op/adaptive_max_pool.cpp
@@ -7,7 +7,6 @@
 #include "adaptive_max_pool_shape_inference.hpp"
 #include "itt.hpp"
 
-using namespace std;
 namespace ov {
 
 op::v8::AdaptiveMaxPool::AdaptiveMaxPool(const Output<Node>& data,
@@ -39,10 +38,10 @@ void op::v8::AdaptiveMaxPool::validate_and_infer_types() {
     set_output_type(1, m_index_element_type, output_shapes[1]);
 }
 
-shared_ptr<Node> op::v8::AdaptiveMaxPool::clone_with_new_inputs(const OutputVector& new_args) const {
+std::shared_ptr<Node> op::v8::AdaptiveMaxPool::clone_with_new_inputs(const OutputVector& new_args) const {
     OV_OP_SCOPE(v8_AdaptiveMaxPool_clone_with_new_inputs);
     check_new_args_count(this, new_args);
-    return make_shared<v8::AdaptiveMaxPool>(new_args.at(0), new_args.at(1), m_index_element_type);
+    return std::make_shared<v8::AdaptiveMaxPool>(new_args.at(0), new_args.at(1), m_index_element_type);
 }
 
 void op::v8::AdaptiveMaxPool::set_index_element_type(const element::Type& type) {

diff --git a/src/core/src/op/avg_pool.cpp b/src/core/src/op/avg_pool.cpp
@@ -2,15 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include "ngraph/op/avg_pool.hpp"
+#include "openvino/op/avg_pool.hpp"
 
 #include "avg_pool_shape_inference.hpp"
 #include "itt.hpp"
-#include "ngraph/attribute_visitor.hpp"
-#include "ngraph/graph_util.hpp"
-#include "ngraph/validation_util.hpp"
-
-using namespace std;
+#include "openvino/core/attribute_visitor.hpp"
 
 // *** AvgPool OP SET 1 ***
 ov::op::v1::AvgPool::AvgPool(const Output<Node>& arg,
@@ -109,15 +105,15 @@ void ov::op::v1::AvgPool::set_rounding_type(op::RoundingType rounding_type) {
     m_rounding_type = rounding_type;
 }
 
-shared_ptr<ov::Node> ov::op::v1::AvgPool::clone_with_new_inputs(const OutputVector& new_args) const {
+std::shared_ptr<ov::Node> ov::op::v1::AvgPool::clone_with_new_inputs(const OutputVector& new_args) const {
     OV_OP_SCOPE(v1_AvgPool_clone_with_new_inputs);
     check_new_args_count(this, new_args);
-    return make_shared<v1::AvgPool>(new_args.at(0),
-                                    m_strides,
-                                    m_pads_begin,
-                                    m_pads_end,
-                                    m_kernel,
-                                    m_exclude_pad,
-                                    m_rounding_type,
-                                    m_auto_pad);
+    return std::make_shared<AvgPool>(new_args.at(0),
+                                     m_strides,
+                                     m_pads_begin,
+                                     m_pads_end,
+                                     m_kernel,
+                                     m_exclude_pad,
+                                     m_rounding_type,
+                                     m_auto_pad);
 }
diff --git a/src/core/src/op/batch_norm.cpp b/src/core/src/op/batch_norm.cpp
@@ -2,16 +2,16 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include "ngraph/op/batch_norm.hpp"
+#include "openvino/op/batch_norm.hpp"
 
 #include <sstream>
 
 #include "itt.hpp"
-#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/validation_util.hpp"
+#include "openvino/core/attribute_visitor.hpp"
+#include "openvino/core/validation_util.hpp"
 
-using namespace std;
-using namespace ngraph;
+namespace ov {
 
 op::v0::BatchNormInference::BatchNormInference(const Output<Node>& input,
                                                const Output<Node>& gamma,
@@ -44,17 +44,17 @@ void op::v0::BatchNormInference::validate_and_infer_types() {
     set_output_size(1);
     OPENVINO_SUPPRESS_DEPRECATED_START
     std::tie(result_et, result_batch_shape, result_channel_shape) =
-        infer_batch_norm_forward(this,
-                                 get_input_element_type(INPUT_DATA),
-                                 get_input_element_type(INPUT_GAMMA),
-                                 get_input_element_type(INPUT_BETA),
-                                 get_input_element_type(INPUT_MEAN),
-                                 get_input_element_type(INPUT_VARIANCE),
-                                 get_input_partial_shape(INPUT_DATA),
-                                 get_input_partial_shape(INPUT_GAMMA),
-                                 get_input_partial_shape(INPUT_BETA),
-                                 get_input_partial_shape(INPUT_MEAN),
-                                 get_input_partial_shape(INPUT_VARIANCE));
+        ngraph::infer_batch_norm_forward(this,
+                                         get_input_element_type(INPUT_DATA),
+                                         get_input_element_type(INPUT_GAMMA),
+                                         get_input_element_type(INPUT_BETA),
+                                         get_input_element_type(INPUT_MEAN),
+                                         get_input_element_type(INPUT_VARIANCE),
+                                         get_input_partial_shape(INPUT_DATA),
+                                         get_input_partial_shape(INPUT_GAMMA),
+                                         get_input_partial_shape(INPUT_BETA),
+                                         get_input_partial_shape(INPUT_MEAN),
+                                         get_input_partial_shape(INPUT_VARIANCE));
     OPENVINO_SUPPRESS_DEPRECATED_END
     set_output_type(0, result_et, result_batch_shape);
 }
@@ -101,17 +101,17 @@ void op::v5::BatchNormInference::validate_and_infer_types() {
     set_output_size(1);
     OPENVINO_SUPPRESS_DEPRECATED_START
     std::tie(result_et, result_batch_shape, result_channel_shape) =
-        infer_batch_norm_forward(this,
-                                 get_input_element_type(INPUT_DATA),
-                                 get_input_element_type(INPUT_GAMMA),
-                                 get_input_element_type(INPUT_BETA),
-                                 get_input_element_type(INPUT_MEAN),
-                                 get_input_element_type(INPUT_VARIANCE),
-                                 get_input_partial_shape(INPUT_DATA),
-                                 get_input_partial_shape(INPUT_GAMMA),
-                                 get_input_partial_shape(INPUT_BETA),
-                                 get_input_partial_shape(INPUT_MEAN),
-                                 get_input_partial_shape(INPUT_VARIANCE));
+        ngraph::infer_batch_norm_forward(this,
+                                         get_input_element_type(INPUT_DATA),
+                                         get_input_element_type(INPUT_GAMMA),
+                                         get_input_element_type(INPUT_BETA),
+                                         get_input_element_type(INPUT_MEAN),
+                                         get_input_element_type(INPUT_VARIANCE),
+                                         get_input_partial_shape(INPUT_DATA),
+                                         get_input_partial_shape(INPUT_GAMMA),
+                                         get_input_partial_shape(INPUT_BETA),
+                                         get_input_partial_shape(INPUT_MEAN),
+                                         get_input_partial_shape(INPUT_VARIANCE));
     OPENVINO_SUPPRESS_DEPRECATED_END
     set_output_type(0, result_et, result_batch_shape);
 }
@@ -126,3 +126,4 @@ std::shared_ptr<Node> op::v5::BatchNormInference::clone_with_new_inputs(const Ou
                                                 new_args.at(4),
                                                 m_epsilon);
 }
+}  // namespace ov
diff --git a/src/core/src/op/batch_to_space.cpp b/src/core/src/op/batch_to_space.cpp
@@ -177,8 +177,8 @@ bool batch_to_space_evaluate(const HostTensorVector& outputs, const HostTensorVe
 bool ngraph::op::v1::BatchToSpace::evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const {
     OV_OP_SCOPE(v1_BatchToSpace_evaluate);
     OPENVINO_SUPPRESS_DEPRECATED_START
-    NGRAPH_CHECK(validate_host_tensor_vector(inputs, 4));
-    NGRAPH_CHECK(validate_host_tensor_vector(outputs, 1));
+    OPENVINO_ASSERT(validate_host_tensor_vector(inputs, 4));
+    OPENVINO_ASSERT(validate_host_tensor_vector(outputs, 1));
     OPENVINO_SUPPRESS_DEPRECATED_END
 
     if (outputs[0]->get_partial_shape().is_dynamic()) {

diff --git a/src/core/src/op/binary_convolution.cpp b/src/core/src/op/binary_convolution.cpp
@@ -11,8 +11,6 @@
 #include "openvino/core/axis_vector.hpp"
 #include "openvino/core/coordinate_diff.hpp"
 
-using namespace std;
-
 ov::op::v1::BinaryConvolution::BinaryConvolution(const Output<Node>& data,
                                                  const Output<Node>& kernel,
                                                  const Strides& strides,
@@ -67,18 +65,18 @@ void ov::op::v1::BinaryConvolution::validate_and_infer_types() {
     set_output_type(0, data_batch_et, output_shapes[0]);
 }
 
-shared_ptr<ov::Node> ov::op::v1::BinaryConvolution::clone_with_new_inputs(const OutputVector& new_args) const {
+std::shared_ptr<ov::Node> ov::op::v1::BinaryConvolution::clone_with_new_inputs(const OutputVector& new_args) const {
     OV_OP_SCOPE(v1_BinaryConvolution_clone_with_new_inputs);
     check_new_args_count(this, new_args);
-    return make_shared<v1::BinaryConvolution>(new_args.at(0),
-                                              new_args.at(1),
-                                              m_strides,
-                                              m_pads_begin,
-                                              m_pads_end,
-                                              m_dilations,
-                                              m_mode,
-                                              m_pad_value,
-                                              m_auto_pad);
+    return std::make_shared<v1::BinaryConvolution>(new_args.at(0),
+                                                   new_args.at(1),
+                                                   m_strides,
+                                                   m_pads_begin,
+                                                   m_pads_end,
+                                                   m_dilations,
+                                                   m_mode,
+                                                   m_pad_value,
+                                                   m_auto_pad);
 }
 
 bool ov::op::v1::BinaryConvolution::visit_attributes(AttributeVisitor& visitor) {