Merge branch 'master' into itikhono/transformations/ngraph_to_ov_refa…

…ctoring
itikhono · Sep 28, 2023 · 288b13a · 288b13a
2 parents 16c7f67 + 23e602f
commit 288b13a
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Showing 36 changed files with 588 additions and 665 deletions.
diff --git a/.github/workflows/code_style.yml b/.github/workflows/code_style.yml
@@ -85,7 +85,7 @@ jobs:
       - name: Install Clang dependency
         run: |
           sudo apt update
-          sudo apt --assume-yes remove clang-7 clang-8 clang-9 clang-10 clang-11 clang-12 clang-13
+          sudo apt --assume-yes remove clang-7 clang-8 clang-9 clang-10 clang-11 clang-12 clang-13 clang-15
           sudo apt --assume-yes install clang-14 libclang-14-dev
 
       - name: Install Python-based dependencies

diff --git a/src/core/dev_api/validation_util.hpp b/src/core/dev_api/validation_util.hpp
@@ -38,5 +38,14 @@ OPENVINO_API int64_t clip(const int64_t& value, const int64_t& min, const int64_
 ///
 /// \return Constant node or nullptr if unable to constantfold the subgraph
 OPENVINO_API std::shared_ptr<op::v0::Constant> constantfold_subgraph(const Output<Node>& subgraph_sink);
+
+/**
+ * @brief Runs an estimation of source tensor. If it succeeded to calculate both bounds and
+ * they are the same returns Constant operation from the resulting bound, otherwise nullptr.
+ *
+ * @param source  Node output used to get its tensor data as constant.
+ * @return Shared pointer to constant data or nullptr.
+ */
+OPENVINO_API std::shared_ptr<op::v0::Constant> get_constant_from_source(const Output<Node>& source);
 }  // namespace util
 }  // namespace ov
diff --git a/src/core/include/openvino/op/reduce_max.hpp b/src/core/include/openvino/op/reduce_max.hpp
@@ -26,9 +26,7 @@ class OPENVINO_API ReduceMax : public util::ArithmeticReductionKeepDims {
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
     bool has_evaluate() const override;
     bool evaluate_lower(TensorVector& outputs) const override;
     bool evaluate_upper(TensorVector& outputs) const override;

diff --git a/src/core/include/openvino/op/reduce_mean.hpp b/src/core/include/openvino/op/reduce_mean.hpp
@@ -24,9 +24,7 @@ class OPENVINO_API ReduceMean : public util::ArithmeticReductionKeepDims {
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
     bool has_evaluate() const override;
 };
 }  // namespace v1

diff --git a/src/core/include/openvino/op/reduce_min.hpp b/src/core/include/openvino/op/reduce_min.hpp
@@ -26,9 +26,7 @@ class OPENVINO_API ReduceMin : public util::ArithmeticReductionKeepDims {
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
     bool has_evaluate() const override;
     bool evaluate_lower(TensorVector& outputs) const override;
     bool evaluate_upper(TensorVector& outputs) const override;

diff --git a/src/core/include/openvino/op/reduce_prod.hpp b/src/core/include/openvino/op/reduce_prod.hpp
@@ -27,9 +27,7 @@ class OPENVINO_API ReduceProd : public util::ArithmeticReductionKeepDims {
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
     bool has_evaluate() const override;
     bool evaluate_lower(TensorVector& outputs) const override;
     bool evaluate_upper(TensorVector& outputs) const override;

diff --git a/src/core/include/openvino/op/reduce_sum.hpp b/src/core/include/openvino/op/reduce_sum.hpp
@@ -73,9 +73,7 @@ class OPENVINO_API ReduceSum : public util::ArithmeticReductionKeepDims {
 
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
     bool has_evaluate() const override;
 };
 }  // namespace v1

diff --git a/src/core/reference/include/openvino/reference/group_normalization.hpp b/src/core/reference/include/openvino/reference/group_normalization.hpp
@@ -8,8 +8,8 @@
 #include <numeric>
 
 #include "openvino/core/shape.hpp"
-#include "openvino/reference/mean.hpp"
-#include "openvino/reference/sum.hpp"
+#include "openvino/reference/reduce_mean.hpp"
+#include "openvino/reference/reduce_sum.hpp"
 
 namespace ov {
 namespace reference {
@@ -38,11 +38,11 @@ void group_normalization(const T* const data,
             const auto group_begin = data + n * batch_size + g * group_size;
             const auto group_end = group_begin + group_size;
             std::vector<T> mean_value(1);
-            mean(group_begin, mean_value.data(), Shape{group_size}, {0});
+            reduce_mean(group_begin, mean_value.data(), Shape{group_size}, {0});
             T mean = mean_value[0];
             T variance = 0, err = 0;
             for_each(group_begin, group_end, [&](const T d) {
-                return details::kahan_summation(static_cast<T>(pow(d - mean, 2)), err, variance);
+                variance = details::kahan_summation(static_cast<T>(pow(d - mean, 2)), variance, err);
             });
             variance /= group_size;
             const T standard_deviation = sqrt(variance + eps);

diff --git a/src/core/reference/include/openvino/reference/log_softmax.hpp b/src/core/reference/include/openvino/reference/log_softmax.hpp
@@ -7,8 +7,8 @@
 #include <cmath>
 
 #include "ngraph/shape_util.hpp"
-#include "openvino/reference/max.hpp"
-#include "openvino/reference/sum.hpp"
+#include "openvino/reference/reduce_max.hpp"
+#include "openvino/reference/reduce_sum.hpp"
 #include "openvino/reference/utils/coordinate_transform.hpp"
 
 namespace ov {
@@ -21,7 +21,7 @@ void log_softmax(const T* arg, T* out, const Shape& shape, const AxisSet& axes)
     auto temp_max = std::vector<T>(temp_elements, 0);
     auto temp_sum = std::vector<T>(temp_elements, 0);
 
-    max(arg, temp_max.data(), shape, axes);
+    reduce_max(arg, temp_max.data(), shape, axes);
 
     CoordinateTransform transform(shape);
     CoordinateTransform temp_transform(temp_shape);
@@ -31,7 +31,7 @@ void log_softmax(const T* arg, T* out, const Shape& shape, const AxisSet& axes)
             static_cast<T>(std::exp(arg[transform.index(coord)] - temp_max[temp_transform.index(temp_coord)]));
     }
 
-    sum(out, temp_sum.data(), shape, axes);
+    reduce_sum(out, temp_sum.data(), shape, axes);
 
     for (const Coordinate& coord : transform) {
         Coordinate temp_coord = ngraph::reduce(coord, axes, true);

diff --git a/src/core/reference/include/openvino/reference/max.hpp b/src/core/reference/include/openvino/reference/max.hpp
diff --git a/src/core/reference/include/openvino/reference/mean.hpp b/src/core/reference/include/openvino/reference/mean.hpp
diff --git a/src/core/reference/include/openvino/reference/min.hpp b/src/core/reference/include/openvino/reference/min.hpp
diff --git a/src/core/reference/include/openvino/reference/mvn.hpp b/src/core/reference/include/openvino/reference/mvn.hpp
@@ -10,11 +10,11 @@
 
 #include "openvino/reference/add.hpp"
 #include "openvino/reference/divide.hpp"
-#include "openvino/reference/mean.hpp"
 #include "openvino/reference/multiply.hpp"
+#include "openvino/reference/reduce_mean.hpp"
+#include "openvino/reference/reduce_sum.hpp"
 #include "openvino/reference/sqrt.hpp"
 #include "openvino/reference/subtract.hpp"
-#include "openvino/reference/sum.hpp"
 
 namespace ov {
 namespace reference {
@@ -28,13 +28,13 @@ void mvn(const T* arg,
          const double eps) {
     auto reduced_shape = ngraph::reduce(in_shape, reduction_axes, true);
     std::vector<T> tmp_buffer(shape_size(in_shape));
-    mean(arg, tmp_buffer.data(), in_shape, reduction_axes);
+    reduce_mean(arg, tmp_buffer.data(), in_shape, reduction_axes);
     subtract(arg, tmp_buffer.data(), out, in_shape, reduced_shape, op::AutoBroadcastType::NUMPY);
 
     if (normalize_variance) {
         multiply(out, out, tmp_buffer.data(), shape_size(in_shape));
         std::vector<T> mean_value(shape_size(reduced_shape));
-        mean(tmp_buffer.data(), mean_value.data(), in_shape, reduction_axes);
+        reduce_mean(tmp_buffer.data(), mean_value.data(), in_shape, reduction_axes);
 
         add(mean_value.data(),
             std::vector<T>(shape_size(reduced_shape), static_cast<T>(eps)).data(),
@@ -58,13 +58,13 @@ void mvn_6(const T* arg,
            op::MVNEpsMode eps_mode) {
     auto reduced_shape = ngraph::reduce(in_shape, reduction_axes, true);
     std::vector<T> tmp_buffer(shape_size(in_shape));
-    mean(arg, tmp_buffer.data(), in_shape, reduction_axes);
+    reduce_mean(arg, tmp_buffer.data(), in_shape, reduction_axes);
     subtract(arg, tmp_buffer.data(), out, in_shape, reduced_shape, op::AutoBroadcastType::NUMPY);
 
     if (normalize_variance) {
         multiply(out, out, tmp_buffer.data(), shape_size(in_shape));
         std::vector<T> mean_value(shape_size(reduced_shape));
-        mean(tmp_buffer.data(), mean_value.data(), in_shape, reduction_axes);
+        reduce_mean(tmp_buffer.data(), mean_value.data(), in_shape, reduction_axes);
 
         if (eps_mode == op::MVNEpsMode::INSIDE_SQRT) {
             add(mean_value.data(),

diff --git a/src/core/reference/include/openvino/reference/normalize_l2.hpp b/src/core/reference/include/openvino/reference/normalize_l2.hpp
@@ -7,7 +7,7 @@
 #include <ngraph/op/normalize_l2.hpp>
 
 #include "openvino/reference/autobroadcast_binop.hpp"
-#include "openvino/reference/sum.hpp"
+#include "openvino/reference/reduce_sum.hpp"
 
 namespace ov {
 namespace reference {
@@ -38,7 +38,7 @@ void normalize_l2(const T* data,
     }
 
     std::vector<T> sum_data(shape_size(reduce_shape));
-    sum(sqr_data.data(), sum_data.data(), data_shape, reduction_axes);
+    reduce_sum(sqr_data.data(), sum_data.data(), data_shape, reduction_axes);
     autobroadcast_binop(data,
                         sum_data.data(),
                         out,

diff --git a/src/core/reference/include/openvino/reference/product.hpp b/src/core/reference/include/openvino/reference/product.hpp