Merge branch 'master' into releases/2024.1

src/bindings/c/include/openvino/c/ov_prepostprocess.h

@@ -215,6 +215,19 @@ ov_preprocess_preprocess_steps_resize(ov_preprocess_preprocess_steps_t* preproce
 OPENVINO_C_API(ov_status_e)
 ov_preprocess_preprocess_steps_scale(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps, float value);
 
+/**
+ * @brief Add scale preprocess operation. Divide each channel element of input by different specified value.
+ * @ingroup ov_prepostprocess_c_api
+ * @param preprocess_input_process_steps A pointer to ov_preprocess_preprocess_steps_t.
+ * @param values Scaling values array for each channels
+ * @param value_size Scaling value size
+ * @return Status code of the operation: OK(0) for success.
+ */
+OPENVINO_C_API(ov_status_e)
+ov_preprocess_preprocess_steps_scale_multi_channels(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps,
+                                                    const float* values,
+                                                    const int32_t value_size);
+
 /**
  * @brief Add mean preprocess operation. Subtract specified value from each element of input.
  * @ingroup ov_prepostprocess_c_api
@@ -225,6 +238,19 @@ ov_preprocess_preprocess_steps_scale(ov_preprocess_preprocess_steps_t* preproces
 OPENVINO_C_API(ov_status_e)
 ov_preprocess_preprocess_steps_mean(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps, float value);
 
+/**
+ * @brief Add mean preprocess operation. Subtract each channel element of input by different specified value.
+ * @ingroup ov_prepostprocess_c_api
+ * @param preprocess_input_process_steps A pointer to ov_preprocess_preprocess_steps_t.
+ * @param values Value array to subtract from each element.
+ * @param value_size Mean value size
+ * @return Status code of the operation: OK(0) for success.
+ */
+OPENVINO_C_API(ov_status_e)
+ov_preprocess_preprocess_steps_mean_multi_channels(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps,
+                                                   const float* values,
+                                                   const int32_t value_size);
+
 /**
  * @brief Crop input tensor between begin and end coordinates.
  * @ingroup ov_prepostprocess_c_api

src/bindings/c/src/ov_prepostprocess.cpp

@@ -167,6 +167,22 @@ ov_status_e ov_preprocess_preprocess_steps_scale(ov_preprocess_preprocess_steps_
     return ov_status_e::OK;
 }
 
+OPENVINO_C_API(ov_status_e)
+ov_preprocess_preprocess_steps_scale_multi_channels(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps,
+                                                    const float* values,
+                                                    const int32_t value_size) {
+    if (!preprocess_input_process_steps || !values || value_size <= 0) {
+        return ov_status_e::INVALID_C_PARAM;
+    }
+    try {
+        std::vector<float> scale_vec(values, values + value_size);
+        preprocess_input_process_steps->object->scale(scale_vec);
+    }
+    CATCH_OV_EXCEPTIONS
+
+    return ov_status_e::OK;
+}
+
 ov_status_e ov_preprocess_preprocess_steps_mean(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps,
                                                 float value) {
     if (!preprocess_input_process_steps) {
@@ -180,6 +196,22 @@ ov_status_e ov_preprocess_preprocess_steps_mean(ov_preprocess_preprocess_steps_t
     return ov_status_e::OK;
 }
 
+OPENVINO_C_API(ov_status_e)
+ov_preprocess_preprocess_steps_mean_multi_channels(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps,
+                                                   const float* values,
+                                                   const int32_t value_size) {
+    if (!preprocess_input_process_steps || !values || value_size <= 0) {
+        return ov_status_e::INVALID_C_PARAM;
+    }
+    try {
+        std::vector<float> mean_vec(values, values + value_size);
+        preprocess_input_process_steps->object->mean(mean_vec);
+    }
+    CATCH_OV_EXCEPTIONS
+
+    return ov_status_e::OK;
+}
+
 ov_status_e ov_preprocess_preprocess_steps_crop(ov_preprocess_preprocess_steps_t* preprocess_input_process_steps,
                                                 int32_t* begin,
                                                 int32_t begin_size,

src/bindings/c/tests/ov_preprocess_test.cpp

@@ -8,6 +8,7 @@ class ov_preprocess_test : public ::testing::Test {
     void SetUp() override {
         core = nullptr;
         model = nullptr;
+        ppp_model = nullptr;
         preprocess = nullptr;
         input_info = nullptr;
         input_tensor_info = nullptr;
@@ -37,13 +38,15 @@ class ov_preprocess_test : public ::testing::Test {
         ov_preprocess_input_info_free(input_info);
         ov_preprocess_prepostprocessor_free(preprocess);
         ov_model_free(model);
+        ov_model_free(ppp_model);
         ov_core_free(core);
         TestDataHelpers::release_test_model();
     }
 
 public:
     ov_core_t* core;
     ov_model_t* model;
+    ov_model_t* ppp_model;
     ov_preprocess_prepostprocessor_t* preprocess;
     ov_preprocess_input_info_t* input_info;
     ov_preprocess_input_tensor_info_t* input_tensor_info;
@@ -113,10 +116,19 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_resize) {
     OV_EXPECT_OK(ov_preprocess_prepostprocessor_get_input_info_by_index(preprocess, 0, &input_info));
     EXPECT_NE(nullptr, input_info);
 
+    ov_layout_t* layout = nullptr;
+    const char* layout_desc = "NCHW";
+    OV_EXPECT_OK(ov_layout_create(layout_desc, &layout));
+    OV_EXPECT_OK(ov_preprocess_input_info_get_model_info(input_info, &input_model));
+    OV_EXPECT_OK(ov_preprocess_input_model_info_set_layout(input_model, layout));
+    ov_layout_free(layout);
+
     OV_EXPECT_OK(ov_preprocess_input_info_get_preprocess_steps(input_info, &input_process));
     EXPECT_NE(nullptr, input_process);
 
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_resize(input_process, ov_preprocess_resize_algorithm_e::RESIZE_LINEAR));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_scale) {
@@ -130,6 +142,31 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_scale) {
     EXPECT_NE(nullptr, input_process);
 
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_scale(input_process, 2.0f));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
+}
+
+TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_scale_multi_channels) {
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_create(model, &preprocess));
+    EXPECT_NE(nullptr, preprocess);
+
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_get_input_info_by_index(preprocess, 0, &input_info));
+    EXPECT_NE(nullptr, input_info);
+
+    ov_layout_t* layout = nullptr;
+    const char* layout_desc = "NCHW";
+    OV_EXPECT_OK(ov_layout_create(layout_desc, &layout));
+    OV_EXPECT_OK(ov_preprocess_input_info_get_model_info(input_info, &input_model));
+    OV_EXPECT_OK(ov_preprocess_input_model_info_set_layout(input_model, layout));
+    ov_layout_free(layout);
+
+    OV_EXPECT_OK(ov_preprocess_input_info_get_preprocess_steps(input_info, &input_process));
+    EXPECT_NE(nullptr, input_process);
+
+    float values[3] = {2.0f, 2.0f, 2.0f};
+    OV_EXPECT_OK(ov_preprocess_preprocess_steps_scale_multi_channels(input_process, values, 3));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_mean) {
@@ -143,6 +180,31 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_mean) {
     EXPECT_NE(nullptr, input_process);
 
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_mean(input_process, 2.0f));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
+}
+
+TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_mean_multi_channels) {
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_create(model, &preprocess));
+    EXPECT_NE(nullptr, preprocess);
+
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_get_input_info_by_index(preprocess, 0, &input_info));
+    EXPECT_NE(nullptr, input_info);
+
+    ov_layout_t* layout = nullptr;
+    const char* layout_desc = "NCHW";
+    OV_EXPECT_OK(ov_layout_create(layout_desc, &layout));
+    OV_EXPECT_OK(ov_preprocess_input_info_get_model_info(input_info, &input_model));
+    OV_EXPECT_OK(ov_preprocess_input_model_info_set_layout(input_model, layout));
+    ov_layout_free(layout);
+
+    OV_EXPECT_OK(ov_preprocess_input_info_get_preprocess_steps(input_info, &input_process));
+    EXPECT_NE(nullptr, input_process);
+
+    float values[3] = {2.0f, 2.0f, 2.0f};
+    OV_EXPECT_OK(ov_preprocess_preprocess_steps_mean_multi_channels(input_process, values, 3));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_crop) {
@@ -152,12 +214,25 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_crop) {
     OV_EXPECT_OK(ov_preprocess_prepostprocessor_get_input_info_by_index(preprocess, 0, &input_info));
     EXPECT_NE(nullptr, input_info);
 
+    ov_layout_t* layout = nullptr;
+    const char* layout_desc = "NCHW";
+    OV_EXPECT_OK(ov_layout_create(layout_desc, &layout));
+    OV_EXPECT_OK(ov_preprocess_input_info_get_model_info(input_info, &input_model));
+    OV_EXPECT_OK(ov_preprocess_input_model_info_set_layout(input_model, layout));
+    ov_layout_free(layout);
+
+    OV_EXPECT_OK(ov_preprocess_input_info_get_tensor_info(input_info, &input_tensor_info));
+    EXPECT_NE(nullptr, input_tensor_info);
+    OV_EXPECT_OK(ov_preprocess_input_tensor_info_set_spatial_static_shape(input_tensor_info, 256, 272));
+
     OV_EXPECT_OK(ov_preprocess_input_info_get_preprocess_steps(input_info, &input_process));
     EXPECT_NE(nullptr, input_process);
 
-    int32_t begin[] = {0, 0, 5, 10};
-    int32_t end[] = {1, 3, 15, 20};
+    int32_t begin[] = {0, 0, 10, 20};
+    int32_t end[] = {1, 3, 237, 247};
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_crop(input_process, begin, 4, end, 4));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_convert_layout) {
@@ -174,6 +249,8 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_convert_layout) {
     const char* input_layout_desc = "NCHW";
     OV_EXPECT_OK(ov_layout_create(input_layout_desc, &layout));
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_convert_layout(input_process, layout));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 
     ov_layout_free(layout);
 }
@@ -185,10 +262,19 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_reverse_channels) {
     OV_EXPECT_OK(ov_preprocess_prepostprocessor_get_input_info_by_index(preprocess, 0, &input_info));
     EXPECT_NE(nullptr, input_info);
 
+    ov_layout_t* layout = nullptr;
+    const char* layout_desc = "NCHW";
+    OV_EXPECT_OK(ov_layout_create(layout_desc, &layout));
+    OV_EXPECT_OK(ov_preprocess_input_info_get_model_info(input_info, &input_model));
+    OV_EXPECT_OK(ov_preprocess_input_model_info_set_layout(input_model, layout));
+    ov_layout_free(layout);
+
     OV_EXPECT_OK(ov_preprocess_input_info_get_preprocess_steps(input_info, &input_process));
     EXPECT_NE(nullptr, input_process);
 
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_reverse_channels(input_process));
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_input_tensor_info_set_element_type) {
@@ -287,6 +373,9 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_convert_element_type)
 
     OV_EXPECT_OK(ov_preprocess_input_tensor_info_set_element_type(input_tensor_info, ov_element_type_e::U8));
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_convert_element_type(input_process, ov_element_type_e::F32));
+
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_convert_color) {
@@ -307,7 +396,19 @@ TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_convert_color) {
                                                                                2,
                                                                                "y",
                                                                                "uv"));
+    OV_EXPECT_OK(ov_preprocess_input_tensor_info_set_spatial_static_shape(input_tensor_info, 320, 320));
     OV_EXPECT_OK(ov_preprocess_preprocess_steps_convert_color(input_process, ov_color_format_e::BGR));
+    OV_EXPECT_OK(ov_preprocess_preprocess_steps_resize(input_process, RESIZE_LINEAR));
+
+    ov_layout_t* layout = nullptr;
+    const char* layout_desc = "NCHW";
+    OV_EXPECT_OK(ov_layout_create(layout_desc, &layout));
+    OV_EXPECT_OK(ov_preprocess_input_info_get_model_info(input_info, &input_model));
+    OV_EXPECT_OK(ov_preprocess_input_model_info_set_layout(input_model, layout));
+    ov_layout_free(layout);
+
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_preprocess_steps_convert_color_rgb_to_gray) {
@@ -408,11 +509,8 @@ TEST_F(ov_preprocess_test, ov_preprocess_prepostprocessor_build) {
     OV_EXPECT_OK(ov_preprocess_prepostprocessor_create(model, &preprocess));
     EXPECT_NE(nullptr, preprocess);
 
-    ov_model_t* new_model = nullptr;
-    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &new_model));
-    EXPECT_NE(nullptr, new_model);
-
-    ov_model_free(new_model);
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_prepostprocessor_build_apply) {
@@ -457,12 +555,9 @@ TEST_F(ov_preprocess_test, ov_preprocess_prepostprocessor_build_apply) {
     EXPECT_NE(nullptr, output_tensor_info);
     OV_EXPECT_OK(ov_preprocess_output_set_element_type(output_tensor_info, ov_element_type_e::F32));
 
-    ov_model_t* new_model = nullptr;
-    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &new_model));
-    EXPECT_NE(nullptr, new_model);
-
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
     ov_shape_free(&shape);
-    ov_model_free(new_model);
 }
 
 TEST_F(ov_preprocess_test, ov_preprocess_prepostprocessor_for_nv12_input) {
@@ -496,10 +591,8 @@ TEST_F(ov_preprocess_test, ov_preprocess_prepostprocessor_for_nv12_input) {
     ov_layout_create("NCHW", &layout);
     OV_EXPECT_OK(ov_preprocess_input_model_info_set_layout(input_model, layout));
 
-    ov_model_t* new_model = nullptr;
-    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &new_model));
-    EXPECT_NE(nullptr, new_model);
+    OV_EXPECT_OK(ov_preprocess_prepostprocessor_build(preprocess, &ppp_model));
+    EXPECT_NE(nullptr, ppp_model);
 
     ov_layout_free(layout);
-    ov_model_free(new_model);
 }

src/frontends/paddle/docs/operation_mapping_flow.md

@@ -1,7 +1,7 @@
 # OpenVINO Paddle Frontend Operator Enabling Flow
 
 1. Declare `CreatorFunction` for the Paddle operator and register it to the map in `src/op_table.cpp`.
-   * The map is retrived from:
+   * The map is retrieved from:
 
      https://github.com/openvinotoolkit/openvino/blob/7d5e0abcaa03703de9918ece2115e6ea652c39e0/src/frontends/paddle/src/op_table.cpp#L106
 

src/frontends/paddle/include/openvino/frontend/paddle/exception.hpp

@@ -34,7 +34,7 @@ class OpValidationFailure : public ov::frontend::OpValidationFailure {
 /// \param cond Condition to check
 /// \param ... Additional error message info to be added to the error message via the `<<`
 ///            stream-insertion operator. Note that the expressions here will be evaluated lazily,
-///            i.e., only if the `cond` evalutes to `false`.
+///            i.e., only if the `cond` evaluates to `false`.
 /// \throws ::ov::OpValidationFailure if `cond` is false.
 #define PADDLE_OP_CHECK(node_context, ...) \
     OPENVINO_ASSERT_HELPER(::ov::frontend::paddle::OpValidationFailure, (node_context), __VA_ARGS__)

src/frontends/paddle/src/internal/op/conditional_block.cpp

@@ -73,7 +73,7 @@ void op::internal::ConditionalBlock::validate_and_infer_types() {
 const OutputVector op::internal::ConditionalBlock::get_inputs_from_parent() const {
     OutputVector result;
     const auto& inputs = this->input_values();
-    for (size_t i = 0; i < inputs.size() - 1; i++) {  // execpt the one at last, which is "cond".
+    for (size_t i = 0; i < inputs.size() - 1; i++) {  // except the one at last, which is "cond".
         result.push_back(inputs[i]);
     }
     return result;

src/frontends/paddle/src/internal/pass/transform_if.cpp

@@ -16,8 +16,8 @@ using namespace ov;
 using namespace ov::pass;
 using namespace ov::frontend::paddle::op::default_opset;
 
-// Transform Paddle "conditonal_block" to OpenVINO If op.
-// The contional_block only has "then" branch, while If op requires both "then" and "else" branch the same time.
+// Transform Paddle "conditional_block" to OpenVINO If op.
+// The conditional_block only has "then" branch, while If op requires both "then" and "else" branch the same time.
 // Thus a "pass-through" model is built on purpose for "else" branch with the same outputs as "then" branch.
 ov::frontend::paddle::pass::TransformIf::TransformIf(std::vector<std::shared_ptr<Model>> funcs) {
     const auto cond_label = pattern::wrap_type<ov::op::internal::ConditionalBlock>();

src/frontends/paddle/tests/test_models/gen_scripts/generate_assign.py

@@ -10,7 +10,7 @@
 from save_model import exportModel
 
 '''
-assign w/ ouput
+assign w/ output
 '''
 @paddle.jit.to_static
 def test_assign_output(array):
@@ -24,7 +24,7 @@ def test_assign_output(array):
 exportModel('assign_output', test_assign_output, [array], target_dir=sys.argv[1])
 
 '''
-assign w/o ouput
+assign w/o output
 '''
 @paddle.jit.to_static
 def test_assign_none(data):