diff --git a/.ci/azure/linux_onnxruntime.yml b/.ci/azure/linux_onnxruntime.yml
index ad5e630820d..4fd14f2c1b1 100644
--- a/.ci/azure/linux_onnxruntime.yml
+++ b/.ci/azure/linux_onnxruntime.yml
@@ -94,7 +94,7 @@ jobs:
-DENABLE_PROFILING_ITT=OFF
-DENABLE_SAMPLES=OFF
-DNGRAPH_ONNX_FRONTEND_ENABLE=ON
- -DNGRAPH_DEBUG_ENABLE=OFF
+ -DOPENVINO_DEBUG_ENABLE=OFF
$(REPO_DIR)
workingDirectory: $(BUILD_DIR)
diff --git a/.ci/azure/windows.yml b/.ci/azure/windows.yml
index 62e0fa7c712..81c1ba95601 100644
--- a/.ci/azure/windows.yml
+++ b/.ci/azure/windows.yml
@@ -16,7 +16,7 @@ jobs:
timeoutInMinutes: 120
pool:
- name: WIN_VMSS_VENV_F8S_WU2
+ name: WIN_VMSS_VENV_F16S_WU2
variables:
system.debug: true
@@ -34,8 +34,6 @@ jobs:
INSTALL_DIR: $(WORK_DIR)\install_pkg
INSTALL_TEST_DIR: $(INSTALL_DIR)\tests
SETUPVARS: $(INSTALL_DIR)\setupvars.bat
- IB_DIR: C:\Program Files (x86)\IncrediBuild
- IB_TESTCONSOLE: $(IB_DIR)\IBTestConsole.exe
steps:
- script: |
@@ -59,12 +57,6 @@ jobs:
rd /Q /S $(BUILD_SAMPLES_DIR) & mkdir $(BUILD_SAMPLES_DIR)
displayName: 'Make dir'
- - script: |
- certutil -urlcache -split -f https://openvinoweb.z5.web.core.windows.net/incredibuild/install_ib_console.bat install_ib_console.bat
- call install_ib_console.bat
- workingDirectory: $(WORK_DIR)
- displayName: 'Install IncrediBuild'
-
- checkout: self
clean: true
lfs: false
@@ -109,9 +101,7 @@ jobs:
- script: dir $(REPO_DIR)\inference-engine\temp\ /s
displayName: 'List temp SDKs'
- - script: |
- set PATH=$(WORK_DIR)\ninja-win;%PATH%
- call "$(MSVS_VARS_PATH)" && "C:\Program Files (x86)\IncrediBuild\BuildConsole.exe" /COMMAND="ninja"
+ - script: call "$(MSVS_VARS_PATH)" && $(WORK_DIR)\ninja-win\ninja
workingDirectory: $(BUILD_DIR)
displayName: 'Build Win'
@@ -153,10 +143,8 @@ jobs:
displayName: 'PaddlePaddle Frontend UT'
continueOnError: false
- - script: |
- set PATH=$(IB_DIR);%PATH%
- call $(SETUPVARS) && "$(IB_TESTCONSOLE)" $(INSTALL_TEST_DIR)\InferenceEngineUnitTests.exe --gtest_output=xml:TEST-InferenceEngineUnitTests-IB.xml
- displayName: 'IE UT old - IB'
+ - script: call $(SETUPVARS) && $(INSTALL_TEST_DIR)\InferenceEngineUnitTests.exe --gtest_output=xml:TEST-InferenceEngineUnitTests.xml
+ displayName: 'IE UT old'
continueOnError: false
- script: call $(SETUPVARS) && $(INSTALL_TEST_DIR)\ieUnitTests --gtest_output=xml:TEST-ieUnitTests.xml
@@ -187,11 +175,8 @@ jobs:
displayName: 'TEMPLATE FuncTests'
continueOnError: false
- # call $(SETUPVARS) && $(INSTALL_TEST_DIR)\cpuFuncTests.exe --gtest_filter=*smoke* --gtest_output=xml:TEST-cpuFuncTests.xml
- - script: |
- set PATH=$(IB_DIR);%PATH%
- call $(SETUPVARS) && "$(IB_TESTCONSOLE)" $(INSTALL_TEST_DIR)\cpuFuncTests.exe --gtest_filter=*smoke*:-*CompareWithRefs/base_size=16_pre_nms_topn=100_post_nms_topn=100_nms_thresh=0.7_feat_stride=1_min_size=1_ratio*:*smoke_GRUSequenceCommonZeroClip/GRUSequenceTest.CompareWithRefs/mode=CONVERT_TO_TI_MAX_SEQ_LEN_CONST_seq_lengths* --gtest_output=xml:TEST-cpuFuncTests-IB.xml /testlevel=24
- displayName: 'CPU FuncTests - IB'
+ - script: $(SETUPVARS) && $(INSTALL_TEST_DIR)\cpuFuncTests.exe --gtest_filter=*smoke* --gtest_output=xml:TEST-cpuFuncTests.xml
+ displayName: 'CPU FuncTests'
continueOnError: false
- script: |
@@ -213,8 +198,3 @@ jobs:
buildPlatform: 'x64' # Optional
buildConfiguration: 'Windows' # Optional
#publishRunAttachments: true # Optional
-
- - script: echo Stop IncrediBuild_Agent && net stop IncrediBuild_Agent
- displayName: Stop IncrediBuild
- continueOnError: true
- enabled: false
diff --git a/.ci/openvino-onnx/Dockerfile b/.ci/openvino-onnx/Dockerfile
index 8e2365e4ebc..ada3c36adb1 100644
--- a/.ci/openvino-onnx/Dockerfile
+++ b/.ci/openvino-onnx/Dockerfile
@@ -68,7 +68,7 @@ RUN cmake .. \
-DENABLE_PYTHON=ON \
-DPYTHON_EXECUTABLE=/usr/bin/python3 \
-DNGRAPH_ONNX_FRONTEND_ENABLE=ON \
- -DNGRAPH_DEBUG_ENABLE=OFF \
+ -DOPENVINO_DEBUG_ENABLE=OFF \
-DCMAKE_INSTALL_PREFIX=/openvino/dist \
-DNGRAPH_USE_PROTOBUF_LITE=${PROTOBUF_LITE}
RUN make -j $(nproc) install
diff --git a/.ci/openvino-onnx/watchdog/src/watchdog.py b/.ci/openvino-onnx/watchdog/src/watchdog.py
index 9c695ef22be..3edbe478683 100644
--- a/.ci/openvino-onnx/watchdog/src/watchdog.py
+++ b/.ci/openvino-onnx/watchdog/src/watchdog.py
@@ -486,7 +486,7 @@ class Watchdog:
self._queue_message(message, message_severity='warning', pr=pr)
elif build_delta > _BUILD_DURATION_THRESHOLD:
# CI job take too long, possibly froze - communicate failure
- message = ('ONNX CI job build #{}, for PR #{} started,'
+ message = ('ONNX CI job build #{}, for PR #{} started, '
'but did not finish in designated time of {} '
'minutes!'.format(build_number, pr_number,
str(_BUILD_DURATION_THRESHOLD.seconds / 60)))
diff --git a/.gitmodules b/.gitmodules
index 8569ecbb958..ce94901db10 100644
--- a/.gitmodules
+++ b/.gitmodules
@@ -53,3 +53,6 @@
[submodule "ncc"]
path = cmake/developer_package/ncc_naming_style/ncc
url = https://github.com/nithinn/ncc.git
+[submodule "thirdparty/onednn_gpu"]
+ path = thirdparty/onednn_gpu
+ url = https://github.com/oneapi-src/oneDNN.git
diff --git a/cmake/dependencies.cmake b/cmake/dependencies.cmake
index b4946d85d11..70562b8cc96 100644
--- a/cmake/dependencies.cmake
+++ b/cmake/dependencies.cmake
@@ -83,7 +83,6 @@ if(THREADING STREQUAL "OMP")
message(FATAL_ERROR "Intel OMP is not available on current platform")
endif()
update_deps_cache(OMP "${OMP}" "Path to OMP root folder")
- log_rpath_from_dir(OMP "${OMP}/lib")
debug_message(STATUS "intel_omp=" ${OMP})
ie_cpack_add_component(omp REQUIRED)
@@ -146,12 +145,6 @@ if(THREADING STREQUAL "TBB" OR THREADING STREQUAL "TBB_AUTO")
update_deps_cache(TBB_DIR "${TBB}/cmake" "Path to TBB cmake folder")
update_deps_cache(TBBBIND_2_4_DIR "${TBBBIND_2_4}/cmake" "Path to TBBBIND_2_4 cmake folder")
-
- if(WIN32)
- log_rpath_from_dir(TBB "${TBB}/bin")
- else ()
- log_rpath_from_dir(TBB "${TBB}/lib")
- endif()
debug_message(STATUS "tbb=" ${TBB})
endif()
@@ -242,14 +235,6 @@ if(ENABLE_OPENCV)
endif()
update_deps_cache(OpenCV_DIR "${ocv_cmake_path}" "Path to OpenCV package folder")
-
- if(WIN32)
- log_rpath_from_dir(OPENCV "${OpenCV_DIR}/../bin")
- elseif(ANDROID)
- log_rpath_from_dir(OPENCV "${OpenCV_DIR}/../../../lib")
- else()
- log_rpath_from_dir(OPENCV "${OpenCV_DIR}/../lib")
- endif()
debug_message(STATUS "opencv=" ${OPENCV})
else()
reset_deps_cache(OpenCV_DIR)
@@ -277,8 +262,8 @@ if(ENABLE_GNA)
set(GNA_HASH "cc954e67525006bf8bd353a6682e38bf208f6d74e973e0fc292850e721f17452")
endif()
if(GNA_LIBRARY_VERSION STREQUAL "GNA2")
- set(GNA_VERSION "02.00.00.1226")
- set(GNA_HASH "d5450af15c993e264c25ac4591a7dab44722e10d15fca4f222a1b84429d4e5b6")
+ set(GNA_VERSION "03.00.00.1377")
+ set(GNA_HASH "d45fb48994d8c2803a16e88e29ae48851066325b97c1c6c4a5bf4f4573d55c65")
endif()
set(FILES_TO_EXTRACT_LIST gna_${GNA_VERSION}/include)
diff --git a/cmake/developer_package/debug.cmake b/cmake/developer_package/debug.cmake
index bb4538dfe02..e14f30b4c0f 100644
--- a/cmake/developer_package/debug.cmake
+++ b/cmake/developer_package/debug.cmake
@@ -15,59 +15,3 @@ function(clean_message type)
message (FATAL_ERROR)
endif()
endfunction()
-
-file(REMOVE ${CMAKE_BINARY_DIR}/ld_library_rpath_64.txt)
-
-# log relative path to shared library that has to be used in LD_LIBRARY_PATH
-function (log_rpath_remove_top component component_remove_top lib lib_remove_top)
-
- set(top_lib_dir ${${component}})
- set(lib_dir ${lib})
-
-# debug_message(STATUS "LIB-IN=${lib} ")
-# debug_message(STATUS "TOPLIB-IN=${top_lib_dir} ")
- get_filename_component(top_lib_dir "${${component}}" DIRECTORY)
-
- if (${component_remove_top} AND ${component})
- else()
- get_filename_component(add_name "${${component}}" NAME)
- set(top_lib_dir "${top_lib_dir}/${add_name}")
- endif()
- if (${lib_remove_top} AND lib)
- get_filename_component(lib_dir ${lib} DIRECTORY)
- endif()
-
- string (REPLACE "//" "/" top_lib_dir "${top_lib_dir}")
- string (REPLACE "//" "/" lib_dir "${lib_dir}")
-
- string (REPLACE "\\\\" "/" top_lib_dir "${top_lib_dir}")
- string (REPLACE "\\\\" "/" lib_dir "${lib_dir}")
-
-# debug_message(STATUS "LIB-OUT=${lib_dir}")
-# debug_message(STATUS "TOPLIB-OUT=${top_lib_dir}")
-
- if (WIN32)
- string (TOLOWER "${top_lib_dir}" top_lib_dir)
- string (TOLOWER "${lib_dir}" lib_dir)
- endif()
-
- string (REPLACE "${top_lib_dir}" "" component_dir "${lib_dir}")
-
- set(RPATH_INFO "${component}=${component_dir}")
- debug_message(STATUS "LD_LIBRARY_RPATH: ${RPATH_INFO}")
- file(APPEND ${CMAKE_BINARY_DIR}/ld_library_rpath_64.txt "${RPATH_INFO}\n")
-endfunction()
-
-function (log_rpath_from_dir component lib_dir)
- log_rpath_remove_top("${component}" TRUE "${lib_dir}" FALSE)
-endfunction()
-
-function (log_rpath component lib_path)
- log_rpath_remove_top(${component} TRUE ${lib_path} TRUE)
-endfunction()
-
-# Just wrapping of the original message() function to make this macro known during IE build.
-# This macro is redefined (with additional checks) within the InferenceEngineConfig.cmake file.
-macro(ext_message TRACE_LEVEL)
- message(${TRACE_LEVEL} "${ARGN}")
-endmacro()
diff --git a/cmake/features.cmake b/cmake/features.cmake
index 450b0d255cc..7528b89d47d 100644
--- a/cmake/features.cmake
+++ b/cmake/features.cmake
@@ -122,7 +122,7 @@ endif()
ie_dependent_option(NGRAPH_ONNX_FRONTEND_ENABLE "Enable ONNX FrontEnd" ON "protoc_available" OFF)
ie_dependent_option(NGRAPH_PDPD_FRONTEND_ENABLE "Enable PaddlePaddle FrontEnd" ON "protoc_available" OFF)
-ie_option(IR_FRONTEND_ENABLE "Enable IR FrontEnd" ON)
+ie_option(NGRAPH_IR_FRONTEND_ENABLE "Enable IR FrontEnd" ON)
ie_dependent_option(NGRAPH_USE_PROTOBUF_LITE "Compiles and links with protobuf-lite" ON
"NGRAPH_ONNX_FRONTEND_ENABLE" OFF)
ie_dependent_option(NGRAPH_USE_SYSTEM_PROTOBUF "Use system protobuf" OFF
@@ -130,7 +130,7 @@ ie_dependent_option(NGRAPH_USE_SYSTEM_PROTOBUF "Use system protobuf" OFF
ie_dependent_option(NGRAPH_UNIT_TEST_ENABLE "Enables ngraph unit tests" ON "ENABLE_TESTS;NOT ANDROID" OFF)
ie_dependent_option(NGRAPH_UNIT_TEST_BACKENDS_ENABLE "Control the building of unit tests using backends" ON
"NGRAPH_UNIT_TEST_ENABLE" OFF)
-ie_option(NGRAPH_DEBUG_ENABLE "Enable output for NGRAPH_DEBUG statements" OFF)
+ie_option(OPENVINO_DEBUG_ENABLE "Enable output for OPENVINO_DEBUG statements" OFF)
ie_option(ENABLE_REQUIREMENTS_INSTALL "Dynamic dependencies install" ON)
# WA for ngraph python build on Windows debug
diff --git a/cmake/templates/OpenVINOConfig.cmake.in b/cmake/templates/OpenVINOConfig.cmake.in
index 14fc57b36c2..eb903e14889 100644
--- a/cmake/templates/OpenVINOConfig.cmake.in
+++ b/cmake/templates/OpenVINOConfig.cmake.in
@@ -63,6 +63,9 @@
# `OpenVINO_Frontend_PaddlePaddle_FOUND`
# OpenVINO PaddlePaddle frontend is available
#
+# `OpenVINO_Frontend_IR_FOUND`
+# OpenVINO IR frontend is available
+#
# OpenVINO version variables:
#
# `OpenVINO_VERSION_MAJOR`
@@ -169,6 +172,7 @@ set(${CMAKE_FIND_PACKAGE_NAME}_PaddlePaddle_FOUND @NGRAPH_PDPD_FRONTEND_ENABLE@)
set(${CMAKE_FIND_PACKAGE_NAME}_Frontend_ONNX_FOUND ${${CMAKE_FIND_PACKAGE_NAME}_ONNX_FOUND})
set(${CMAKE_FIND_PACKAGE_NAME}_Frontend_PaddlePaddle_FOUND ${${CMAKE_FIND_PACKAGE_NAME}_PaddlePaddle_FOUND})
+set(${CMAKE_FIND_PACKAGE_NAME}_Frontend_IR_FOUND ${${CMAKE_FIND_PACKAGE_NAME}_IR_FOUND})
# if no components specified, only Runtime is provided
if(NOT ${CMAKE_FIND_PACKAGE_NAME}_FIND_COMPONENTS)
diff --git a/cmake/templates/ngraphConfig.cmake.in b/cmake/templates/ngraphConfig.cmake.in
index a94e6b50a58..c5b467f2dd3 100644
--- a/cmake/templates/ngraphConfig.cmake.in
+++ b/cmake/templates/ngraphConfig.cmake.in
@@ -88,5 +88,6 @@ if(ngraph_onnx_importer_FOUND)
endif()
set(ngraph_paddlepaddle_frontend_FOUND ${OpenVINO_Frontend_PaddlePaddle_FOUND})
+set(ngraph_ir_frontend_FOUND ${OpenVINO_Frontend_IR_FOUND})
check_required_components(ngraph)
diff --git a/cmake/test_model_zoo.cmake b/cmake/test_model_zoo.cmake
index 580cab35ec4..00e360e3800 100644
--- a/cmake/test_model_zoo.cmake
+++ b/cmake/test_model_zoo.cmake
@@ -2,6 +2,8 @@
# SPDX-License-Identifier: Apache-2.0
#
+set_property(GLOBAL PROPERTY JOB_POOLS four_jobs=4)
+
function(ov_model_convert SRC DST OUT)
set(onnx_gen_script ${OpenVINO_SOURCE_DIR}/ngraph/test/models/onnx/onnx_prototxt_converter.py)
@@ -43,6 +45,7 @@ function(ov_model_convert SRC DST OUT)
"${SRC}/${in_file}" ${full_out_name}
DEPENDS ${onnx_gen_script} "${SRC}/${in_file}"
COMMENT "Generate ${rel_out_name}"
+ JOB_POOL four_jobs
WORKING_DIRECTORY "${model_source_dir}")
else()
add_custom_command(OUTPUT ${full_out_name}
@@ -50,6 +53,7 @@ function(ov_model_convert SRC DST OUT)
"${SRC}/${in_file}" ${full_out_name}
DEPENDS ${onnx_gen_script} "${SRC}/${in_file}"
COMMENT "Copy ${rel_out_name}"
+ JOB_POOL four_jobs
WORKING_DIRECTORY "${model_source_dir}")
endif()
list(APPEND files "${full_out_name}")
diff --git a/docs/MO_DG/prepare_model/convert_model/pytorch_specific/Convert_RNNT.md b/docs/MO_DG/prepare_model/convert_model/pytorch_specific/Convert_RNNT.md
index 31de647f379..a304a0bb6b2 100644
--- a/docs/MO_DG/prepare_model/convert_model/pytorch_specific/Convert_RNNT.md
+++ b/docs/MO_DG/prepare_model/convert_model/pytorch_specific/Convert_RNNT.md
@@ -73,19 +73,21 @@ inp = torch.randn([seq_length, batch_size, feature_length])
feature_length = torch.LongTensor([seq_length])
x_padded, x_lens = model.encoder(inp, feature_length)
torch.onnx.export(model.encoder, (inp, feature_length), "rnnt_encoder.onnx", opset_version=12,
- input_names=['input.1', '1'], dynamic_axes={'input.1': {0: 'seq_len', 1: 'batch'}})
+ input_names=['input', 'feature_length'], output_names=['x_padded', 'x_lens'],
+ dynamic_axes={'input': {0: 'seq_len', 1: 'batch'}})
symbol = torch.LongTensor([[20]])
hidden = torch.randn([2, batch_size, 320]), torch.randn([2, batch_size, 320])
g, hidden = model.prediction.forward(symbol, hidden)
torch.onnx.export(model.prediction, (symbol, hidden), "rnnt_prediction.onnx", opset_version=12,
- input_names=['input.1', '1', '2'],
- dynamic_axes={'input.1': {0: 'batch'}, '1': {1: 'batch'}, '2': {1: 'batch'}})
+ input_names=['symbol', 'hidden_in_1', 'hidden_in_2'],
+ output_names=['g', 'hidden_out_1', 'hidden_out_2'],
+ dynamic_axes={'symbol': {0: 'batch'}, 'hidden_in_1': {1: 'batch'}, 'hidden_in_2': {1: 'batch'}})
f = torch.randn([batch_size, 1, 1024])
model.joint.forward(f, g)
torch.onnx.export(model.joint, (f, g), "rnnt_joint.onnx", opset_version=12,
- input_names=['0', '1'], dynamic_axes={'0': {0: 'batch'}, '1': {0: 'batch'}})
+ input_names=['0', '1'], output_names=['result'], dynamic_axes={'0': {0: 'batch'}, '1': {0: 'batch'}})
```
```bash
@@ -97,10 +99,10 @@ After completing this step, the files `rnnt_encoder.onnx`, `rnnt_prediction.onnx
**Step 6**. Run the conversion command:
```bash
-python3 {path_to_openvino}/mo.py --input_model rnnt_encoder.onnx --input "input.1[157 1 240],1->157"
-python3 {path_to_openvino}/mo.py --input_model rnnt_prediction.onnx --input "input.1[1 1],1[2 1 320],2[2 1 320]"
+python3 {path_to_openvino}/mo.py --input_model rnnt_encoder.onnx --input "input[157 1 240],feature_length->157"
+python3 {path_to_openvino}/mo.py --input_model rnnt_prediction.onnx --input "symbol[1 1],hidden_in_1[2 1 320],hidden_in_2[2 1 320]"
python3 {path_to_openvino}/mo.py --input_model rnnt_joint.onnx --input "0[1 1 1024],1[1 1 320]"
```
Please note that hardcoded value for sequence length = 157 was taken from the MLCommons but conversion to IR preserves
network [reshapeability](../../../../IE_DG/ShapeInference.md), this means you can change input shapes manually to any value either during conversion or
-inference.
\ No newline at end of file
+inference.
diff --git a/docs/index.md b/docs/index.md
index 9ad04bfe960..7cc4eb90f7b 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -104,3 +104,9 @@ Intel® Distribution of OpenVINO™ toolkit includes the following components:
- [Intel® Media SDK](https://software.intel.com/en-us/media-sdk) (in Intel® Distribution of OpenVINO™ toolkit for Linux only)
OpenVINO™ Toolkit opensource version is available on [GitHub](https://github.com/openvinotoolkit/openvino). For building the Inference Engine from the source code, see the build instructions.
+
+
+## OpenVINO™ API 2.0
+
+The new OpenVINO™ API 2.0 was introduced to make OpenVINO™ interface more user-friendly and align OpenVINO™ with other frameworks.
+The [migration guide](@ref ov_2_0_transition_guide) should allow to simplify the process of migration application from old API to OpenVINO™ API 2.0.
diff --git a/docs/migration_ov_2_0/docs/common_inference_pipeline.md b/docs/migration_ov_2_0/docs/common_inference_pipeline.md
new file mode 100644
index 00000000000..af2dbf25304
--- /dev/null
+++ b/docs/migration_ov_2_0/docs/common_inference_pipeline.md
@@ -0,0 +1,55 @@
+# OpenVINO™ Inference Pipeline {#ov_inference_pipeline}
+
+Usually to inference network with the OpenVINO™ toolkit users need to do next steps:
+ 1. Create Core
+ 2. (Optional) Read model from the disk
+ 2.1. Configure Input and Output of the Model
+ 3. Load the Model to the Device
+ 4. Create an Inference Request
+ 5. Prepare Input
+ 6. Start Inference
+ 7. Process the Inference Results
+
+Code snippets below cover these steps and show how application code should be changed for migration to OpenVINO™ 2.0.
+
+## 1. Create Core
+
+Inference Engine API:
+
+@snippet snippets/ie_common.cpp ie:create_core
+
+OpenVINO™ 2.0 API:
+
+@snippet snippets/ov_common.cpp ov_api_2_0:create_core
+
+## 2. (Optional) Read model from the disk
+
+Inference Engine API:
+
+@snippet snippets/ie_common.cpp ie:read_model
+
+OpenVINO™ 2.0 API:
+
+@snippet snippets/ov_common.cpp ov_api_2_0:read_model
+
+### 2.1 Configure Input and Output of the Model
+
+Inference Engine API:
+
+@snippet snippets/ie_common.cpp ie:get_inputs_outputs
+
+OpenVINO™ 2.0 API:
+
+@snippet snippets/ov_common.cpp ov_api_2_0:get_inputs_outputs
+
+## 3. Load the Model to the Device
+
+Inference Engine API:
+
+@snippet snippets/ie_common.cpp ie:compile_model
+
+OpenVINO™ 2.0 API:
+
+@snippet snippets/ov_common.cpp ov_api_2_0:compile_model
+
+## 5. TBD
diff --git a/docs/migration_ov_2_0/docs/intro.md b/docs/migration_ov_2_0/docs/intro.md
new file mode 100644
index 00000000000..5d89b7aff3d
--- /dev/null
+++ b/docs/migration_ov_2_0/docs/intro.md
@@ -0,0 +1,12 @@
+# OpenVINO™ API 2.0 transition guide {#ov_2_0_transition_guide}
+
+The OpenVINO™ API 2.0 introduced in order to simplify migration from other frameworks and make the OpenVINO™ API more user-friendly.
+The list with differences between APIs below:
+
+ - OpenVINO™ API 2.0 uses tensor names or indexes to work with Inputs or Outputs, the old API works with operation names.
+ - Structures for Shapes, element types were changed.
+ - Naming style was changed. The old API uses CamelCaseStyle and OpenVINO™ API 2.0 uses snake_case for function names.
+ - Namespaces were aligned between components.
+
+Please look at next transition guides to understand how transit own application to OpenVINO™ API 2.0.
+ - [OpenVINO™ Common Inference pipeline](@ref ov_inference_pipeline)
diff --git a/docs/nGraph_DG/nGraph_debug_capabilities.md b/docs/nGraph_DG/nGraph_debug_capabilities.md
index e2ae82743c1..bda4dff150c 100644
--- a/docs/nGraph_DG/nGraph_debug_capabilities.md
+++ b/docs/nGraph_DG/nGraph_debug_capabilities.md
@@ -3,7 +3,7 @@
nGraph representation provides an API to get detailed information about the graph structure.
To receive additional messages about applied graph modifications, rebuild the nGraph library with
-the `-DNGRAPH_DEBUG_ENABLE=ON` option.
+the `-DOPENVINO_DEBUG_ENABLE=ON` option.
To visualize the nGraph function to the xDot format or to an image file, use the
`ngraph::pass::VisualizeTree` graph transformation pass:
diff --git a/docs/snippets/ie_common.cpp b/docs/snippets/ie_common.cpp
new file mode 100644
index 00000000000..6a558129243
--- /dev/null
+++ b/docs/snippets/ie_common.cpp
@@ -0,0 +1,43 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include
+
+int main() {
+ //! [ie:create_core]
+ InferenceEngine::Core core;
+ //! [ie:create_core]
+
+ //! [ie:read_model]
+ InferenceEngine::CNNNetwork network = core.ReadNetwork("model.xml");
+ //! [ie:read_model]
+
+ //! [ie:get_inputs_outputs]
+ InferenceEngine::InputsDataMap inputs = network.getInputsInfo();
+ InferenceEngine::OutputsDataMap outputs = network.getOutputsInfo();
+ //! [ie:get_inputs_outputs]
+
+ //! [ie:compile_model]
+ InferenceEngine::ExecutableNetwork exec_network = core.LoadNetwork(network, "CPU");
+ //! [ie:compile_model]
+
+ //! [ie:create_infer_request]
+ InferenceEngine::InferRequest infer_request = exec_network.CreateInferRequest();
+ //! [ie:create_infer_request]
+
+ //! [ie:get_input_tensor]
+ InferenceEngine::Blob::Ptr input_blob = infer_request.GetBlob(inputs.begin()->first);
+ // fill input blob
+ //! [ie:get_input_tensor]
+
+ //! [ie:inference]
+ infer_request.Infer();
+ //! [ie:inference]
+
+ //! [ie:get_output_tensor]
+ InferenceEngine::Blob::Ptr output_blob = infer_request.GetBlob(outputs.begin()->first);
+ // process output data
+ //! [ie:get_output_tensor]
+ return 0;
+}
diff --git a/docs/snippets/nGraphTutorial.cpp b/docs/snippets/nGraphTutorial.cpp
index 6011becf4ec..e39e783d5eb 100644
--- a/docs/snippets/nGraphTutorial.cpp
+++ b/docs/snippets/nGraphTutorial.cpp
@@ -23,12 +23,10 @@ acos0->set_argument(0, add0);
add1->set_argument(0, acos0);
add1->set_argument(1, abs0);
-// Run shape inference on the nodes
-NodeVector ops{arg0, arg1, add0, abs0, acos0, add1};
-validate_nodes_and_infer_types(ops);
-
// Create a graph with one output (add1) and four inputs (arg0, arg1)
auto ng_function = make_shared(OutputVector{add1}, ParameterVector{arg0, arg1});
+// Run shape inference on the nodes
+ng_function->validate_nodes_and_infer_types();
//! [part0]
diff --git a/docs/snippets/ov_common.cpp b/docs/snippets/ov_common.cpp
new file mode 100644
index 00000000000..7cb9e344f7c
--- /dev/null
+++ b/docs/snippets/ov_common.cpp
@@ -0,0 +1,34 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+#include
+#include
+
+int main() {
+ //! [ov_api_2_0:create_core]
+ ov::runtime::Core core;
+ //! [ov_api_2_0:create_core]
+
+ //! [ov_api_2_0:read_model]
+ std::shared_ptr network = core.read_model("model.xml");
+ //! [ov_api_2_0:read_model]
+
+ //! [ov_api_2_0:get_inputs_outputs]
+ ov::ParameterVector inputs = network->get_parameters();
+ ov::ResultVector outputs = network->get_results();
+ //! [ov_api_2_0:get_inputs_outputs]
+
+ //! [ov_api_2_0:compile_model]
+ ov::runtime::ExecutableNetwork exec_network = core.compile_model(network, "CPU");
+ //! [ov_api_2_0:compile_model]
+
+ ov::runtime::InferRequest infer_request = exec_network.create_infer_request();
+ //
+ // InferenceEngine::Blob::Ptr input_blob = infer_request.GetBlob(inputs.begin()->first);
+ // // fill input blob
+ // infer_request.Infer();
+ //
+ // InferenceEngine::Blob::Ptr output_blob = infer_request.GetBlob(outputs.begin()->first);
+ // process output data
+ return 0;
+}
diff --git a/inference-engine/cmake/vpu_dependencies.cmake b/inference-engine/cmake/vpu_dependencies.cmake
index e6ec3799a3c..00cf63344ce 100644
--- a/inference-engine/cmake/vpu_dependencies.cmake
+++ b/inference-engine/cmake/vpu_dependencies.cmake
@@ -110,8 +110,6 @@ if(ANDROID)
set(LIBUSB_INCLUDE_DIR "${LIBUSB}/include")
set(LIBUSB_LIBRARY "${LIBUSB}/libs/${ANDROID_ABI}/libusb1.0.so")
-
- log_rpath_from_dir(LIBUSB "${LIBUSB}/libs/${ANDROID_ABI}")
endif()
#
diff --git a/inference-engine/ie_bridges/python/sample/speech_sample/README.md b/inference-engine/ie_bridges/python/sample/speech_sample/README.md
index 54403416bc4..2809cc72a5f 100644
--- a/inference-engine/ie_bridges/python/sample/speech_sample/README.md
+++ b/inference-engine/ie_bridges/python/sample/speech_sample/README.md
@@ -89,15 +89,15 @@ optional arguments:
Path to an .xml file with a trained model (required if
-rg is missing).
-rg IMPORT_GNA_MODEL, --import_gna_model IMPORT_GNA_MODEL
- Read GNA model from file using path/filename provided
+ Read GNA model from file using path/filename provided
(required if -m is missing).
Options:
-h, --help Show this help message and exit.
-i INPUT, --input INPUT
- Required. Path to an input file (.ark or .npz).
+ Required. Path to an input file (.ark or .npz).
-o OUTPUT, --output OUTPUT
- Optional. Output file name to save inference results
+ Optional. Output file name to save inference results
(.ark or .npz).
-r REFERENCE, --reference REFERENCE
Optional. Read reference score file and compare
@@ -117,7 +117,8 @@ Options:
(default 16).
-sf SCALE_FACTOR, --scale_factor SCALE_FACTOR
Optional. The user-specified input scale factor for
- quantization.
+ quantization. If the network contains multiple inputs,
+ provide scale factors by separating them with commas.
-wg EXPORT_GNA_MODEL, --export_gna_model EXPORT_GNA_MODEL
Optional. Write GNA model to file using path/filename
provided.
@@ -176,27 +177,30 @@ The sample application logs each step in a standard output stream.
[ INFO ] Creating Inference Engine
[ INFO ] Reading the network: wsj_dnn5b.xml
[ INFO ] Configuring input and output blobs
-[ INFO ] Using scale factor of 2175.4322417 calculated from first utterance.
+[ INFO ] Using scale factor(s) calculated from first utterance
+[ INFO ] For input 0 using scale factor of 2175.4322418
[ INFO ] Loading the model to the plugin
[ INFO ] Starting inference in synchronous mode
[ INFO ] Utterance 0 (4k0c0301)
+[ INFO ] Output blob name: affinetransform14/Fused_Add_
[ INFO ] Frames in utterance: 1294
-[ INFO ] Total time in Infer (HW and SW): 5305.47ms
-[ INFO ] max error: 0.7051839
-[ INFO ] avg error: 0.0448387
-[ INFO ] avg rms error: 0.0582387
-[ INFO ] stdev error: 0.0371649
+[ INFO ] Total time in Infer (HW and SW): 6211.45ms
+[ INFO ] max error: 0.7051840
+[ INFO ] avg error: 0.0448388
+[ INFO ] avg rms error: 0.0582387
+[ INFO ] stdev error: 0.0371650
[ INFO ]
[ INFO ] Utterance 1 (4k0c0302)
+[ INFO ] Output blob name: affinetransform14/Fused_Add_
[ INFO ] Frames in utterance: 1005
-[ INFO ] Total time in Infer (HW and SW): 5031.53ms
+[ INFO ] Total time in Infer (HW and SW): 4742.27ms
[ INFO ] max error: 0.7575974
[ INFO ] avg error: 0.0452166
[ INFO ] avg rms error: 0.0586013
[ INFO ] stdev error: 0.0372769
-[ INFO ]
...
-[ INFO ] Total sample time: 38033.09ms
+[ INFO ] Total sample time: 40219.99ms
+[ INFO ] File result.npz was created!
[ INFO ] This sample is an API example, for any performance measurements please use the dedicated benchmark_app tool
```
diff --git a/inference-engine/ie_bridges/python/sample/speech_sample/arg_parser.py b/inference-engine/ie_bridges/python/sample/speech_sample/arg_parser.py
index 1d2ad5c7d71..d4e2b345ea2 100644
--- a/inference-engine/ie_bridges/python/sample/speech_sample/arg_parser.py
+++ b/inference-engine/ie_bridges/python/sample/speech_sample/arg_parser.py
@@ -28,8 +28,9 @@ def parse_args() -> argparse.Namespace:
args.add_argument('-bs', '--batch_size', default=1, type=int, help='Optional. Batch size 1-8 (default 1).')
args.add_argument('-qb', '--quantization_bits', default=16, type=int,
help='Optional. Weight bits for quantization: 8 or 16 (default 16).')
- args.add_argument('-sf', '--scale_factor', type=float,
- help='Optional. The user-specified input scale factor for quantization.')
+ args.add_argument('-sf', '--scale_factor', type=str,
+ help='Optional. The user-specified input scale factor for quantization. '
+ 'If the network contains multiple inputs, provide scale factors by separating them with commas.')
args.add_argument('-wg', '--export_gna_model', type=str,
help='Optional. Write GNA model to file using path/filename provided.')
args.add_argument('-we', '--export_embedded_gna_model', type=str, help=argparse.SUPPRESS)
diff --git a/inference-engine/ie_bridges/python/sample/speech_sample/speech_sample.py b/inference-engine/ie_bridges/python/sample/speech_sample/speech_sample.py
index 67601e1f379..14d2e4fa441 100755
--- a/inference-engine/ie_bridges/python/sample/speech_sample/speech_sample.py
+++ b/inference-engine/ie_bridges/python/sample/speech_sample/speech_sample.py
@@ -103,6 +103,32 @@ def get_output_layer_list(net: Union[IENetwork, ExecutableNetwork],
return [list(net.outputs.keys())[-1]]
+def parse_scale_factors(args: argparse.Namespace) -> list:
+ """Get a list of scale factors for input files"""
+ input_files = re.split(', |,', args.input)
+ scale_factors = re.split(', |,', str(args.scale_factor))
+ scale_factors = list(map(float, scale_factors))
+
+ if len(input_files) != len(scale_factors):
+ log.error(f'Incorrect command line for multiple inputs: {len(scale_factors)} scale factors provided for '
+ f'{len(input_files)} input files.')
+ sys.exit(-7)
+
+ for i, scale_factor in enumerate(scale_factors):
+ if float(scale_factor) < 0:
+ log.error(f'Scale factor for input #{i} (counting from zero) is out of range (must be positive).')
+ sys.exit(-8)
+
+ return scale_factors
+
+
+def set_scale_factors(plugin_config: dict, scale_factors: list):
+ """Set a scale factor provided for each input"""
+ for i, scale_factor in enumerate(scale_factors):
+ log.info(f'For input {i} using scale factor of {scale_factor:.7f}')
+ plugin_config[f'GNA_SCALE_FACTOR_{i}'] = str(scale_factor)
+
+
def main():
log.basicConfig(format='[ %(levelname)s ] %(message)s', level=log.INFO, stream=sys.stdout)
args = parse_args()
@@ -149,16 +175,23 @@ def main():
# Set a GNA scale factor
if args.import_gna_model:
- log.info(f'Using scale factor from the imported GNA model: {args.import_gna_model}')
- elif args.scale_factor:
- log.info(f'Using scale factor of {args.scale_factor:.7f} specified by user.')
- plugin_config['GNA_SCALE_FACTOR'] = str(args.scale_factor)
+ if args.scale_factor:
+ log.warning(f'Custom scale factor will be used for imported GNA model: {args.import_gna_model}')
+ set_scale_factors(plugin_config, parse_scale_factors(args))
+ else:
+ log.info(f'Using scale factor from the imported GNA model: {args.import_gna_model}')
else:
- utterances = read_utterance_file(args.input.split(',')[0])
- key = sorted(utterances)[0]
- scale_factor = get_scale_factor(utterances[key])
- log.info(f'Using scale factor of {scale_factor:.7f} calculated from first utterance.')
- plugin_config['GNA_SCALE_FACTOR'] = str(scale_factor)
+ if args.scale_factor:
+ set_scale_factors(plugin_config, parse_scale_factors(args))
+ else:
+ scale_factors = []
+
+ for file_name in re.split(', |,', args.input):
+ first_utterance = next(iter(read_utterance_file(file_name).values()))
+ scale_factors.append(get_scale_factor(first_utterance))
+
+ log.info('Using scale factor(s) calculated from first utterance')
+ set_scale_factors(plugin_config, scale_factors)
if args.export_embedded_gna_model:
plugin_config['GNA_FIRMWARE_MODEL_IMAGE'] = args.export_embedded_gna_model
diff --git a/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.cpp b/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.cpp
index fcd8613f444..a0763f79765 100644
--- a/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.cpp
+++ b/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.cpp
@@ -196,6 +196,10 @@ public:
versionInfo = &ExtensionDescription;
}
+ std::map getOpSets() override {
+ return {{"framework_node_ext", ngraph::OpSet()}};
+ }
+
void Unload() noexcept override {}
};
diff --git a/inference-engine/ie_bridges/python/src/openvino/offline_transformations/CMakeLists.txt b/inference-engine/ie_bridges/python/src/openvino/offline_transformations/CMakeLists.txt
index 0aa8280bc5c..bc9115229e6 100644
--- a/inference-engine/ie_bridges/python/src/openvino/offline_transformations/CMakeLists.txt
+++ b/inference-engine/ie_bridges/python/src/openvino/offline_transformations/CMakeLists.txt
@@ -59,10 +59,8 @@ add_custom_command(TARGET ${TARGET_NAME}
# ie_cpack_add_component(${PYTHON_VERSION}_dev DEPENDS ${PYTHON_COMPONENT})
install(TARGETS ${TARGET_NAME}
- RUNTIME DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/offline_transformations
- COMPONENT ${PYTHON_COMPONENT}
- LIBRARY DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/offline_transformations
- COMPONENT ${PYTHON_COMPONENT})
+ RUNTIME DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/offline_transformations COMPONENT ${PYTHON_COMPONENT}
+ LIBRARY DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/offline_transformations COMPONENT ${PYTHON_COMPONENT})
install(PROGRAMS __init__.py
DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/offline_transformations
diff --git a/inference-engine/ie_bridges/python/src/openvino/test_utils/CMakeLists.txt b/inference-engine/ie_bridges/python/src/openvino/test_utils/CMakeLists.txt
index cb071162e35..c6ae33c7951 100644
--- a/inference-engine/ie_bridges/python/src/openvino/test_utils/CMakeLists.txt
+++ b/inference-engine/ie_bridges/python/src/openvino/test_utils/CMakeLists.txt
@@ -51,4 +51,17 @@ add_custom_command(TARGET ${TARGET_NAME}
)
add_clang_format_target(${TARGET_NAME}_clang FOR_TARGETS ${TARGET_NAME}
- EXCLUDE_PATTERNS ".*\\.cxx;.*\\.pxd;.*\\.pyx")
\ No newline at end of file
+ EXCLUDE_PATTERNS ".*\\.cxx;.*\\.pxd;.*\\.pyx")
+
+# install
+
+install(TARGETS ${TARGET_NAME}
+ RUNTIME DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/test_utils
+ COMPONENT tests EXCLUDE_FROM_ALL
+ LIBRARY DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/test_utils
+ COMPONENT tests EXCLUDE_FROM_ALL)
+
+install(PROGRAMS __init__.py
+ DESTINATION ${PYTHON_BRIDGE_CPACK_PATH}/${PYTHON_VERSION}/openvino/test_utils
+ COMPONENT tests
+ EXCLUDE_FROM_ALL)
diff --git a/inference-engine/ie_bridges/python/tests/conftest.py b/inference-engine/ie_bridges/python/tests/conftest.py
index f0e5059d040..365e2f2f368 100644
--- a/inference-engine/ie_bridges/python/tests/conftest.py
+++ b/inference-engine/ie_bridges/python/tests/conftest.py
@@ -51,10 +51,44 @@ def pytest_configure(config):
)
-def create_ngraph_function(inputShape):
+def create_encoder(input_shape, levels = 4):
import ngraph as ng
- inputShape = ng.impl.PartialShape(inputShape)
- param = ng.parameter(inputShape, dtype=np.float32, name="data")
- result = ng.relu(param, name='out')
+ # input
+ input_node = ng.parameter(input_shape, np.float32, name="data")
+
+ padding_begin = padding_end = [0, 0]
+ strides = [1, 1]
+ dilations = [1, 1]
+ input_channels = [input_shape[1]]
+ last_output = input_node
+
+ # convolution layers
+ for i in range(levels):
+ input_c = input_channels[-1]
+ output_c = input_c * 2
+ conv_w = np.random.uniform(0, 1, [output_c, input_c, 5, 5]).astype(np.float32)
+ conv_node = ng.convolution(last_output, conv_w, strides, padding_begin, padding_end, dilations)
+ input_channels.append(output_c)
+ last_output = conv_node
+
+ # deconvolution layers
+ for i in range(levels):
+ input_c = input_channels[-2]
+ output_c = input_channels.pop(-1)
+ deconv_w = np.random.uniform(0, 1, [output_c, input_c, 5, 5]).astype(np.float32)
+ deconv_node = ng.convolution_backprop_data(last_output, deconv_w, strides)
+ last_output = deconv_node
+
+ # result
+ last_output.set_friendly_name("out")
+ result_node = ng.result(last_output)
+ return ng.Function(result_node, [input_node], "Encoder")
+
+
+def create_relu(input_shape):
+ import ngraph as ng
+ input_shape = ng.impl.PartialShape(input_shape)
+ param = ng.parameter(input_shape, dtype=np.float32, name="data")
+ result = ng.relu(param, name="out")
function = ng.Function(result, [param], "TestFunction")
return function
diff --git a/inference-engine/ie_bridges/python/tests/test_Blob.py b/inference-engine/ie_bridges/python/tests/test_Blob.py
index cd2a48a2724..14624fa3daa 100644
--- a/inference-engine/ie_bridges/python/tests/test_Blob.py
+++ b/inference-engine/ie_bridges/python/tests/test_Blob.py
@@ -140,10 +140,11 @@ def test_set_shape():
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_blob_set_shape_after_async_infer():
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function([ng.Dimension(0,5), ng.Dimension(4), ng.Dimension(20), ng.Dimension(20)])
+ function = create_encoder([1, 4, 20, 20])
net = ng.function_to_cnn(function)
+ net.reshape({"data": [(1, 5), 4, 20, 20]})
ie_core = IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE")
@@ -152,3 +153,4 @@ def test_blob_set_shape_after_async_infer():
with pytest.raises(RuntimeError) as e:
request.input_blobs['data'].set_shape([3, 4, 20, 20])
assert "REQUEST_BUSY" in str(e.value)
+ request.wait()
diff --git a/inference-engine/ie_bridges/python/tests/test_CDataPtr.py b/inference-engine/ie_bridges/python/tests/test_CDataPtr.py
index 4969aba4a5c..838c8c8f282 100644
--- a/inference-engine/ie_bridges/python/tests/test_CDataPtr.py
+++ b/inference-engine/ie_bridges/python/tests/test_CDataPtr.py
@@ -61,9 +61,9 @@ def test_initialized(device):
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_is_dynamic():
- from conftest import create_ngraph_function
+ from conftest import create_relu
import ngraph as ng
- function = create_ngraph_function([-1, 3, 20, 20])
+ function = create_relu([-1, 3, 20, 20])
net = ng.function_to_cnn(function)
ie = IECore()
ie.register_plugin("templatePlugin", "TEMPLATE")
diff --git a/inference-engine/ie_bridges/python/tests/test_DataPtr.py b/inference-engine/ie_bridges/python/tests/test_DataPtr.py
index 40ae28b2001..27b6fec64ed 100644
--- a/inference-engine/ie_bridges/python/tests/test_DataPtr.py
+++ b/inference-engine/ie_bridges/python/tests/test_DataPtr.py
@@ -48,9 +48,9 @@ def test_initialized():
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_is_dynamic():
- from conftest import create_ngraph_function
+ from conftest import create_relu
import ngraph as ng
- function = create_ngraph_function([-1, 3, 20, 20])
+ function = create_relu([-1, 3, 20, 20])
net = ng.function_to_cnn(function)
assert net.input_info["data"].input_data.is_dynamic
assert net.outputs["out"].is_dynamic
diff --git a/inference-engine/ie_bridges/python/tests/test_IENetwork.py b/inference-engine/ie_bridges/python/tests/test_IENetwork.py
index 607c8296f4b..7a6daac7214 100644
--- a/inference-engine/ie_bridges/python/tests/test_IENetwork.py
+++ b/inference-engine/ie_bridges/python/tests/test_IENetwork.py
@@ -166,9 +166,9 @@ def test_reshape():
([1, 3, -1, 25], [1, 3, 22, -1])
])
def test_reshape_with_partial_shape(device, shape, p_shape):
- from conftest import create_ngraph_function
+ from conftest import create_relu
import ngraph as ng
- function = create_ngraph_function(shape)
+ function = create_relu(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
changedFunction = ng.function_from_cnn(net)
@@ -185,9 +185,9 @@ def test_reshape_with_partial_shape(device, shape, p_shape):
@pytest.mark.ngraph_dependent_test
def test_incorrect_reshape(device):
- from conftest import create_ngraph_function
+ from conftest import create_relu
import ngraph as ng
- function = create_ngraph_function([1, 3, 22, 22])
+ function = create_relu([1, 3, 22, 22])
net = ng.function_to_cnn(function)
with pytest.raises(ValueError) as e:
net.reshape({"data": [(2, 4, 6), 3, 22, 22]})
@@ -287,9 +287,9 @@ def test_tensor_names():
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_create_two_exec_net():
- from conftest import create_ngraph_function
+ from conftest import create_relu
import ngraph as ng
- function = create_ngraph_function([ng.Dimension(0,5), ng.Dimension(4), ng.Dimension(20), ng.Dimension(20)])
+ function = create_relu([ng.Dimension(0,5), ng.Dimension(4), ng.Dimension(20), ng.Dimension(20)])
net = ng.function_to_cnn(function)
ie_core = IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
diff --git a/inference-engine/ie_bridges/python/tests/test_InferRequest.py b/inference-engine/ie_bridges/python/tests/test_InferRequest.py
index a1ea7ce8bce..f82cbf5327f 100644
--- a/inference-engine/ie_bridges/python/tests/test_InferRequest.py
+++ b/inference-engine/ie_bridges/python/tests/test_InferRequest.py
@@ -589,13 +589,13 @@ def test_query_state_write_buffer(device, input_shape, data_type, mode):
@pytest.mark.parametrize("shape, p_shape, ref_shape", [
([1, 4, 20, 20], [-1, 4, 20, 20], [5, 4, 20, 20]),
([1, 4, 20, 20], [(0,5), 4, 20, 20], [3, 4, 20, 20]),
- ([1, 4, 20, 20], [(3,5), 3, 20, 20], [2, 4, 20, 20]),
- ([1, 4, 20, 20], [(3,5), 3, 20, 20], [6, 4, 20, 20]),
+ ([1, 4, 20, 20], [(3,5), 4, 20, 20], [2, 4, 20, 20]),
+ ([1, 4, 20, 20], [(3,5), 4, 20, 20], [6, 4, 20, 20]),
])
def test_infer_dynamic_network_with_set_shape(shape, p_shape, ref_shape):
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function(shape)
+ function = create_encoder(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
ie_core = ie.IECore()
@@ -616,13 +616,13 @@ def test_infer_dynamic_network_with_set_shape(shape, p_shape, ref_shape):
@pytest.mark.parametrize("shape, p_shape, ref_shape", [
([1, 4, 20, 20], [-1, 4, 20, 20], [5, 4, 20, 20]),
([1, 4, 20, 20], [(0,5), 4, 20, 20], [3, 4, 20, 20]),
- ([1, 4, 20, 20], [(3,5), 3, 20, 20], [2, 4, 20, 20]),
- ([1, 4, 20, 20], [(3,5), 3, 20, 20], [6, 4, 20, 20]),
+ ([1, 4, 20, 20], [(3,5), 4, 20, 20], [2, 4, 20, 20]),
+ ([1, 4, 20, 20], [(3,5), 4, 20, 20], [6, 4, 20, 20]),
])
def test_infer_dynamic_network_without_set_shape(shape, p_shape, ref_shape):
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function(shape)
+ function = create_encoder(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
ie_core = ie.IECore()
@@ -642,13 +642,13 @@ def test_infer_dynamic_network_without_set_shape(shape, p_shape, ref_shape):
@pytest.mark.parametrize("shape, p_shape, ref_shape", [
([1, 4, 20, 20], [-1, 4, 20, 20], [5, 4, 20, 20]),
([1, 4, 20, 20], [(0,5), 4, 20, 20], [3, 4, 20, 20]),
- ([1, 4, 20, 20], [(3,5), 3, 20, 20], [2, 4, 20, 20]),
- ([1, 4, 20, 20], [(3,5), 3, 20, 20], [6, 4, 20, 20]),
+ ([1, 4, 20, 20], [(3,5), 4, 20, 20], [2, 4, 20, 20]),
+ ([1, 4, 20, 20], [(3,5), 4, 20, 20], [6, 4, 20, 20]),
])
def test_infer_dynamic_network_with_set_blob(shape, p_shape, ref_shape):
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function(shape)
+ function = create_encoder(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
ie_core = ie.IECore()
@@ -670,11 +670,11 @@ def test_infer_dynamic_network_with_set_blob(shape, p_shape, ref_shape):
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_infer_dynamic_network_twice():
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
shape, p_shape = [1, 4, 20, 20], [(0,5), 4, 20, 20]
ref_shape1, ref_shape2 = [2, 4, 20, 20], [3, 4, 20, 20]
- function = create_ngraph_function(shape)
+ function = create_encoder(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
ie_core = ie.IECore()
@@ -692,11 +692,11 @@ def test_infer_dynamic_network_twice():
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_infer_dynamic_network_with_set_blob_twice():
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
shape, p_shape = [1, 4, 20, 20], [(0,5), 4, 20, 20]
ref_shape1, ref_shape2 = [2, 4, 20, 20], [3, 4, 20, 20]
- function = create_ngraph_function(shape)
+ function = create_encoder(shape)
net = ng.function_to_cnn(function)
net.reshape({"data": p_shape})
ie_core = ie.IECore()
@@ -723,14 +723,14 @@ def test_infer_dynamic_network_with_set_blob_twice():
@pytest.mark.template_plugin
@pytest.mark.parametrize("shapes", [
([3, 4, 20, 20], [3, 4, 20, 20], [3, 4, 20, 20]),
- ([3, 4, 20, 20], [3, 6, 20, 20], [3, 8, 20, 20]),
+ ([3, 4, 20, 20], [3, 4, 28, 28], [3, 4, 45, 45]),
])
def test_async_infer_dynamic_network_3_requests(shapes):
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function([3, 4, 20, 20])
+ function = create_encoder([3, 4, 20, 20])
net = ng.function_to_cnn(function)
- net.reshape({"data": [3, (2, 10), 20, 20]})
+ net.reshape({"data": [3, 4, (20, 50), (20, 50)]})
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE", num_requests=3)
@@ -745,9 +745,9 @@ def test_async_infer_dynamic_network_3_requests(shapes):
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_set_blob_with_incorrect_name():
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function([4, 4, 20, 20])
+ function = create_encoder([4, 4, 20, 20])
net = ng.function_to_cnn(function)
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
@@ -763,9 +763,9 @@ def test_set_blob_with_incorrect_name():
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_set_blob_with_incorrect_size():
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function([4, 4, 20, 20])
+ function = create_encoder([4, 4, 20, 20])
net = ng.function_to_cnn(function)
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
@@ -773,6 +773,7 @@ def test_set_blob_with_incorrect_size():
tensor_desc = exec_net.requests[0].input_blobs["data"].tensor_desc
tensor_desc.dims = [tensor_desc.dims[0]*2, 4, 20, 20]
blob = ie.Blob(tensor_desc)
+ print(exec_net.requests[0].output_blobs)
with pytest.raises(RuntimeError) as e:
exec_net.requests[0].set_blob("data", blob)
assert f"Input blob size is not equal network input size" in str(e.value)
@@ -784,10 +785,11 @@ def test_set_blob_with_incorrect_size():
@pytest.mark.ngraph_dependent_test
@pytest.mark.template_plugin
def test_set_blob_after_async_infer():
- from conftest import create_ngraph_function
+ from conftest import create_encoder
import ngraph as ng
- function = create_ngraph_function([ng.Dimension(0,5), ng.Dimension(4), ng.Dimension(20), ng.Dimension(20)])
+ function = create_encoder([1, 4, 20, 20])
net = ng.function_to_cnn(function)
+ net.reshape({"data": [(0, 5), 4, 20, 20]})
ie_core = ie.IECore()
ie_core.register_plugin("templatePlugin", "TEMPLATE")
exec_net = ie_core.load_network(net, "TEMPLATE")
@@ -799,3 +801,4 @@ def test_set_blob_after_async_infer():
with pytest.raises(RuntimeError) as e:
request.set_blob("data", blob)
assert "REQUEST_BUSY" in str(e.value)
+ request.wait()
diff --git a/inference-engine/ie_bridges/python/tests/test_NGraph.py b/inference-engine/ie_bridges/python/tests/test_NGraph.py
index 139d132eb0f..13d2061ecbb 100644
--- a/inference-engine/ie_bridges/python/tests/test_NGraph.py
+++ b/inference-engine/ie_bridges/python/tests/test_NGraph.py
@@ -6,14 +6,14 @@ import ngraph as ng
from ngraph.impl.op import Parameter
from ngraph.impl import Function, Shape, Type
-from conftest import model_path, create_ngraph_function
+from conftest import model_path, create_relu
test_net_xml, test_net_bin = model_path()
def test_create_IENetwork_from_nGraph():
- func = create_ngraph_function([1, 3, 22, 22])
+ func = create_relu([1, 3, 22, 22])
caps = Function.to_capsule(func)
cnnNetwork = IENetwork(caps)
assert cnnNetwork != None
@@ -23,7 +23,7 @@ def test_create_IENetwork_from_nGraph():
def test_get_IENetwork_from_nGraph():
- func = create_ngraph_function([1, 3, 22, 22])
+ func = create_relu([1, 3, 22, 22])
caps = Function.to_capsule(func)
cnnNetwork = IENetwork(caps)
assert cnnNetwork != None
diff --git a/inference-engine/samples/benchmark_app/CMakeLists.txt b/inference-engine/samples/benchmark_app/CMakeLists.txt
index b37495e5e43..e3412774f27 100644
--- a/inference-engine/samples/benchmark_app/CMakeLists.txt
+++ b/inference-engine/samples/benchmark_app/CMakeLists.txt
@@ -2,11 +2,46 @@
# SPDX-License-Identifier: Apache-2.0
#
+set(TARGET_NAME "benchmark_app")
+
file (GLOB SRC ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp)
file (GLOB HDR ${CMAKE_CURRENT_SOURCE_DIR}/*.hpp)
-ie_add_sample(NAME benchmark_app
+ie_add_sample(NAME ${TARGET_NAME}
SOURCES ${SRC}
HEADERS ${HDR}
DEPENDENCIES format_reader ie_samples_utils
OPENCV_DEPENDENCIES core)
+
+find_package(OpenCL)
+
+find_path(OpenCL_HPP_INCLUDE_DIR
+ NAMES
+ CL/cl2.hpp OpenCL/cl2.hpp
+ HINTS
+ ${opencl_root_hints}
+ ENV "PROGRAMFILES(X86)"
+ ENV AMDAPPSDKROOT
+ ENV INTELOCLSDKROOT
+ ENV NVSDKCOMPUTE_ROOT
+ ENV CUDA_PATH
+ ENV ATISTREAMSDKROOT
+ ENV OCL_ROOT
+ PATH_SUFFIXES
+ include
+ OpenCL/common/inc
+ "AMD APP/include")
+
+if(OPENCL_HEADERS_DIR)
+ # Use OpenCL CPP headers from sources if present
+ set(OpenCL_HEADERS OPENCL_HEADERS_DIR)
+elseif(OpenCL_HPP_INCLUDE_DIR)
+ # Append OpenCL CPP headers to C headers and use both
+ set(OpenCL_HEADERS OpenCL_INCLUDE_DIR OpenCL_HPP_INCLUDE_DIR)
+endif()
+
+if(OpenCL_FOUND AND OpenCL_HEADERS)
+ target_link_libraries(${TARGET_NAME} PRIVATE OpenCL::OpenCL)
+ target_include_directories(${TARGET_NAME} PRIVATE ${OpenCL_HEADERS})
+ target_compile_definitions(${TARGET_NAME} PRIVATE HAVE_GPU_DEVICE_MEM_SUPPORT)
+endif()
diff --git a/inference-engine/samples/benchmark_app/benchmark_app.hpp b/inference-engine/samples/benchmark_app/benchmark_app.hpp
index c062cee1960..6395db4ff29 100644
--- a/inference-engine/samples/benchmark_app/benchmark_app.hpp
+++ b/inference-engine/samples/benchmark_app/benchmark_app.hpp
@@ -4,6 +4,10 @@
#pragma once
+#if defined(HAVE_GPU_DEVICE_MEM_SUPPORT)
+# define HAVE_DEVICE_MEM_SUPPORT
+#endif
+
#include
#include
@@ -132,6 +136,12 @@ static const char progress_message[] =
// @brief message for performance counters option
static const char pc_message[] = "Optional. Report performance counters.";
+#ifdef HAVE_DEVICE_MEM_SUPPORT
+// @brief message for switching memory allocation type option
+static const char use_device_mem_message[] =
+ "Optional. Switch between host and device memory allocation for input and output buffers.";
+#endif
+
#ifdef USE_OPENCV
// @brief message for load config option
static const char load_config_message[] =
@@ -266,6 +276,11 @@ DEFINE_bool(progress, false, progress_message);
/// @brief Define flag for showing performance counters
DEFINE_bool(pc, false, pc_message);
+#ifdef HAVE_DEVICE_MEM_SUPPORT
+/// @brief Define flag for switching beetwen host and device memory allocation for input and output buffers
+DEFINE_bool(use_device_mem, false, use_device_mem_message);
+#endif
+
#ifdef USE_OPENCV
/// @brief Define flag for loading configuration file
DEFINE_string(load_config, "", load_config_message);
@@ -339,6 +354,9 @@ static void showUsage() {
std::cout << " -nthreads \"\" " << infer_num_threads_message << std::endl;
std::cout << " -enforcebf16= " << enforce_bf16_message << std::endl;
std::cout << " -pin \"YES\"/\"HYBRID_AWARE\"/\"NO\"/\"NUMA\" " << infer_threads_pinning_message << std::endl;
+#ifdef HAVE_DEVICE_MEM_SUPPORT
+ std::cout << " -use_device_mem " << use_device_mem_message << std::endl;
+#endif
std::cout << std::endl << " Statistics dumping options:" << std::endl;
std::cout << " -report_type \"\" " << report_type_message << std::endl;
std::cout << " -report_folder " << report_folder_message << std::endl;
diff --git a/inference-engine/samples/benchmark_app/infer_request_wrap.hpp b/inference-engine/samples/benchmark_app/infer_request_wrap.hpp
index 5e15f597e7e..dd10a28eb7a 100644
--- a/inference-engine/samples/benchmark_app/infer_request_wrap.hpp
+++ b/inference-engine/samples/benchmark_app/infer_request_wrap.hpp
@@ -65,6 +65,10 @@ public:
return _request.GetBlob(name);
}
+ void setBlob(const std::string& name, const InferenceEngine::Blob::Ptr& data) {
+ _request.SetBlob(name, data);
+ }
+
double getExecutionTimeInMilliseconds() const {
auto execTime = std::chrono::duration_cast(_endTime - _startTime);
return static_cast(execTime.count()) * 0.000001;
diff --git a/inference-engine/samples/benchmark_app/main.cpp b/inference-engine/samples/benchmark_app/main.cpp
index 6c643d45486..9120ce7136e 100644
--- a/inference-engine/samples/benchmark_app/main.cpp
+++ b/inference-engine/samples/benchmark_app/main.cpp
@@ -21,6 +21,7 @@
#include "infer_request_wrap.hpp"
#include "inputs_filling.hpp"
#include "progress_bar.hpp"
+#include "remote_blobs_filling.hpp"
#include "statistics_report.hpp"
#include "utils.hpp"
@@ -592,7 +593,16 @@ int main(int argc, char* argv[]) {
next_step();
InferRequestsQueue inferRequestsQueue(exeNetwork, nireq);
- fillBlobs(inputFiles, batchSize, app_inputs_info, inferRequestsQueue.requests);
+ if (isFlagSetInCommandLine("use_device_mem")) {
+ if (device_name.find("GPU") == 0)
+ ::gpu::fillRemoteBlobs(inputFiles, batchSize, app_inputs_info, inferRequestsQueue.requests, exeNetwork);
+ else if (device_name.find("CPU") == 0)
+ fillBlobs(inputFiles, batchSize, app_inputs_info, inferRequestsQueue.requests);
+ else
+ IE_THROW() << "Requested device doesn't support `use_device_mem` option.";
+ } else {
+ fillBlobs(inputFiles, batchSize, app_inputs_info, inferRequestsQueue.requests);
+ }
// ----------------- 10. Measuring performance
// ------------------------------------------------------------------
diff --git a/inference-engine/samples/benchmark_app/remote_blobs_filling.cpp b/inference-engine/samples/benchmark_app/remote_blobs_filling.cpp
new file mode 100644
index 00000000000..dc6d9fbf34a
--- /dev/null
+++ b/inference-engine/samples/benchmark_app/remote_blobs_filling.cpp
@@ -0,0 +1,140 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "remote_blobs_filling.hpp"
+
+#include
+#include
+#include
+#include
+
+namespace gpu {
+
+template
+using uniformDistribution = typename std::conditional<
+ std::is_floating_point::value,
+ std::uniform_real_distribution,
+ typename std::conditional::value, std::uniform_int_distribution, void>::type>::type;
+
+template
+void fillBufferRandom(void* inputBuffer,
+ size_t elementsNum,
+ T rand_min = std::numeric_limits::min(),
+ T rand_max = std::numeric_limits::max()) {
+ std::mt19937 gen(0);
+ uniformDistribution distribution(rand_min, rand_max);
+ auto inputBufferData = static_cast(inputBuffer);
+ for (size_t i = 0; i < elementsNum; i++) {
+ inputBufferData[i] = static_cast(distribution(gen));
+ }
+}
+
+void fillBuffer(void* inputBuffer, size_t elementsNum, InferenceEngine::Precision precision) {
+ if (precision == InferenceEngine::Precision::FP32) {
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::FP16) {
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::I32) {
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::I64) {
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::U8) {
+ // uniform_int_distribution is not allowed in the C++17
+ // standard and vs2017/19
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::I8) {
+ // uniform_int_distribution is not allowed in the C++17 standard
+ // and vs2017/19
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::U16) {
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::I16) {
+ fillBufferRandom(inputBuffer, elementsNum);
+ } else if (precision == InferenceEngine::Precision::BOOL) {
+ fillBufferRandom(inputBuffer, elementsNum, 0, 1);
+ } else {
+ IE_THROW() << "Requested precision is not supported";
+ }
+}
+
+size_t getBytesPerElement(InferenceEngine::Precision precision) {
+ switch (precision) {
+ case InferenceEngine::Precision::FP32:
+ return 4;
+ case InferenceEngine::Precision::FP16:
+ return 2;
+ case InferenceEngine::Precision::I32:
+ return 4;
+ case InferenceEngine::Precision::I64:
+ return 8;
+ case InferenceEngine::Precision::U8:
+ return 1;
+ case InferenceEngine::Precision::I8:
+ return 1;
+ case InferenceEngine::Precision::U16:
+ return 2;
+ case InferenceEngine::Precision::I16:
+ return 2;
+ case InferenceEngine::Precision::BOOL:
+ return 1;
+ default:
+ IE_THROW() << "Requested precision is not supported";
+ }
+}
+
+void fillRemoteBlobs(const std::vector& inputFiles,
+ const size_t& batchSize,
+ benchmark_app::InputsInfo& app_inputs_info,
+ std::vector requests,
+ const InferenceEngine::ExecutableNetwork& exeNetwork) {
+#ifdef HAVE_DEVICE_MEM_SUPPORT
+ slog::info << "Device memory will be used for input and output blobs" << slog::endl;
+ if (inputFiles.size()) {
+ slog::warn << "Device memory supports only random data at this moment, input images will be ignored"
+ << slog::endl;
+ }
+ auto context = exeNetwork.GetContext();
+ auto oclContext = std::dynamic_pointer_cast(context)->get();
+ auto oclInstance = std::make_shared(oclContext);
+
+ auto setShared = [&](size_t requestId,
+ const std::string name,
+ const InferenceEngine::TensorDesc& desc,
+ bool fillRandom = false) {
+ cl_int err;
+ auto inputDims = desc.getDims();
+ auto elementsNum = std::accumulate(begin(inputDims), end(inputDims), 1, std::multiplies());
+ auto inputSize = elementsNum * getBytesPerElement(desc.getPrecision());
+
+ cl::Buffer sharedBuffer =
+ cl::Buffer(oclInstance->_context, CL_MEM_READ_WRITE, (cl::size_type)inputSize, NULL, &err);
+
+ if (fillRandom) {
+ void* mappedPtr = oclInstance->_queue.enqueueMapBuffer(sharedBuffer,
+ CL_TRUE,
+ CL_MEM_READ_WRITE,
+ 0,
+ (cl::size_type)inputSize);
+ fillBuffer(mappedPtr, elementsNum, desc.getPrecision());
+ oclInstance->_queue.enqueueUnmapMemObject(sharedBuffer, mappedPtr);
+ }
+
+ InferenceEngine::Blob::Ptr sharedBlob = InferenceEngine::gpu::make_shared_blob(desc, context, sharedBuffer);
+
+ requests.at(requestId)->setBlob(name, sharedBlob);
+ };
+
+ for (size_t requestId = 0; requestId < requests.size(); requestId++) {
+ for (auto& item : exeNetwork.GetInputsInfo())
+ setShared(requestId, item.first, item.second->getTensorDesc(), true);
+
+ for (auto& item : exeNetwork.GetOutputsInfo())
+ setShared(requestId, item.first, item.second->getTensorDesc());
+ }
+#else
+ IE_THROW() << "Device memory requested for GPU device, but OpenCL was not linked";
+#endif
+}
+
+} // namespace gpu
diff --git a/inference-engine/samples/benchmark_app/remote_blobs_filling.hpp b/inference-engine/samples/benchmark_app/remote_blobs_filling.hpp
new file mode 100644
index 00000000000..66e2b1b2c66
--- /dev/null
+++ b/inference-engine/samples/benchmark_app/remote_blobs_filling.hpp
@@ -0,0 +1,64 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#if defined(HAVE_GPU_DEVICE_MEM_SUPPORT)
+# define HAVE_DEVICE_MEM_SUPPORT
+# include
+#endif
+
+#include
+
+#include "infer_request_wrap.hpp"
+#include "utils.hpp"
+
+namespace gpu {
+
+#ifdef HAVE_DEVICE_MEM_SUPPORT
+struct OpenCL {
+ cl::Context _context;
+ cl::Device _device;
+ cl::CommandQueue _queue;
+
+ explicit OpenCL(std::shared_ptr> media_api_context_properties = nullptr) {
+ // get Intel GPU OCL device, create context and queue
+ {
+ std::vector devices;
+ std::vector platforms;
+ const unsigned int refVendorID = 0x8086;
+
+ cl::Platform::get(&platforms);
+ for (auto& p : platforms) {
+ p.getDevices(CL_DEVICE_TYPE_GPU, &devices);
+ for (auto& d : devices) {
+ if (refVendorID == d.getInfo()) {
+ _device = d;
+ _context = cl::Context(_device);
+ break;
+ }
+ }
+ }
+
+ cl_command_queue_properties props = CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE;
+ _queue = cl::CommandQueue(_context, _device, props);
+ }
+ }
+
+ explicit OpenCL(cl_context context) {
+ // user-supplied context handle
+ _context = cl::Context(context, true);
+ _device = cl::Device(_context.getInfo()[0].get(), true);
+
+ cl_command_queue_properties props = CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE;
+ _queue = cl::CommandQueue(_context, _device, props);
+ }
+};
+#endif
+
+void fillRemoteBlobs(const std::vector& inputFiles,
+ const size_t& batchSize,
+ benchmark_app::InputsInfo& app_inputs_info,
+ std::vector requests,
+ const InferenceEngine::ExecutableNetwork& exeNetwork);
+
+} // namespace gpu
diff --git a/inference-engine/scripts/dependencies.bat b/inference-engine/scripts/dependencies.bat
deleted file mode 100644
index 5241d428d18..00000000000
--- a/inference-engine/scripts/dependencies.bat
+++ /dev/null
@@ -1,96 +0,0 @@
-@echo off
-
-:: Copyright (C) 2018-2021 Intel Corporation
-:: SPDX-License-Identifier: Apache-2.0
-
-setlocal enabledelayedexpansion
-
-for /f "delims=" %%x in (dependencies_64.txt) do (set "%%x")
-
-for %%A in ("%MKL%") do set MKL_FILENAME=%%~nxA
-for %%A in ("%OMP%") do set OMP_FILENAME=%%~nxA
-for %%A in ("%MYRIAD%") do set MYRIAD_FILENAME=%%~nxA
-for %%A in ("%GNA%") do set GNA_FILENAME=%%~nxA
-for %%A in ("%OPENCV%") do set OPENCV_FILENAME=%%~nxA
-for %%A in ("%HDDL%") do set HDDL_FILENAME=%%~nxA
-for %%A in ("%VPU_FIRMWARE_MA2X8X%") do set VPU_FIRMWARE_MA2X8X_FILENAME=%%~nxA
-for %%A in ("%TBB%") do set TBB_FILENAME=%%~nxA
-
-call :DownloadFile MKL %MKL%
-call :DownloadFile OMP %OMP%
-call :DownloadFile MYRIAD %MYRIAD%
-call :DownloadFile GNA %GNA%
-call :DownloadFile OPENCV %OPENCV%
-call :DownloadFile HDDL %HDDL%
-call :DownloadFile VPU_FIRMWARE_MA2X8X %VPU_FIRMWARE_MA2X8X%
-call :DownloadFile TBB %TBB%
-
-for /f "delims=" %%x in (ld_library_rpath_64.txt) do (set "%%x")
-
-set PATH=%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%;%PATH%
-set PATH=%DL_SDK_TEMP%\test_dependencies\MKL\%MKL_FILENAME%%MKL%;%PATH%
-set PATH=%DL_SDK_TEMP%\test_dependencies\OMP\%OMP_FILENAME%%OMP%;%PATH%
-set PATH=%DL_SDK_TEMP%\test_dependencies\GNA\%GNA_FILENAME%%GNA%;%PATH%
-set PATH=%DL_SDK_TEMP%\test_dependencies\OPENCV\%OPENCV_FILENAME%%OPENCV%;%PATH%
-set PATH=%DL_SDK_TEMP%\test_dependencies\TBB\%TBB_FILENAME%%TBB%;%PATH%
-
-set PATH=%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%;%PATH%
-
-if not "%MYRIAD%"=="" (
- if exist "%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%\mvnc" (
- echo xcopy.exe "%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%" intel64 /S /I /Y /R
- xcopy.exe "%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%" intel64 /S /I /Y /R
- )
-
- if exist "%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%\..\bin\mvnc" (
- echo xcopy.exe "%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%\..\bin\*" intel64 /S /I /Y /R
- xcopy.exe "%DL_SDK_TEMP%\test_dependencies\MYRIAD\%MYRIAD_FILENAME%%MYRIAD%\..\bin\*" intel64 /S /I /Y /R
- )
-)
-
-if not "%VPU_FIRMWARE_MA2X8X%"=="" (
- if exist "%DL_SDK_TEMP%\test_dependencies\VPU\%VPU_FIRMWARE_MA2X8X_FILENAME%" (
- echo xcopy.exe "%DL_SDK_TEMP%\test_dependencies\VPU\%VPU_FIRMWARE_MA2X8X_FILENAME%\*" intel64 /S /I /Y /R
- xcopy.exe "%DL_SDK_TEMP%\test_dependencies\VPU\%VPU_FIRMWARE_MA2X8X_FILENAME%\*" intel64 /S /I /Y /R
- )
-)
-
-set PATH=%DL_SDK_TEMP%\test_dependencies\HDDL\%HDDL_FILENAME%%HDDL%\..\bin;%PATH%
-
-if not "%HDDL%"=="" (
- set HDDL_INSTALL_DIR=%DL_SDK_TEMP%\test_dependencies\HDDL\%HDDL_FILENAME%%HDDL%\..
- if exist "%DL_SDK_TEMP%\test_dependencies\VPU\%VPU_FIRMWARE_MA2X8X_FILENAME%" (
- echo xcopy.exe "%DL_SDK_TEMP%\test_dependencies\VPU\%VPU_FIRMWARE_MA2X8X_FILENAME%\*" %HDDL_INSTALL_DIR%\lib /S /I /Y /R
- xcopy.exe "%DL_SDK_TEMP%\test_dependencies\VPU\%VPU_FIRMWARE_MA2X8X_FILENAME%\*" "%HDDL_INSTALL_DIR%\lib" /S /I /Y /R
- )
-)
-
-echo PATH=%PATH%
-
-endlocal & set PATH=%PATH%
-
-exit /B %ERRORLEVEL%
-
-:DownloadFile
-set DEPENDENCY=%~1
-set DEPENDENCY_URL=%~2
-set DEPENDENCY_FILE=%~nx2
-set DEPENDENCY_EXT=%~x2
-
-if not "%DEPENDENCY_URL%"=="" (
- if not exist "%DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\%DEPENDENCY_FILE%" (
- mkdir "%DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\%DEPENDENCY_FILE%"
- for /L %%a in (1,1,10) do (
- powershell -command "[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12; iwr -outf '%DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\_%DEPENDENCY_FILE%' %DEPENDENCY_URL%"
- call "C:\Program Files\7-Zip\7z.exe" x -y %DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\_%DEPENDENCY_FILE% -o%DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\%DEPENDENCY_FILE%
- if !ERRORLEVEL! equ 0 goto :DownloadFileContinue
- timeout /T 15
- )
- )
-)
-goto:eof
-
-:DownloadFileContinue
-if "%DEPENDENCY_EXT%" == ".txz" call "C:\Program Files\7-Zip\7z.exe" x -y %DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\%DEPENDENCY_FILE%\_%DEPENDENCY_FILE:txz=tar% -o%DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\%DEPENDENCY_FILE%
-del "%DL_SDK_TEMP%\test_dependencies\%DEPENDENCY%\_%DEPENDENCY_FILE%" /F /Q
-goto:eof
diff --git a/inference-engine/scripts/dependencies.sh b/inference-engine/scripts/dependencies.sh
deleted file mode 100755
index 640ed7e9947..00000000000
--- a/inference-engine/scripts/dependencies.sh
+++ /dev/null
@@ -1,68 +0,0 @@
-#!/bin/bash
-
-# Copyright (C) 2018-2021 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-if [ "$1" = "" ]; then
- dep_arch=64
- else
- dep_arch=$1
-fi
-
-item_path=""
-add_path() {
- component=$1
- item_path=""
- echo "Read file: dependencies_${dep_arch}.txt"
- grep_component="\b${component}\b"
-
- if [[ $(grep -m 1 "$grep_component" "dependencies_${dep_arch}.txt") ]];then
- archive_path=$(grep -m 1 "$grep_component" "dependencies_${dep_arch}.txt" | sed -E "s/${component}=//g")
- library_rpath=$(grep -m 1 "$grep_component" "ld_library_rpath_${dep_arch}.txt" | sed -E "s/${component}=//g")
- filename=$(basename "$archive_path")
- if [[ (! -d "$DL_SDK_TEMP/test_dependencies/$component/$filename") ||
- (-d "$DL_SDK_TEMP/test_dependencies/$component/$filename" &&
- ! $(ls -A "$DL_SDK_TEMP/test_dependencies/$component/$filename")) ]]; then
- mkdir -p "$DL_SDK_TEMP/test_dependencies/$component/$filename"
- wget -q "$archive_path" -O "$DL_SDK_TEMP/test_dependencies/$filename"
- if [[ $filename == *.zip ]]; then
- unzip "$DL_SDK_TEMP/test_dependencies/$filename" -d "$DL_SDK_TEMP/test_dependencies/$component/$filename"
- elif [[ $filename == *.7z ]]; then
- 7za x -y "$DL_SDK_TEMP/test_dependencies/$filename" -o "$DL_SDK_TEMP/test_dependencies/$component/$filename"
- else
- tar xf "$DL_SDK_TEMP/test_dependencies/$filename" -C "$DL_SDK_TEMP/test_dependencies/$component/$filename"
- fi
- rm "$DL_SDK_TEMP/test_dependencies/$filename"
- fi
- item_path=$component/$filename/$library_rpath
- fi
-}
-
-runtimes=(MKL CLDNN MYRIAD GNA DLIA OPENCV VPU_FIRMWARE_USB-MA2X8X HDDL OMP TBB AOCL_RTE LIBUSB)
-
-export_library_path() {
- export LD_LIBRARY_PATH=$DL_SDK_TEMP/test_dependencies/$1:$LD_LIBRARY_PATH
-}
-
-export_env_variable() {
- export "$2"="$DL_SDK_TEMP/test_dependencies/$1"
-}
-
-ma2480_path=""
-for i in "${runtimes[@]}"
-do
- add_path "$i"
- export_library_path "$item_path"
- if [ "$i" == "VPU_FIRMWARE_USB-MA2X8X" ]
- then
- ma2480_path="$item_path"
- fi
- if [ "$i" == "HDDL" ]
- then
- cp -r "$DL_SDK_TEMP/test_dependencies/$ma2480_path/"* "$DL_SDK_TEMP/test_dependencies/$item_path"
- export HDDL_INSTALL_DIR="$DL_SDK_TEMP/test_dependencies/$item_path/.."
- fi
-done
-
-echo DATA_PATH="$DATA_PATH"
-export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:lib:/usr/local/lib
\ No newline at end of file
diff --git a/inference-engine/src/CMakeLists.txt b/inference-engine/src/CMakeLists.txt
index ceb077de7a7..8b198bfbf28 100644
--- a/inference-engine/src/CMakeLists.txt
+++ b/inference-engine/src/CMakeLists.txt
@@ -47,9 +47,8 @@ add_subdirectory(snippets)
add_custom_target(ie_libraries ALL
DEPENDS inference_engine_transformations inference_engine_legacy
inference_engine inference_engine_preproc
- inference_engine_ir_v7_reader inference_engine_ir_reader
- inference_engine_lp_transformations inference_engine_snippets
- ir_frontend)
+ inference_engine_ir_v7_reader ir_ngraph_frontend
+ inference_engine_lp_transformations inference_engine_snippets)
if(NGRAPH_ONNX_FRONTEND_ENABLE)
add_dependencies(ie_libraries onnx_ngraph_frontend)
diff --git a/inference-engine/src/cldnn_engine/cldnn_config.cpp b/inference-engine/src/cldnn_engine/cldnn_config.cpp
index 28aa8063e47..533e32271bd 100644
--- a/inference-engine/src/cldnn_engine/cldnn_config.cpp
+++ b/inference-engine/src/cldnn_engine/cldnn_config.cpp
@@ -28,7 +28,7 @@ namespace CLDNNPlugin {
static void createDirectory(std::string _path) {
#if defined(ENABLE_UNICODE_PATH_SUPPORT) && defined(_WIN32)
- std::wstring widepath = FileUtils::multiByteCharToWString(_path.c_str());
+ std::wstring widepath = ov::util::string_to_wstring(_path.c_str());
const wchar_t* path = widepath.c_str();
#else
const char* path = _path.c_str();
diff --git a/inference-engine/src/cldnn_engine/cldnn_graph.cpp b/inference-engine/src/cldnn_engine/cldnn_graph.cpp
index 75ea9d2a251..49d5212d37e 100644
--- a/inference-engine/src/cldnn_engine/cldnn_graph.cpp
+++ b/inference-engine/src/cldnn_engine/cldnn_graph.cpp
@@ -60,8 +60,6 @@ CLDNNGraph::CLDNNGraph(std::shared_ptr graph, uint16_t stream_id)
void CLDNNGraph::UpdateLayersMaps() {
OV_ITT_SCOPED_TASK(itt::domains::CLDNNPlugin, "CLDNNGraph::UpdateLayersMaps");
primitiveIDs = m_program->primitiveIDs;
- primitivesToIRLayersMap = m_program->primitivesToIRLayersMap;
- IRToNgraphLayersMap = m_program->IRToNgraphLayersMap;
prevPrimitiveIDs = m_program->prevPrimitiveIDs;
profilingIDs = m_program->profilingIDs;
perfMap = m_program->perfMap;
@@ -219,25 +217,6 @@ std::shared_ptr CLDNNGraph::GetExecGraphInfoByPrimitivesInfo(s
return res;
};
- auto split_string = [](std::string src, std::string delimiter = ",") -> std::vector {
- std::vector tokens;
- std::string tokenBuf;
- size_t prev = 0, pos = 0, srcLength = src.length(), delimLength = delimiter.length();
- do {
- pos = src.find(delimiter, prev);
- if (pos == std::string::npos) {
- pos = srcLength;
- }
- tokenBuf = src.substr(prev, pos - prev);
- if (!tokenBuf.empty()) {
- tokens.push_back(tokenBuf);
- }
- prev = pos + delimLength;
- } while (pos < srcLength && prev < srcLength);
-
- return tokens;
- };
-
auto remove_type_from_name = [](const std::string& name) -> std::string {
auto it = std::find(name.begin(), name.end(), ':');
if (it == name.end() || (it + 1) == name.end())
@@ -246,22 +225,13 @@ std::shared_ptr CLDNNGraph::GetExecGraphInfoByPrimitivesInfo(s
return std::string((it+1), name.end());
};
+ auto extIdMap = GetNetwork()->get_ext_id_mapping();
+
auto find_origin_layers = [&](const std::string& name) -> std::vector {
- if (primitivesToIRLayersMap.find(name) == primitivesToIRLayersMap.end())
+ if (extIdMap.find(name) == extIdMap.end()) {
return {};
-
- auto cnn_names = primitivesToIRLayersMap.at(name);
- std::vector res;
-
- for (auto& cnn_name : cnn_names) {
- if (IRToNgraphLayersMap.find(cnn_name) != IRToNgraphLayersMap.end()) {
- auto ngraph_names = split_string(IRToNgraphLayersMap.at(cnn_name));
- res.insert(res.end(), ngraph_names.begin(), ngraph_names.end());
- } else {
- res.push_back(cnn_name);
- }
}
- return res;
+ return { extIdMap.at(name) };
};
auto get_inputs = [&] (const cldnn::primitive_info& prim_info) {
@@ -599,13 +569,21 @@ std::map CLDNNGraph::G
auto allIds = GetNetwork()->get_all_primitive_org_ids();
auto executedPrimitives = GetNetwork()->get_executed_primitives();
auto primitivesInfo = GetNetwork()->get_primitives_info();
+ auto extIdMap = GetNetwork()->get_ext_id_mapping();
- auto getUpperCaseName = [&](std::string name) {
+ auto getUpperCaseName = [](std::string name) {
if (name.length() > 0)
name[0] = toupper(name[0]);
return name;
};
+ auto getClearName = [](std::string name) {
+ if (name.find(":") != std::string::npos) {
+ name = name.substr(name.find(":") + 1, name.length());
+ }
+ return name;
+ };
+
auto getFromProfiling = [&](std::string primId) -> bool {
auto perfIter = perfMap.find(primId);
@@ -696,10 +674,7 @@ std::map CLDNNGraph::G
}
}
- std::string layerName = primId;
- if (primId.find(":") != std::string::npos) {
- layerName = primId.substr(primId.find(":") + 1, primId.length());
- }
+ std::string layerName = getClearName(primId);
for (auto& pi : primitivesInfo) {
if (pi.original_id == primId) {
@@ -735,10 +710,27 @@ std::map CLDNNGraph::G
}
// Step 3. Checking primitives which has been deleted from execution order but added by clDNNPlugin
- for (auto& primId : profilingIDs)
+ for (auto& primId : profilingIDs) {
if (std::find(allIds.begin(), allIds.end(), primId) == allIds.end()) {
getFromProfiling(primId);
}
+ }
+
+ for (auto& p : extIdMap) {
+ if (p.first.find(p.second) != std::string::npos) {
+ continue;
+ }
+ auto first_res = result.find(getClearName(p.first));
+ auto second_res = result.find(getClearName(p.second));
+
+ if (first_res != result.end() && second_res != result.end() && first_res != second_res) {
+ std::swap(first_res->second.cpu_uSec, second_res->second.cpu_uSec);
+ std::swap(first_res->second.realTime_uSec, second_res->second.realTime_uSec);
+ std::swap(first_res->second.status, second_res->second.status);
+ std::swap(first_res->second.exec_type, second_res->second.exec_type);
+ std::swap(first_res->second.execution_index, second_res->second.execution_index);
+ }
+ }
return result;
}
diff --git a/inference-engine/src/cldnn_engine/cldnn_graph.h b/inference-engine/src/cldnn_engine/cldnn_graph.h
index 206c58aaccd..d220c4009f5 100644
--- a/inference-engine/src/cldnn_engine/cldnn_graph.h
+++ b/inference-engine/src/cldnn_engine/cldnn_graph.h
@@ -61,8 +61,6 @@ protected:
InferenceEngine::gpu::ClContext::Ptr m_context;
std::vector> m_networks;
std::map primitiveIDs;
- std::map> primitivesToIRLayersMap;
- std::map IRToNgraphLayersMap;
std::map> prevPrimitiveIDs;
std::map> perfMap;
diff --git a/inference-engine/src/cldnn_engine/cldnn_infer_request.cpp b/inference-engine/src/cldnn_engine/cldnn_infer_request.cpp
index 9a55217975c..6c0e2527eac 100644
--- a/inference-engine/src/cldnn_engine/cldnn_infer_request.cpp
+++ b/inference-engine/src/cldnn_engine/cldnn_infer_request.cpp
@@ -12,6 +12,7 @@
#include "cldnn_remote_context.h"
#include "cldnn_executable_network.h"
#include "cldnn_itt.h"
+#include "cldnn/runtime/debug_configuration.hpp"
#include
#include
@@ -622,6 +623,10 @@ void CLDNNInferRequest::allocate_inputs() {
IE_THROW() << "Input layout for " << name << " is not found";
}
+ GPU_DEBUG_GET_INSTANCE(debug_config);
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << name << ": input blob]" << std::endl;
+ }
if (desc.getPrecision() == Precision::I16 || desc.getPrecision() == Precision::U16) {
TensorDesc desc_fp32 = desc;
desc_fp32.setPrecision(Precision::FP32);
@@ -673,6 +678,10 @@ void CLDNNInferRequest::allocate_outputs() {
const cldnn::layout output_layout = m_graph->GetNetwork()->get_output_memory(outputID)->get_layout();
const TensorDesc& desc = no.second->getTensorDesc();
+ GPU_DEBUG_GET_INSTANCE(debug_config);
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << no.first << ": output blob]" << std::endl;
+ }
auto blobPtr = create_device_blob(desc, output_layout);
_deviceOutputs[no.first] = blobPtr;
_outputs[no.first] = blobPtr;
diff --git a/inference-engine/src/cldnn_engine/cldnn_program.cpp b/inference-engine/src/cldnn_engine/cldnn_program.cpp
index 7386501f0b1..22a55d743bd 100644
--- a/inference-engine/src/cldnn_engine/cldnn_program.cpp
+++ b/inference-engine/src/cldnn_engine/cldnn_program.cpp
@@ -284,14 +284,12 @@ std::vector Program::GetInputPrimitiveIDs(const std::shared
void Program::AddPrimitiveToProfiler(const std::shared_ptr& op,
cldnn::primitive_id customOutputId) {
auto id = layer_type_name_ID(op);
- primitivesToIRLayersMap[id] = { op->get_friendly_name() };
primitiveIDs[id] = customOutputId.empty() ? id : customOutputId;
profilingIDs.push_back(id);
}
void Program::AddPrimitiveToProfiler(cldnn::primitive_id id, const std::shared_ptr& op,
cldnn::primitive_id customOutputId) {
- primitivesToIRLayersMap[id] = { op->get_friendly_name() };
primitiveIDs[id] = customOutputId.empty() ? id : customOutputId;
profilingIDs.push_back(id);
}
@@ -299,7 +297,6 @@ void Program::AddPrimitiveToProfiler(cldnn::primitive_id id, const std::shared_p
void Program::AddInnerPrimitiveToProfiler(cldnn::primitive_id id, cldnn::primitive_id parentId,
const std::shared_ptr& op) {
InitProfileInfo(id, layer_type_lower(op), false, InferenceEngine::InferenceEngineProfileInfo::EXECUTED, parentId);
- primitivesToIRLayersMap[id] = { op->get_friendly_name() };
primitiveIDs[id] = id;
profilingIDs.push_back(id);
}
@@ -328,28 +325,24 @@ void Program::InitProfileInfo(const std::string& layerName,
// TODO: Does it make sense to add such method to ngraph core?
bool IsNodeOnConstPath(const std::shared_ptr& node) {
- std::list> nodes_to_process = { node };
- while (!nodes_to_process.empty()) {
- auto current_node = nodes_to_process.front();
- nodes_to_process.pop_front();
-
- for (size_t i = 0; i < current_node->get_input_size(); i++) {
- auto input_node = current_node->get_input_node_shared_ptr(i);
-
- // If input is constant, then drop if from the processing list
- if (std::dynamic_pointer_cast(input_node) != nullptr)
- continue;
-
- // If the node doesn't have any parents and it's not a constant, then we deal with dynamic path
- if (input_node->get_input_size() == 0) {
+ std::set> nodes_processed = {};
+ std::function&)> is_const_node = [&nodes_processed, &is_const_node](const std::shared_ptr& node) {
+ if (nodes_processed.count(node)) return true;
+ nodes_processed.insert(node);
+ // If input is constant, then drop if from the processing list
+ if (std::dynamic_pointer_cast(node) != nullptr)
+ return true;
+ // If the node doesn't have any parents and it's not a constant, then we deal with dynamic path
+ if (node->get_input_size() == 0)
+ return false;
+ for (size_t i = 0; i < node->get_input_size(); i++) {
+ auto input_node = node->get_input_node_shared_ptr(i);
+ if (!is_const_node(input_node))
return false;
- }
-
- nodes_to_process.insert(nodes_to_process.end(), input_node);
}
- }
-
- return true;
+ return true;
+ };
+ return is_const_node(node);
}
} // namespace CLDNNPlugin
diff --git a/inference-engine/src/cldnn_engine/cldnn_program.h b/inference-engine/src/cldnn_engine/cldnn_program.h
index 23b6313cac9..f499104a9b9 100644
--- a/inference-engine/src/cldnn_engine/cldnn_program.h
+++ b/inference-engine/src/cldnn_engine/cldnn_program.h
@@ -76,8 +76,6 @@ public:
static const cldnn::primitive_id m_postCustomLayerTag;
std::map primitiveIDs;
- std::map> primitivesToIRLayersMap;
- std::map IRToNgraphLayersMap;
std::map> prevPrimitiveIDs;
std::map> perfMap;
diff --git a/inference-engine/src/cldnn_engine/ops/batch_to_space.cpp b/inference-engine/src/cldnn_engine/ops/batch_to_space.cpp
index e46643f0617..d67f9e9888a 100644
--- a/inference-engine/src/cldnn_engine/ops/batch_to_space.cpp
+++ b/inference-engine/src/cldnn_engine/ops/batch_to_space.cpp
@@ -42,7 +42,8 @@ void CreateBatchToSpaceOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(batchToSpacePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/broadcast.cpp b/inference-engine/src/cldnn_engine/ops/broadcast.cpp
index 6d6e6303200..16264a31fea 100644
--- a/inference-engine/src/cldnn_engine/ops/broadcast.cpp
+++ b/inference-engine/src/cldnn_engine/ops/broadcast.cpp
@@ -31,8 +31,13 @@ static void CreateCommonBroadcastOp(Program& p, const std::shared_ptrget_input_element_type(0));
- auto reorderPrim = cldnn::reorder(reorderName, inputPrimitive, targetFormat, targetDatatype);
-
+ auto reorderPrim = cldnn::reorder(reorderName,
+ inputPrimitive,
+ targetFormat,
+ targetDatatype,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(reorderPrim);
p.AddInnerPrimitiveToProfiler(reorderName, layerName, op);
@@ -66,7 +71,7 @@ static void CreateCommonBroadcastOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(reshapePrim);
p.AddInnerPrimitiveToProfiler(reshapeName, layerName, op);
@@ -75,7 +80,9 @@ static void CreateCommonBroadcastOp(Program& p, const std::shared_ptrget_output_shape(0)));
+ CldnnTensorFromIEDims(op->get_output_shape(0)),
+ {},
+ op->get_friendly_name());
p.AddPrimitive(broadcastPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/concat.cpp b/inference-engine/src/cldnn_engine/ops/concat.cpp
index 453e9996530..fc1e51d1981 100644
--- a/inference-engine/src/cldnn_engine/ops/concat.cpp
+++ b/inference-engine/src/cldnn_engine/ops/concat.cpp
@@ -45,7 +45,8 @@ void CreateConcatOp(Program& p, const std::shared_ptr& o
layerName,
inputPrimitives,
GetConcatAxis(op->get_axis(), op->get_input_shape(0).size()),
- DataTypeFromPrecision(op->get_output_element_type(0)));
+ DataTypeFromPrecision(op->get_output_element_type(0)),
+ op->get_friendly_name());
p.AddPrimitive(concatPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/constant.cpp b/inference-engine/src/cldnn_engine/ops/constant.cpp
index fea42f31d98..58bc0a18d4a 100644
--- a/inference-engine/src/cldnn_engine/ops/constant.cpp
+++ b/inference-engine/src/cldnn_engine/ops/constant.cpp
@@ -18,6 +18,7 @@
#include "ngraph/op/util/op_types.hpp"
#include "cldnn/primitives/data.hpp"
+#include "cldnn/runtime/debug_configuration.hpp"
namespace CLDNNPlugin {
@@ -169,6 +170,10 @@ void CreateConstantOp(Program& p, const std::shared_ptrsecond;
} else {
+ GPU_DEBUG_GET_INSTANCE(debug_config);
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << initialconstPrimID << ": constant]" << std::endl;
+ }
cldnn::memory::ptr mem = p.GetEngine().allocate_memory(constLayout, false);
auto& stream = p.GetEngine().get_program_stream();
cldnn::mem_lock lock{mem, stream};
@@ -199,7 +204,7 @@ void CreateConstantOp(Program& p, const std::shared_ptrget_friendly_name()));
p.blobMemCache[std::make_pair(data, constDims)] = initialconstPrimID;
constPrimID = initialconstPrimID;
}
diff --git a/inference-engine/src/cldnn_engine/ops/convert.cpp b/inference-engine/src/cldnn_engine/ops/convert.cpp
index 6af5bee759d..603eb26abeb 100644
--- a/inference-engine/src/cldnn_engine/ops/convert.cpp
+++ b/inference-engine/src/cldnn_engine/ops/convert.cpp
@@ -19,8 +19,13 @@ void CreateConvertLikeOp(Program& p, const std::shared_ptrget_input_element_type(1));
- auto reorderPrim = cldnn::reorder(layerName, inputPrimitives[0], cldnn::format::any, outDataType);
-
+ auto reorderPrim = cldnn::reorder(layerName,
+ inputPrimitives[0],
+ cldnn::format::any,
+ outDataType,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(reorderPrim);
p.AddPrimitiveToProfiler(op);
}
@@ -32,7 +37,13 @@ void CreateConvertOp(Program& p, const std::shared_ptr&
auto outDataType = DataTypeFromPrecision(op->get_destination_type());
- auto reorderPrim = cldnn::reorder(layerName, inputPrimitives[0], cldnn::format::any, outDataType);
+ auto reorderPrim = cldnn::reorder(layerName,
+ inputPrimitives[0],
+ cldnn::format::any,
+ outDataType,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(reorderPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/convolution.cpp b/inference-engine/src/cldnn_engine/ops/convolution.cpp
index 83f536a68b7..e8c44693dbd 100644
--- a/inference-engine/src/cldnn_engine/ops/convolution.cpp
+++ b/inference-engine/src/cldnn_engine/ops/convolution.cpp
@@ -84,7 +84,8 @@ void CreateGroupConvolutionOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(convPrim);
p.AddPrimitiveToProfiler(op);
@@ -112,7 +113,8 @@ void CreateConvolutionOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(convPrim);
p.AddPrimitiveToProfiler(op);
@@ -146,7 +148,8 @@ void CreateConvolutionBackpropDataOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(permutePrim);
p.AddInnerPrimitiveToProfiler(permuteName, layerName, op);
@@ -159,14 +162,15 @@ void CreateConvolutionBackpropDataOp(Program& p, const std::shared_ptrget_pads_begin(), op->get_dilations(), op->get_strides(), 1);
auto deconvPrim = cldnn::deconvolution(layerName,
- inputs[0],
- weights,
- {},
- params.groups,
- params.stride,
- params.padding,
- CldnnTensorFromIEDims(op->get_output_tensor(0).get_shape()),
- weights_have_group_dim);
+ inputs[0],
+ weights,
+ {},
+ params.groups,
+ params.stride,
+ params.padding,
+ CldnnTensorFromIEDims(op->get_output_tensor(0).get_shape()),
+ weights_have_group_dim,
+ op->get_friendly_name());
p.AddPrimitive(deconvPrim);
p.AddPrimitiveToProfiler(op);
@@ -202,7 +206,8 @@ void CreateGroupConvolutionBackpropDataOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(permutePrim);
p.AddInnerPrimitiveToProfiler(permuteName, layerName, op);
@@ -214,14 +219,15 @@ void CreateGroupConvolutionBackpropDataOp(Program& p, const std::shared_ptrget_output_tensor(0).get_shape()),
- weights_have_group_dim);
+ inputs[0],
+ weights,
+ {},
+ params.groups,
+ params.stride,
+ params.padding,
+ CldnnTensorFromIEDims(op->get_output_tensor(0).get_shape()),
+ weights_have_group_dim,
+ op->get_friendly_name());
p.AddPrimitive(deconvPrim);
p.AddPrimitiveToProfiler(op);
@@ -247,7 +253,8 @@ void CreateDeformableConvolutionOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(convPrim);
p.AddPrimitiveToProfiler(op);
@@ -280,7 +287,8 @@ void CreateDeformableConvolutionOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(defConvPrimInterp);
p.AddInnerPrimitiveToProfiler(defConvLayerNameInterp, defConvLayerNameConv, op);
auto defConvPrim = cldnn::deformable_conv(defConvLayerNameConv,
@@ -288,7 +296,8 @@ void CreateDeformableConvolutionOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(defConvPrim);
p.AddPrimitiveToProfiler(defConvLayerNameConv, op);
}
@@ -313,7 +322,8 @@ void CreateBinaryConvolutionOp(Program& p, const std::shared_ptrget_pad_value(),
- calc_precision);
+ calc_precision,
+ op->get_friendly_name());
p.AddPrimitive(convPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/ctc_greedy_decoder.cpp b/inference-engine/src/cldnn_engine/ops/ctc_greedy_decoder.cpp
index c8bd8d54e07..4ff72462a47 100644
--- a/inference-engine/src/cldnn_engine/ops/ctc_greedy_decoder.cpp
+++ b/inference-engine/src/cldnn_engine/ops/ctc_greedy_decoder.cpp
@@ -11,6 +11,7 @@
#include "cldnn/primitives/ctc_greedy_decoder.hpp"
#include "cldnn/primitives/reorder.hpp"
#include "cldnn/primitives/mutable_data.hpp"
+#include "cldnn/runtime/debug_configuration.hpp"
#include "transformations/utils/utils.hpp"
@@ -33,7 +34,10 @@ void CreateCommonCTCGreedyDecoderOp(Program& p, const std::shared_ptr(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layer_type_name_ID(op), op);
reorderedInputs[portIndex] = (reorderPrimName);
@@ -70,11 +74,16 @@ void CreateCommonCTCGreedyDecoderOp(Program& p, const std::shared_ptrget_output_shape(1).size()),
CldnnTensorFromIEDims(op->get_output_shape(1)));
+ GPU_DEBUG_GET_INSTANCE(debug_config);
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << layer_type_name_ID(op) << ": mutable data]" << std::endl;
+ }
shared_memory.emplace_back(p.GetEngine().allocate_memory(mutableLayout));
cldnn::primitive_id ctc_gd_mutable_id_w = layer_type_name_ID(op) + "_md_write";
- auto ctc_gd_mutable_prim = cldnn::mutable_data(ctc_gd_mutable_id_w, shared_memory[0]);
- p.primitivesToIRLayersMap[ctc_gd_mutable_id_w] = { op->get_friendly_name() };
+ auto ctc_gd_mutable_prim = cldnn::mutable_data(ctc_gd_mutable_id_w,
+ shared_memory[0],
+ op->get_friendly_name());
p.primitiveIDs[ctc_gd_mutable_id_w] = ctc_gd_mutable_id_w;
p.AddPrimitive(ctc_gd_mutable_prim);
reorderedInputs.push_back(ctc_gd_mutable_id_w);
@@ -86,7 +95,8 @@ void CreateCommonCTCGreedyDecoderOp(Program& p, const std::shared_ptrget_output_shape(0)));
+ CldnnTensorFromIEDims(op->get_output_shape(0)),
+ op->get_friendly_name());
// clDNN primitive supports only i32 as output data type
primitive.output_data_type = DataTypeFromPrecision(ngraph::element::i32);
@@ -99,8 +109,10 @@ void CreateCommonCTCGreedyDecoderOp(Program& p, const std::shared_ptrget_friendly_name() };
+ auto ctc_gd_mutable_prim_r = cldnn::mutable_data(ctc_gd_mutable_id_r,
+ { CTCGreedyDecoderLayerName },
+ shared_memory[0],
+ op->get_friendly_name());
p.primitiveIDs[ctc_gd_mutable_id_r] = ctc_gd_mutable_id_r;
p.AddPrimitive(ctc_gd_mutable_prim_r);
}
diff --git a/inference-engine/src/cldnn_engine/ops/cum_sum.cpp b/inference-engine/src/cldnn_engine/ops/cum_sum.cpp
index 1bdcec2957e..9f8e2a463f2 100644
--- a/inference-engine/src/cldnn_engine/ops/cum_sum.cpp
+++ b/inference-engine/src/cldnn_engine/ops/cum_sum.cpp
@@ -63,7 +63,8 @@ void CreateCumSumOp(Program& p, const std::shared_ptr& o
inputPrimitives[0],
GetCumSumAxis(axis, rank),
exclusive,
- reverse);
+ reverse,
+ op->get_friendly_name());
p.AddPrimitive(primitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/custom.cpp b/inference-engine/src/cldnn_engine/ops/custom.cpp
index 85945bfbdb9..c967100d1f9 100644
--- a/inference-engine/src/cldnn_engine/ops/custom.cpp
+++ b/inference-engine/src/cldnn_engine/ops/custom.cpp
@@ -145,7 +145,10 @@ void CreateCustomOp(Program& p, const std::shared_ptr& op, CLDNNCu
reorderPrimName,
inputPrimitives[param.portIndex],
param.format,
- DataTypeFromPrecision(op->get_input_element_type(param.portIndex)));
+ DataTypeFromPrecision(op->get_input_element_type(param.portIndex)),
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layer_type_name_ID(op), op);
@@ -229,7 +232,8 @@ void CreateCustomOp(Program& p, const std::shared_ptr& op, CLDNNCu
customLayer->CompilerOptions(),
outputLayout,
gws,
- lws);
+ lws,
+ op->get_friendly_name());
auto prevLayerName = genericLayerName;
if (outputLayout.format != cldnn::format::any) {
@@ -239,7 +243,10 @@ void CreateCustomOp(Program& p, const std::shared_ptr& op, CLDNNCu
cldnn::reorder(reorderPrimName,
genericLayerName,
DefaultFormatForDims(op->get_output_shape(0).size()),
- customPrim.output_layout.data_type));
+ customPrim.output_layout.data_type,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
prevLayerName = reorderPrimName;
p.AddInnerPrimitiveToProfiler(reorderPrimName, layer_type_name_ID(op), op);
}
diff --git a/inference-engine/src/cldnn_engine/ops/depth_to_space.cpp b/inference-engine/src/cldnn_engine/ops/depth_to_space.cpp
index b53262ab23d..aa762a356d7 100644
--- a/inference-engine/src/cldnn_engine/ops/depth_to_space.cpp
+++ b/inference-engine/src/cldnn_engine/ops/depth_to_space.cpp
@@ -33,7 +33,8 @@ void CreateDepthToSpaceOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(depthToSpacePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/detection_output.cpp b/inference-engine/src/cldnn_engine/ops/detection_output.cpp
index aa2b505f0e7..80616090655 100644
--- a/inference-engine/src/cldnn_engine/ops/detection_output.cpp
+++ b/inference-engine/src/cldnn_engine/ops/detection_output.cpp
@@ -75,7 +75,8 @@ void CreateDetectionOutputOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(detectionPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/eltwise.cpp b/inference-engine/src/cldnn_engine/ops/eltwise.cpp
index 817512d5bf9..f486bff593d 100644
--- a/inference-engine/src/cldnn_engine/ops/eltwise.cpp
+++ b/inference-engine/src/cldnn_engine/ops/eltwise.cpp
@@ -46,7 +46,13 @@ void CreateElementwiseOp(Program& p, const std::shared_ptr& op, cl
if (targetFormat.value != DefaultFormatForDims(inputRank).value) {
auto reorderName = layerName + "_cldnn_in" + std::to_string(i) + "_reorder";
auto targetDatatype = DataTypeFromPrecision(op->get_input_element_type(i));
- auto reorderPrim = cldnn::reorder(reorderName, inputPrimitives[i], targetFormat, targetDatatype);
+ auto reorderPrim = cldnn::reorder(reorderName,
+ inputPrimitives[i],
+ targetFormat,
+ targetDatatype,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(reorderPrim);
p.AddInnerPrimitiveToProfiler(reorderName, layerName, op);
@@ -61,7 +67,7 @@ void CreateElementwiseOp(Program& p, const std::shared_ptr& op, cl
auto targetShape = CldnnTensorFromIEDims(inputShape);
- auto reshapePrim = cldnn::reshape(reshapeName, inputPrimitives[i], targetShape);
+ auto reshapePrim = cldnn::reshape(reshapeName, inputPrimitives[i], targetShape, op->get_friendly_name());
p.AddPrimitive(reshapePrim);
p.AddInnerPrimitiveToProfiler(reshapeName, layerName, op);
@@ -74,7 +80,8 @@ void CreateElementwiseOp(Program& p, const std::shared_ptr& op, cl
inputPrimitives,
mode,
{},
- out_dt);
+ out_dt,
+ op->get_friendly_name());
p.AddPrimitive(eltwisePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/embedding_bag.cpp b/inference-engine/src/cldnn_engine/ops/embedding_bag.cpp
index 2e97a60aebf..369c0eca44a 100644
--- a/inference-engine/src/cldnn_engine/ops/embedding_bag.cpp
+++ b/inference-engine/src/cldnn_engine/ops/embedding_bag.cpp
@@ -49,7 +49,10 @@ void CreateEmbeddingBagOffsetsSumOp(Program& p, const std::shared_ptr(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layer_type_name_ID(op), op);
reorderedInputs[portIndex] = (reorderPrimName);
@@ -62,7 +65,8 @@ void CreateEmbeddingBagOffsetsSumOp(Program& p, const std::shared_ptrget_output_shape(0)),
- defaultIndex);
+ defaultIndex,
+ op->get_friendly_name());
p.AddPrimitive(embeddingBagPrim);
p.AddPrimitiveToProfiler(op);
@@ -86,7 +90,10 @@ void CreateEmbeddingBagPackedSumOp(Program& p, const std::shared_ptr(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layer_type_name_ID(op), op);
reorderedInputs[portIndex] = (reorderPrimName);
@@ -98,7 +105,9 @@ void CreateEmbeddingBagPackedSumOp(Program& p, const std::shared_ptrget_output_shape(0)));
+ CldnnTensorFromIEDims(op->get_output_shape(0)),
+ -1,
+ op->get_friendly_name());
p.AddPrimitive(embeddingBagPrim);
p.AddPrimitiveToProfiler(op);
@@ -140,7 +149,10 @@ void CreateEmbeddingSegmentsSumOp(Program& p, const std::shared_ptr(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layer_type_name_ID(op), op);
reorderedInputs[portIndex] = (reorderPrimName);
@@ -153,7 +165,8 @@ void CreateEmbeddingSegmentsSumOp(Program& p, const std::shared_ptrget_output_shape(0)),
- defaultIndex);
+ defaultIndex,
+ op->get_friendly_name());
p.AddPrimitive(embeddingBagPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/extract_image_patches.cpp b/inference-engine/src/cldnn_engine/ops/extract_image_patches.cpp
index 23b5f014320..088a0fcd413 100644
--- a/inference-engine/src/cldnn_engine/ops/extract_image_patches.cpp
+++ b/inference-engine/src/cldnn_engine/ops/extract_image_patches.cpp
@@ -38,7 +38,8 @@ void CreateExtractImagePatchesOp(Program& p, const std::shared_ptrget_output_shape(0)));
+ CldnnTensorFromIEDims(op->get_output_shape(0)),
+ op->get_friendly_name());
p.AddPrimitive(extractImagePatchesPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/fake_quantize.cpp b/inference-engine/src/cldnn_engine/ops/fake_quantize.cpp
index 345a70f34bb..52ea33e5d3d 100644
--- a/inference-engine/src/cldnn_engine/ops/fake_quantize.cpp
+++ b/inference-engine/src/cldnn_engine/ops/fake_quantize.cpp
@@ -31,7 +31,8 @@ void CreateFakeQuantizeOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(quantizationPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/gather tree.cpp b/inference-engine/src/cldnn_engine/ops/gather tree.cpp
index 6b73131fd29..5476aa40d97 100644
--- a/inference-engine/src/cldnn_engine/ops/gather tree.cpp
+++ b/inference-engine/src/cldnn_engine/ops/gather tree.cpp
@@ -30,7 +30,10 @@ void CreateGatherTreeOp(Program& p, const std::shared_ptr(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layerName, op);
reorderedInputs[portIndex] = reorderPrimName;
@@ -43,7 +46,8 @@ void CreateGatherTreeOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(gatherTreePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/gather.cpp b/inference-engine/src/cldnn_engine/ops/gather.cpp
index d22258e0673..bcf632f3194 100644
--- a/inference-engine/src/cldnn_engine/ops/gather.cpp
+++ b/inference-engine/src/cldnn_engine/ops/gather.cpp
@@ -77,7 +77,10 @@ void CreateGatherOpBase(Program& p, const std::shared_ptr& op, const int64_t
auto preprocessPrim = cldnn::reorder(reorderPrimName,
inputPrimitives[portIndex],
targetFormat,
- cldnn::data_types::i32);
+ cldnn::data_types::i32,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layerName, op);
reorderedInputs[portIndex] = reorderPrimName;
@@ -94,7 +97,8 @@ void CreateGatherOpBase(Program& p, const std::shared_ptr& op, const int64_t
outLayout,
CldnnTensorFromIEDims(op->get_output_shape(0)),
batch_dim,
- support_neg_ind);
+ support_neg_ind,
+ op->get_friendly_name());
p.AddPrimitive(gatherPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/gather_elements.cpp b/inference-engine/src/cldnn_engine/ops/gather_elements.cpp
index d6138280750..50c25c37f1c 100644
--- a/inference-engine/src/cldnn_engine/ops/gather_elements.cpp
+++ b/inference-engine/src/cldnn_engine/ops/gather_elements.cpp
@@ -55,7 +55,8 @@ void CreateGatherElementsOp(Program& p, const std::shared_ptrget_output_shape(0)),
- GetGatherAxis(axis, rank));
+ GetGatherAxis(axis, rank),
+ op->get_friendly_name());
p.AddPrimitive(primitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/gather_nd.cpp b/inference-engine/src/cldnn_engine/ops/gather_nd.cpp
index cbdc5659bb3..266ada7f904 100644
--- a/inference-engine/src/cldnn_engine/ops/gather_nd.cpp
+++ b/inference-engine/src/cldnn_engine/ops/gather_nd.cpp
@@ -22,10 +22,11 @@ void CreateGatherNDOp(Program& p, const std::shared_ptrget_batch_dims();
auto primitive = cldnn::gather_nd(layerName,
- inputPrimitives[0],
- inputPrimitives[1],
- indices_rank,
- batch_dims);
+ inputPrimitives[0],
+ inputPrimitives[1],
+ indices_rank,
+ batch_dims,
+ op->get_friendly_name());
p.AddPrimitive(primitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/grn.cpp b/inference-engine/src/cldnn_engine/ops/grn.cpp
index 960dd034947..c6d07fe6191 100644
--- a/inference-engine/src/cldnn_engine/ops/grn.cpp
+++ b/inference-engine/src/cldnn_engine/ops/grn.cpp
@@ -19,7 +19,8 @@ void CreateGRNOp(Program& p, const std::shared_ptr& op) {
auto primitive = cldnn::grn(layerName,
inputPrimitives[0],
op->get_bias(),
- DataTypeFromPrecision(op->get_output_element_type(0)));
+ DataTypeFromPrecision(op->get_output_element_type(0)),
+ op->get_friendly_name());
p.AddPrimitive(primitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/interpolate.cpp b/inference-engine/src/cldnn_engine/ops/interpolate.cpp
index df99e6972ee..190032897b4 100644
--- a/inference-engine/src/cldnn_engine/ops/interpolate.cpp
+++ b/inference-engine/src/cldnn_engine/ops/interpolate.cpp
@@ -193,7 +193,8 @@ void CreateInterpolateOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(resamplePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/loop.cpp b/inference-engine/src/cldnn_engine/ops/loop.cpp
index 1ac452265b8..604f73b7e5a 100644
--- a/inference-engine/src/cldnn_engine/ops/loop.cpp
+++ b/inference-engine/src/cldnn_engine/ops/loop.cpp
@@ -29,11 +29,11 @@ using Loop = ngraph::op::v5::Loop;
namespace CLDNNPlugin {
template
-static DATA_TYPE CreateScalarData(Program &p, const cldnn::primitive_id& id, int64_t num) {
+static DATA_TYPE CreateScalarData(Program &p, const cldnn::primitive_id& id, int64_t num, const cldnn::primitive_id& ext_prim_id) {
auto mem = p.GetEngine().allocate_memory({ cldnn::data_types::i64, cldnn::format::bfyx, { 1, 1, 1, 1 } });
cldnn::mem_lock ptr{mem, p.GetEngine().get_program_stream()};
*ptr.begin() = num;
- return {id, mem};
+ return {id, mem, ext_prim_id};
}
static cldnn::mutable_data CreateAdditionalOutputData(Program &p, const std::shared_ptr& op,
@@ -44,7 +44,7 @@ static cldnn::mutable_data CreateAdditionalOutputData(Program &p, const std::sha
const auto tensor = CldnnTensorFromIEDims(op->get_output_shape(output_idx));
cldnn::layout output_layout = cldnn::layout(precision, format, tensor);
auto mem = p.GetEngine().allocate_memory(output_layout);
- auto md = cldnn::mutable_data(id, {input}, mem); // cldnn::data cannot set dependency
+ auto md = cldnn::mutable_data(id, {input}, mem, op->get_friendly_name()); // cldnn::data cannot set dependency
return md;
}
@@ -161,8 +161,7 @@ void CreateLoopOp(Program& p, const std::shared_ptr& op) {
}
const cldnn::primitive_id num_iteration_id = layerName + "_numIteration";
{
- cldnn::mutable_data num_iteration = CreateScalarData(p, num_iteration_id, 0);
- p.primitivesToIRLayersMap[num_iteration_id] = { op->get_friendly_name() };
+ cldnn::mutable_data num_iteration = CreateScalarData(p, num_iteration_id, 0, op->get_friendly_name());
p.primitiveIDs[num_iteration_id] = num_iteration_id;
p.AddPrimitive(num_iteration);
p.AddInnerPrimitiveToProfiler(num_iteration_id, layerName, op);
@@ -216,7 +215,8 @@ void CreateLoopOp(Program& p, const std::shared_ptr& op) {
back_edges, /* back edge mapping */
num_iterations, /* max iteration, i.e. length of iteration axis */
body_current_iteration_id,
- body_execution_condition_id);
+ body_execution_condition_id,
+ op->get_friendly_name());
p.AddPrimitive(loopPrimitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/lrn.cpp b/inference-engine/src/cldnn_engine/ops/lrn.cpp
index c13c17daaeb..28e55bf038f 100644
--- a/inference-engine/src/cldnn_engine/ops/lrn.cpp
+++ b/inference-engine/src/cldnn_engine/ops/lrn.cpp
@@ -38,7 +38,8 @@ void CreateLRNOp(Program& p, const std::shared_ptr& op) {
static_cast(op->get_bias()),
static_cast(op->get_alpha()),
static_cast(op->get_beta()),
- GetNormRegion(axis_value));
+ GetNormRegion(axis_value),
+ op->get_friendly_name());
p.AddPrimitive(lrnPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/matmul.cpp b/inference-engine/src/cldnn_engine/ops/matmul.cpp
index 3d09fc7fd4e..53b8fecd6c2 100644
--- a/inference-engine/src/cldnn_engine/ops/matmul.cpp
+++ b/inference-engine/src/cldnn_engine/ops/matmul.cpp
@@ -89,7 +89,8 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
auto permuteName = op->get_friendly_name() + "/transpose_b";
auto permutePrim = cldnn::permute(permuteName,
weightsName,
- cldnn_permute_order);
+ cldnn_permute_order,
+ op->get_friendly_name());
p.AddPrimitive(permutePrim);
p.AddInnerPrimitiveToProfiler(permuteName, layerName, op);
weightsName = permuteName;
@@ -108,7 +109,8 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
auto permuteName = op->get_friendly_name() + "/transpose_a";
auto permutePrim = cldnn::permute(permuteName,
inputName,
- cldnn_permute_order);
+ cldnn_permute_order,
+ op->get_friendly_name());
p.AddPrimitive(permutePrim);
p.AddInnerPrimitiveToProfiler(permuteName, layerName, op);
inputName = permuteName;
@@ -124,7 +126,10 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
IE_THROW() << "Inconsistent reshape in Matmul op: " << op->get_friendly_name();
auto reshapeInName = op->get_friendly_name() + suffix;
- auto reshapeInPrim = cldnn::reshape(reshapeInName, inputName, CldnnTensorFromIEDims(reshapeSize));
+ auto reshapeInPrim = cldnn::reshape(reshapeInName,
+ inputName,
+ CldnnTensorFromIEDims(reshapeSize),
+ op->get_friendly_name());
p.AddPrimitive(reshapeInPrim);
p.AddInnerPrimitiveToProfiler(reshapeInName, layerName, op);
return reshapeInName;
@@ -144,6 +149,7 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
weightsName,
"",
DataTypeFromPrecision(op->get_output_element_type(0)),
+ op->get_friendly_name(),
cldnn::padding(),
input_rank);
@@ -153,7 +159,7 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
if (reshape_fc) {
auto outputShape = CldnnTensorFromIEDims(op->get_output_shape(0));
auto outReshapeName = layerName + "_cldnn_out_reshape";
- auto outReshapePrim = cldnn::reshape(outReshapeName, layerName, outputShape);
+ auto outReshapePrim = cldnn::reshape(outReshapeName, layerName, outputShape, op->get_friendly_name());
p.AddPrimitive(outReshapePrim);
p.AddInnerPrimitiveToProfiler(outReshapeName, layerName, op);
@@ -188,7 +194,13 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
if (targetFormat.value != DefaultFormatForDims(inputDimsN).value) {
auto reorderName = layerName + "_cldnn_in" + std::to_string(i) + "_reorder";
auto targetDatatype = DataTypeFromPrecision(op->get_output_element_type(0));
- auto reorderPrim = cldnn::reorder(reorderName, inputPrimitives[i], targetFormat, targetDatatype);
+ auto reorderPrim = cldnn::reorder(reorderName,
+ inputPrimitives[i],
+ targetFormat,
+ targetDatatype,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(reorderPrim);
p.AddInnerPrimitiveToProfiler(reorderName, layerName, op);
@@ -227,7 +239,7 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
auto targetShape = gemmSpecificTensor(inputDims);
- auto reshapePrim = cldnn::reshape(reshapeName, inputPrimitives[i], targetShape);
+ auto reshapePrim = cldnn::reshape(reshapeName, inputPrimitives[i], targetShape, op->get_friendly_name());
p.AddPrimitive(reshapePrim);
p.AddInnerPrimitiveToProfiler(reshapeName, layerName, op);
@@ -248,7 +260,8 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
transA,
transB,
alpha,
- beta);
+ beta,
+ op->get_friendly_name());
p.AddPrimitive(gemmPrim);
@@ -258,7 +271,7 @@ void CreateMatMulOp(Program& p, const std::shared_ptr& o
if (outDimsN < 4) {
auto outputShape = CldnnTensorFromIEDims(outDims);
auto outReshapeName = layerName + "_cldnn_out_reshape";
- auto outReshapePrim = cldnn::reshape(outReshapeName, layerName, outputShape);
+ auto outReshapePrim = cldnn::reshape(outReshapeName, layerName, outputShape, op->get_friendly_name());
p.AddPrimitive(outReshapePrim);
p.AddInnerPrimitiveToProfiler(outReshapeName, layerName, op);
diff --git a/inference-engine/src/cldnn_engine/ops/mvn.cpp b/inference-engine/src/cldnn_engine/ops/mvn.cpp
index b9cb376a24e..abd2128326b 100644
--- a/inference-engine/src/cldnn_engine/ops/mvn.cpp
+++ b/inference-engine/src/cldnn_engine/ops/mvn.cpp
@@ -24,7 +24,8 @@ static void CreateCommonMVNOp(Program& p, const std::shared_ptr& o
normalize_variance,
eps,
eps_inside_sqrt,
- across_channels);
+ across_channels,
+ op->get_friendly_name());
p.AddPrimitive(mvnPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/non_max_suppression.cpp b/inference-engine/src/cldnn_engine/ops/non_max_suppression.cpp
index 8adaa3cfa76..b5c2e05e711 100644
--- a/inference-engine/src/cldnn_engine/ops/non_max_suppression.cpp
+++ b/inference-engine/src/cldnn_engine/ops/non_max_suppression.cpp
@@ -12,6 +12,7 @@
#include "cldnn/primitives/reorder.hpp"
#include "cldnn/primitives/mutable_data.hpp"
#include "cldnn/primitives/non_max_suppression.hpp"
+#include "cldnn/runtime/debug_configuration.hpp"
namespace CLDNNPlugin {
@@ -41,7 +42,10 @@ void CreateNonMaxSuppressionIEInternalOp(Program& p, const std::shared_ptr(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(preprocessPrim);
p.AddInnerPrimitiveToProfiler(reorderPrimName, layer_type_name_ID(op), op);
reorderedInputs[portIndex] = (reorderPrimName);
@@ -63,6 +67,7 @@ void CreateNonMaxSuppressionIEInternalOp(Program& p, const std::shared_ptrget_output_size();
std::vector shared_memory;
+ GPU_DEBUG_GET_INSTANCE(debug_config);
switch (num_output) {
case 3: {
auto mutable_precision_second = op->get_output_element_type(2);
@@ -74,11 +79,15 @@ void CreateNonMaxSuppressionIEInternalOp(Program& p, const std::shared_ptrget_output_shape(2).size()),
CldnnTensorFromIEDims(op->get_output_shape(2)));
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << layer_type_name_ID(op) << ": mutable data]" << std::endl;
+ }
shared_memory.emplace_back(p.GetEngine().allocate_memory(mutableLayoutSecond));
cldnn::primitive_id non_max_supression_mutable_id_w_second = layer_type_name_ID(op) + "_md_write_second";
- auto nms_mutable_prim_second = cldnn::mutable_data(non_max_supression_mutable_id_w_second, shared_memory.back());
- p.primitivesToIRLayersMap[non_max_supression_mutable_id_w_second] = { op->get_friendly_name() };
+ auto nms_mutable_prim_second = cldnn::mutable_data(non_max_supression_mutable_id_w_second,
+ shared_memory.back(),
+ op->get_friendly_name());
p.primitiveIDs[non_max_supression_mutable_id_w_second] = non_max_supression_mutable_id_w_second;
p.AddPrimitive(nms_mutable_prim_second);
inputPrimitives.push_back(non_max_supression_mutable_id_w_second);
@@ -91,11 +100,15 @@ void CreateNonMaxSuppressionIEInternalOp(Program& p, const std::shared_ptr(outputIndices), 3, 1, 1));
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << layer_type_name_ID(op) << ": mutable data]" << std::endl;
+ }
shared_memory.emplace_back(p.GetEngine().allocate_memory(mutableLayoutFirst));
cldnn::primitive_id non_max_supression_mutable_id_w_first = layer_type_name_ID(op) + "_md_write_first";
- auto nms_mutable_prim_first = cldnn::mutable_data(non_max_supression_mutable_id_w_first, shared_memory.back());
- p.primitivesToIRLayersMap[non_max_supression_mutable_id_w_first] = { op->get_friendly_name() };
+ auto nms_mutable_prim_first = cldnn::mutable_data(non_max_supression_mutable_id_w_first,
+ shared_memory.back(),
+ op->get_friendly_name());
p.primitiveIDs[non_max_supression_mutable_id_w_first] = non_max_supression_mutable_id_w_first;
p.AddPrimitive(nms_mutable_prim_first);
inputPrimitives.push_back(non_max_supression_mutable_id_w_first);
@@ -112,7 +125,9 @@ void CreateNonMaxSuppressionIEInternalOp(Program& p, const std::shared_ptr(outputIndices),
op->m_center_point_box,
- op->m_sort_result_descending);
+ op->m_sort_result_descending,
+ "", "", "", "", "", "",
+ op->get_friendly_name());
prim.output_data_type = DataTypeFromPrecision(out_type);
@@ -136,15 +151,19 @@ void CreateNonMaxSuppressionIEInternalOp(Program& p, const std::shared_ptrget_friendly_name() };
+ auto nms_mutable_prim_r_second = cldnn::mutable_data(non_max_supression_id_r_second,
+ { nonMaxSupressionLayerName },
+ shared_memory.front(),
+ op->get_friendly_name());
p.primitiveIDs[non_max_supression_id_r_second] = non_max_supression_id_r_second;
p.AddPrimitive(nms_mutable_prim_r_second);
}
case 2: {
cldnn::primitive_id non_max_supression_id_r_first = layer_type_name_ID(op) + ".1";
- auto nms_mutable_prim_r_first = cldnn::mutable_data(non_max_supression_id_r_first, { nonMaxSupressionLayerName }, shared_memory.back());
- p.primitivesToIRLayersMap[non_max_supression_id_r_first] = { op->get_friendly_name() };
+ auto nms_mutable_prim_r_first = cldnn::mutable_data(non_max_supression_id_r_first,
+ { nonMaxSupressionLayerName },
+ shared_memory.back(),
+ op->get_friendly_name());
p.primitiveIDs[non_max_supression_id_r_first] = non_max_supression_id_r_first;
p.AddPrimitive(nms_mutable_prim_r_first);
}
diff --git a/inference-engine/src/cldnn_engine/ops/normalize_l2.cpp b/inference-engine/src/cldnn_engine/ops/normalize_l2.cpp
index 85f2eb95de8..315dee55952 100644
--- a/inference-engine/src/cldnn_engine/ops/normalize_l2.cpp
+++ b/inference-engine/src/cldnn_engine/ops/normalize_l2.cpp
@@ -45,14 +45,15 @@ void CreateNormalizeL2Op(Program& p, const std::shared_ptrget_data_ptr(), bufSize);
auto scalesName = layerName + "_cldnn_input_scales";
- p.AddPrimitive(cldnn::data(scalesName, mem));
+ p.AddPrimitive(cldnn::data(scalesName, mem, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(scalesName, layerName, op);
auto normPrim = cldnn::normalize(layerName,
inputPrimitives[0],
scalesName,
across_spatial,
- eps);
+ eps,
+ op->get_friendly_name());
p.AddPrimitive(normPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/one_hot.cpp b/inference-engine/src/cldnn_engine/ops/one_hot.cpp
index 3d792bda8ae..b7c4fe8a126 100644
--- a/inference-engine/src/cldnn_engine/ops/one_hot.cpp
+++ b/inference-engine/src/cldnn_engine/ops/one_hot.cpp
@@ -53,7 +53,8 @@ void CreateOneHotOp(Program& p, const std::shared_ptr& o
DataTypeFromPrecision(op->get_output_element_type(0)),
static_cast(axis),
on_value,
- off_value);
+ off_value,
+ op->get_friendly_name());
p.AddPrimitive(oneHotPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/pad.cpp b/inference-engine/src/cldnn_engine/ops/pad.cpp
index 0d409414b58..40336df057c 100644
--- a/inference-engine/src/cldnn_engine/ops/pad.cpp
+++ b/inference-engine/src/cldnn_engine/ops/pad.cpp
@@ -66,7 +66,8 @@ void CreatePadOp(Program& p, const std::shared_ptr& op) {
pads_begin,
pads_end,
border_mode,
- pad_value);
+ pad_value,
+ op->get_friendly_name());
p.AddPrimitive(tilePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/parameter.cpp b/inference-engine/src/cldnn_engine/ops/parameter.cpp
index b68593dd0a5..6dd43841cf3 100644
--- a/inference-engine/src/cldnn_engine/ops/parameter.cpp
+++ b/inference-engine/src/cldnn_engine/ops/parameter.cpp
@@ -195,8 +195,8 @@ void CreateParameterOp(Program& p, const std::shared_ptrname());
+ auto inputUV = cldnn::input_layout(uv_name, uv_layout, inputInfo->name());
p.AddPrimitive(inputY);
p.inputLayouts.insert({ inputInfo->name() + "_Y" + std::to_string(i), y_layout });
@@ -205,20 +205,29 @@ void CreateParameterOp(Program& p, const std::shared_ptrname()));
break;
}
case MEAN_IMAGE: {
- p.AddPrimitive(cldnn::reorder(preprocessPrimID, y_name, uv_name, networkInputLayout, meanBlobID));
+ p.AddPrimitive(cldnn::reorder(preprocessPrimID,
+ y_name,
+ uv_name,
+ networkInputLayout,
+ meanBlobID,
+ cldnn::reorder_mean_mode::subtract,
+ inputInfo->name()));
break;
}
default: IE_THROW(Unexpected) << "Invalid mean variant in input " + inputName;
break;
}
- p.primitivesToIRLayersMap[preprocessPrimID] = { inputInfo->name() };
- p.primitivesToIRLayersMap[y_name] = { inputInfo->name() };
- p.primitivesToIRLayersMap[uv_name] = { inputInfo->name() };
p.profilingIDs.push_back(preprocessPrimID);
p.InitProfileInfo(preprocessPrimID, "Reorder");
p.primitiveIDs[inputName] = preprocessPrimID; // If it is batched blob, it will be overwritten afterwards.
@@ -228,7 +237,7 @@ void CreateParameterOp(Program& p, const std::shared_ptr 1) {
auto concatPrimID = "concat:" + inputName + Program::m_preProcessTag;
- p.AddPrimitive(cldnn::concatenation(concatPrimID, reorders, cldnn::concatenation::along_b));
+ p.AddPrimitive(cldnn::concatenation(concatPrimID, reorders, cldnn::concatenation::along_b, op->get_friendly_name()));
p.primitiveIDs[inputName] = concatPrimID;
}
} else {
@@ -237,20 +246,26 @@ void CreateParameterOp(Program& p, const std::shared_ptrname(), inputLayout });
- p.AddPrimitive(cldnn::input_layout(inputName, inputLayout));
- p.primitivesToIRLayersMap[inputName] = { inputInfo->name() };
+ p.AddPrimitive(cldnn::input_layout(inputName, inputLayout, inputInfo->name()));
switch (preProcess.getMeanVariant()) {
case NONE:
case MEAN_VALUE: {
- p.AddPrimitive(cldnn::reorder(preprocessPrimID, inputName, networkInputLayout, meanValues));
+ p.AddPrimitive(cldnn::reorder(preprocessPrimID,
+ inputName,
+ networkInputLayout,
+ meanValues,
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
break;
}
case MEAN_IMAGE: {
p.AddPrimitive(cldnn::reorder(preprocessPrimID,
- inputName,
- networkInputLayout,
- meanBlobID));
+ inputName,
+ networkInputLayout,
+ meanBlobID,
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
break;
}
default: IE_THROW() << "Invalid mean variant in input " << inputName;
diff --git a/inference-engine/src/cldnn_engine/ops/pooling.cpp b/inference-engine/src/cldnn_engine/ops/pooling.cpp
index f1bf6952292..1e0db7bd204 100644
--- a/inference-engine/src/cldnn_engine/ops/pooling.cpp
+++ b/inference-engine/src/cldnn_engine/ops/pooling.cpp
@@ -70,7 +70,8 @@ void CreateAvgPoolOp(Program& p, const std::shared_ptr&
params.stride,
params.pad_begin,
CldnnTensorFromIEDims(op->get_output_shape(0)),
- DataTypeFromPrecision(op->get_output_element_type(0)));
+ DataTypeFromPrecision(op->get_output_element_type(0)),
+ op->get_friendly_name());
poolPrim.pad_end = params.pad_end;
p.AddPrimitive(poolPrim);
p.AddPrimitiveToProfiler(op);
@@ -89,7 +90,8 @@ void CreateMaxPoolOp(Program& p, const std::shared_ptr&
params.stride,
params.pad_begin,
CldnnTensorFromIEDims(op->get_output_shape(0)),
- DataTypeFromPrecision(op->get_output_element_type(0)));
+ DataTypeFromPrecision(op->get_output_element_type(0)),
+ op->get_friendly_name());
poolPrim.pad_end = params.pad_end;
p.AddPrimitive(poolPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/prior_box.cpp b/inference-engine/src/cldnn_engine/ops/prior_box.cpp
index 6cf0aaa6535..43eb5a69941 100644
--- a/inference-engine/src/cldnn_engine/ops/prior_box.cpp
+++ b/inference-engine/src/cldnn_engine/ops/prior_box.cpp
@@ -54,7 +54,8 @@ void CreatePriorBoxClusteredOp(Program& p, const std::shared_ptrget_output_element_type(0)));
+ DataTypeFromPrecision(op->get_output_element_type(0)),
+ op->get_friendly_name());
p.AddPrimitive(priorBoxPrim);
p.AddPrimitiveToProfiler(op);
@@ -103,7 +104,8 @@ void CreatePriorBoxOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(priorBoxPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/proposal.cpp b/inference-engine/src/cldnn_engine/ops/proposal.cpp
index d5b906e5e6e..9be2f1d4e99 100644
--- a/inference-engine/src/cldnn_engine/ops/proposal.cpp
+++ b/inference-engine/src/cldnn_engine/ops/proposal.cpp
@@ -9,6 +9,7 @@
#include "cldnn/primitives/proposal.hpp"
#include "cldnn/primitives/mutable_data.hpp"
+#include "cldnn/runtime/debug_configuration.hpp"
namespace CLDNNPlugin {
@@ -62,11 +63,16 @@ void CreateProposalOp(Program& p, const std::shared_ptrget_output_shape(1).size()),
CldnnTensorFromIEDims(op->get_output_shape(1)));
+ GPU_DEBUG_GET_INSTANCE(debug_config);
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << layer_type_name_ID(op) << ": mutable data]" << std::endl;
+ }
auto shared_memory = p.GetEngine().allocate_memory(mutableLayout);
cldnn::primitive_id proposal_mutable_id_w = layer_type_name_ID(op) + "_md_write";
- auto argmax_mutable_prim = cldnn::mutable_data(proposal_mutable_id_w, shared_memory);
- p.primitivesToIRLayersMap[proposal_mutable_id_w] = { op->get_friendly_name() };
+ auto argmax_mutable_prim = cldnn::mutable_data(proposal_mutable_id_w,
+ shared_memory,
+ op->get_friendly_name());
p.primitiveIDs[proposal_mutable_id_w] = proposal_mutable_id_w;
p.AddPrimitive(argmax_mutable_prim);
inputPrimitives.push_back(proposal_mutable_id_w);
@@ -96,13 +102,16 @@ void CreateProposalOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(proposalPrim);
cldnn::primitive_id proposal_mutable_id_r = layer_type_name_ID(op) + ".1";
- auto argmax_mutable_prim_r = cldnn::mutable_data(proposal_mutable_id_r, { proposalLayerName }, shared_memory);
- p.primitivesToIRLayersMap[proposal_mutable_id_r] = { op->get_friendly_name() };
+ auto argmax_mutable_prim_r = cldnn::mutable_data(proposal_mutable_id_r,
+ { proposalLayerName },
+ shared_memory,
+ op->get_friendly_name());
p.primitiveIDs[proposal_mutable_id_r] = proposal_mutable_id_r;
p.AddPrimitive(argmax_mutable_prim_r);
@@ -134,7 +143,8 @@ void CreateProposalOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(proposalPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/reduce.cpp b/inference-engine/src/cldnn_engine/ops/reduce.cpp
index b336a2e78fa..47a54c70299 100644
--- a/inference-engine/src/cldnn_engine/ops/reduce.cpp
+++ b/inference-engine/src/cldnn_engine/ops/reduce.cpp
@@ -75,7 +75,8 @@ void CreateReduceOp(Program& p, const std::shared_ptr& op, cldnn::
inputPrimitives[0],
mode,
axes,
- static_cast(keep_dims));
+ static_cast(keep_dims),
+ op->get_friendly_name());
p.AddPrimitive(reducePrim);
@@ -96,7 +97,7 @@ void CreateReduceOp(Program& p, const std::shared_ptr& op, cldnn::
outTensor = cldnn::tensor(TensorValue(out_shape[0]), TensorValue(out_shape[1]),
1, TensorValue(out_shape[2]));
}
- auto reshape_prim = cldnn::reshape(resultLayerName, layerName, outTensor);
+ auto reshape_prim = cldnn::reshape(resultLayerName, layerName, outTensor, op->get_friendly_name());
p.AddPrimitive(reshape_prim);
p.AddPrimitiveToProfiler(op, resultLayerName);
}
@@ -112,7 +113,13 @@ void CreateReduceOp(Program& p, const std::shared_ptr& op, cldnn::
else if (rank - rawAxes.size() <= 4)
out_format = cldnn::format::bfyx;
- auto reorder_prim = cldnn::reorder(reorderLayerName, resultLayerName, out_format, out_dt);
+ auto reorder_prim = cldnn::reorder(reorderLayerName,
+ resultLayerName,
+ out_format,
+ out_dt,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(reorder_prim);
p.AddPrimitiveToProfiler(op, reorderLayerName);
} else {
diff --git a/inference-engine/src/cldnn_engine/ops/region_yolo.cpp b/inference-engine/src/cldnn_engine/ops/region_yolo.cpp
index 348dd0f7eeb..314950027cb 100644
--- a/inference-engine/src/cldnn_engine/ops/region_yolo.cpp
+++ b/inference-engine/src/cldnn_engine/ops/region_yolo.cpp
@@ -28,7 +28,8 @@ void CreateRegionYoloOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(regionPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/reorg_yolo.cpp b/inference-engine/src/cldnn_engine/ops/reorg_yolo.cpp
index 4a7f54cf810..9c47ccc9fb0 100644
--- a/inference-engine/src/cldnn_engine/ops/reorg_yolo.cpp
+++ b/inference-engine/src/cldnn_engine/ops/reorg_yolo.cpp
@@ -20,7 +20,8 @@ void CreateReorgYoloOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(reorgPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/reshape.cpp b/inference-engine/src/cldnn_engine/ops/reshape.cpp
index f0084bb6a1c..a4978fbae29 100644
--- a/inference-engine/src/cldnn_engine/ops/reshape.cpp
+++ b/inference-engine/src/cldnn_engine/ops/reshape.cpp
@@ -36,9 +36,13 @@ void CreateCommonReshapeOp(Program& p, const std::shared_ptr& op)
}
cldnn::layout outputLayout(DataTypeFromPrecision(op->get_output_element_type(0)), outputFormat, outTensor);
- p.AddPrimitive(cldnn::reorder(reorderId, reshapeInputId, outputLayout));
+ p.AddPrimitive(cldnn::reorder(reorderId,
+ reshapeInputId,
+ outputLayout,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
p.InitProfileInfo(reorderId, "Reorder", false, InferenceEngine::InferenceEngineProfileInfo::EXECUTED, layerName);
- p.primitivesToIRLayersMap[reorderId] = { op->get_friendly_name() };
p.primitiveIDs[layerName + "_reorder"] = reorderId;
p.primitiveIDs[reorderId] = reorderId;
p.profilingIDs.push_back(reorderId);
@@ -47,7 +51,8 @@ void CreateCommonReshapeOp(Program& p, const std::shared_ptr& op)
auto reshapePrim = cldnn::reshape(layerName,
reshapeInputId,
- outTensor);
+ outTensor,
+ op->get_friendly_name());
p.AddPrimitive(reshapePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/result.cpp b/inference-engine/src/cldnn_engine/ops/result.cpp
index fe0d0f05658..c1219ad8fba 100644
--- a/inference-engine/src/cldnn_engine/ops/result.cpp
+++ b/inference-engine/src/cldnn_engine/ops/result.cpp
@@ -56,9 +56,12 @@ void CreateResultOp(Program& p, const std::shared_ptr& o
std::string outputID = inputs[0];
p.AddPrimitive(cldnn::reorder(outLayerName,
- outputID,
- FormatFromLayout(outputData->getLayout()),
- DataTypeFromPrecision(precision)));
+ outputID,
+ FormatFromLayout(outputData->getLayout()),
+ DataTypeFromPrecision(precision),
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
p.InitProfileInfo(outLayerName, "reorder");
p.profilingIDs.push_back(outLayerName);
p.primitiveIDs[outLayerName] = outLayerName;
diff --git a/inference-engine/src/cldnn_engine/ops/reverse_sequence.cpp b/inference-engine/src/cldnn_engine/ops/reverse_sequence.cpp
index 766bbc89a31..6421a01dc75 100644
--- a/inference-engine/src/cldnn_engine/ops/reverse_sequence.cpp
+++ b/inference-engine/src/cldnn_engine/ops/reverse_sequence.cpp
@@ -22,7 +22,8 @@ void CreateReverseSequenceOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(reverseSequencePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/rnn.cpp b/inference-engine/src/cldnn_engine/ops/rnn.cpp
index 2d4705f1a91..1ebaa0a7868 100644
--- a/inference-engine/src/cldnn_engine/ops/rnn.cpp
+++ b/inference-engine/src/cldnn_engine/ops/rnn.cpp
@@ -107,8 +107,13 @@ void CreateLSTMCellOp(Program& p, const std::shared_ptrget_friendly_name()));
+ p.AddPrimitive(cldnn::reorder(permuteID,
+ inReshapeID,
+ inputLayout,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(inReshapeID, op->get_friendly_name(), op);
p.AddInnerPrimitiveToProfiler(permuteID, op->get_friendly_name(), op);
@@ -117,11 +122,24 @@ void CreateLSTMCellOp(Program& p, const std::shared_ptrget_friendly_name()));
+ p.AddPrimitive(cldnn::reorder(hiddenInStr,
+ hiddenInResh,
+ hiddenLayout,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
+ p.AddPrimitive(cldnn::reshape(cellInResh, inputPrimitives[2], inStateShape, op->get_friendly_name()));
+ p.AddPrimitive(cldnn::reorder(cellInStr,
+ cellInResh,
+ hiddenLayout,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
+ p.AddPrimitive(cldnn::concatenation(input_concatID,
+ { permuteID, hiddenInStr },
+ cldnn::concatenation::concatenation_axis::along_x,
+ op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(hiddenInResh, op->get_friendly_name(), op);
p.AddInnerPrimitiveToProfiler(hiddenInStr, op->get_friendly_name(), op);
@@ -139,14 +157,19 @@ void CreateLSTMCellOp(Program& p, const std::shared_ptrget_friendly_name()));
p.AddInnerPrimitiveToProfiler(WRconcatID, op->get_friendly_name(), op);
- p.AddPrimitive(cldnn::fully_connected(lstm_fc_id, input_concatID, WRconcatID, hasBias ? biasID : ""));
- p.AddPrimitive(cldnn::reshape(gemmReshapeID, lstm_fc_id, gemmSz));
- p.AddPrimitive(cldnn::reorder(gemmReorderID, gemmReshapeID, gemmLayout));
- p.AddPrimitive(cldnn::lstm_elt(lstm_elt_id, gemmReorderID, cellInStr,
- clip, 0, activations, activation_params, cldnn::lstm_weights_order::fizo));
+ p.AddPrimitive(cldnn::fully_connected(lstm_fc_id, input_concatID, WRconcatID, hasBias ? biasID : "", op->get_friendly_name()));
+ p.AddPrimitive(cldnn::reshape(gemmReshapeID, lstm_fc_id, gemmSz, op->get_friendly_name()));
+ p.AddPrimitive(cldnn::reorder(gemmReorderID,
+ gemmReshapeID,
+ gemmLayout,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
+ p.AddPrimitive(cldnn::lstm_elt(lstm_elt_id, gemmReorderID, cellInStr, clip, 0, activations,
+ activation_params, cldnn::lstm_weights_order::fizo, 0, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(lstm_fc_id, op->get_friendly_name(), op);
p.AddInnerPrimitiveToProfiler(gemmReshapeID, op->get_friendly_name(), op);
@@ -156,16 +179,16 @@ void CreateLSTMCellOp(Program& p, const std::shared_ptrget_friendly_name()));
p.AddInnerPrimitiveToProfiler(outputHiddenCropID, op->get_friendly_name(), op);
- p.AddPrimitive(cldnn::reshape(outputHiddenID, outputHiddenCropID, outSz));
+ p.AddPrimitive(cldnn::reshape(outputHiddenID, outputHiddenCropID, outSz, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(outputHiddenID, op->get_friendly_name(), op);
cldnn::primitive_id outputCellCropID = layerName + "_cc";
cldnn::primitive_id outputCellID = layerName + ".1";
- p.AddPrimitive(cldnn::crop(outputCellCropID, lstm_elt_id, hiddenSz, cellCropSz));
+ p.AddPrimitive(cldnn::crop(outputCellCropID, lstm_elt_id, hiddenSz, cellCropSz, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(outputCellCropID, op->get_friendly_name(), op);
- p.AddPrimitive(cldnn::reshape(outputCellID, outputCellCropID, outSz));
+ p.AddPrimitive(cldnn::reshape(outputCellID, outputCellCropID, outSz, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(outputCellID, op->get_friendly_name(), op);
// output primitive IDs
@@ -223,11 +246,16 @@ void CreateLSTMSequenceOp(Program& p, const std::shared_ptrget_friendly_name()));
+ p.AddPrimitive(cldnn::reorder(permuteID,
+ inReshapeID,
+ inputLayout,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
- p.AddPrimitive(cldnn::reshape(inHiddenStateID, inputPrimitives[1], inStateShape));
- p.AddPrimitive(cldnn::reshape(inCellStateID, inputPrimitives[2], inStateShape));
+ p.AddPrimitive(cldnn::reshape(inHiddenStateID, inputPrimitives[1], inStateShape, op->get_friendly_name()));
+ p.AddPrimitive(cldnn::reshape(inCellStateID, inputPrimitives[2], inStateShape, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(inReshapeID, op->get_friendly_name(), op);
p.AddInnerPrimitiveToProfiler(permuteID, op->get_friendly_name(), op);
@@ -243,12 +271,12 @@ void CreateLSTMSequenceOp(Program& p, const std::shared_ptrget_friendly_name()));
p.AddInnerPrimitiveToProfiler(WRconcatID, op->get_friendly_name(), op);
std::vector WRreshapeSize = { 4 * size_t(lstm_hidden_size), size_t(lstm_input_size + lstm_hidden_size) };
cldnn::primitive_id WRreshapeID = WRconcatID + "_reshape";
- auto reshapeInPrim = cldnn::reshape(WRreshapeID, WRconcatID, CldnnTensorFromIEDims(WRreshapeSize));
+ auto reshapeInPrim = cldnn::reshape(WRreshapeID, WRconcatID, CldnnTensorFromIEDims(WRreshapeSize), op->get_friendly_name());
p.AddPrimitive(reshapeInPrim);
p.AddInnerPrimitiveToProfiler(WRreshapeID, op->get_friendly_name(), op);
@@ -267,30 +295,35 @@ void CreateLSTMSequenceOp(Program& p, const std::shared_ptr(seqIdx), 0, 0 };
cldnn::primitive_id inputCrop_id = inputCropID + ":" + seqIdx_str;
- p.AddPrimitive(cldnn::crop(inputCrop_id, permuteID, crop_tensor, offset_tensor));
+ p.AddPrimitive(cldnn::crop(inputCrop_id, permuteID, crop_tensor, offset_tensor, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(inputCrop_id, op->get_friendly_name(), op);
- p.AddPrimitive(cldnn::concatenation(concatID, { inputCrop_id, hiddenStr }, cldnn::concatenation::concatenation_axis::along_x));
+ p.AddPrimitive(cldnn::concatenation(concatID, { inputCrop_id, hiddenStr }, cldnn::concatenation::concatenation_axis::along_x, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(concatID, op->get_friendly_name(), op);
- p.AddPrimitive(cldnn::fully_connected(lstm_fc_id, concatID, WRreshapeID, biasID));
+ p.AddPrimitive(cldnn::fully_connected(lstm_fc_id, concatID, WRreshapeID, biasID, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(lstm_fc_id, op->get_friendly_name(), op);
- p.AddPrimitive(cldnn::reshape(lstm_fc_resh_id, lstm_fc_id, gemmSz));
- p.AddPrimitive(cldnn::reorder(lstm_fc_reor_id, lstm_fc_resh_id, gemmLayout));
- p.AddPrimitive(cldnn::lstm_elt(lstm_elt_id, lstm_fc_reor_id, cellStr,
- clip, 0, activations, activation_params, cldnn::lstm_weights_order::fizo));
+ p.AddPrimitive(cldnn::reshape(lstm_fc_resh_id, lstm_fc_id, gemmSz, op->get_friendly_name()));
+ p.AddPrimitive(cldnn::reorder(lstm_fc_reor_id,
+ lstm_fc_resh_id,
+ gemmLayout,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name()));
+ p.AddPrimitive(cldnn::lstm_elt(lstm_elt_id, lstm_fc_reor_id, cellStr, clip, 0, activations,
+ activation_params, cldnn::lstm_weights_order::fizo, 0, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(lstm_fc_resh_id, op->get_friendly_name(), op);
p.AddInnerPrimitiveToProfiler(lstm_fc_reor_id, op->get_friendly_name(), op);
p.AddInnerPrimitiveToProfiler(lstm_elt_id, op->get_friendly_name(), op);
hiddenStr = crop_id + ":hidden";
cellStr = crop_id + ":cell";
- p.AddPrimitive(cldnn::crop(hiddenStr, lstm_elt_id, hiddenSz, cldnn::tensor{ 0, 0, 0, 0 }));
+ p.AddPrimitive(cldnn::crop(hiddenStr, lstm_elt_id, hiddenSz, cldnn::tensor{ 0, 0, 0, 0 }, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(hiddenStr, op->get_friendly_name(), op);
output_ids_offsets.push_back(hiddenStr);
if (i < lstm_sequence_len - 1) {
- p.AddPrimitive(cldnn::crop(cellStr, lstm_elt_id, hiddenSz, cellCropSz));
+ p.AddPrimitive(cldnn::crop(cellStr, lstm_elt_id, hiddenSz, cellCropSz, op->get_friendly_name()));
p.AddInnerPrimitiveToProfiler(cellStr, op->get_friendly_name(), op);
} else {
// last hidden state crop (output 2)
@@ -299,7 +332,7 @@ void CreateLSTMSequenceOp(Program& p, const std::shared_ptrget_friendly_name()));
cldnn::primitive_id outputCellID = layerName + ".2";
p.AddInnerPrimitiveToProfiler(cellStr, op->get_friendly_name(), op);
p.primitiveIDs[outputCellID] = cellStr;
@@ -310,7 +343,7 @@ void CreateLSTMSequenceOp(Program& p, const std::shared_ptrget_friendly_name()));
p.primitiveIDs[outputConcatID] = concatStr;
p.primitiveIDs[layerName] = concatStr;
diff --git a/inference-engine/src/cldnn_engine/ops/roi_pooling.cpp b/inference-engine/src/cldnn_engine/ops/roi_pooling.cpp
index f2087756405..5de1a56019c 100644
--- a/inference-engine/src/cldnn_engine/ops/roi_pooling.cpp
+++ b/inference-engine/src/cldnn_engine/ops/roi_pooling.cpp
@@ -57,7 +57,8 @@ void CreateDeformablePSROIPoolingOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(psROIPoolingPrim);
p.AddPrimitiveToProfiler(op);
}
@@ -85,7 +86,8 @@ void CreatePSROIPoolingOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(psROIPoolingPrim);
p.AddPrimitiveToProfiler(op);
}
@@ -110,7 +112,11 @@ void CreateROIPoolingOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(roiPoolingPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/scatter_elements_update.cpp b/inference-engine/src/cldnn_engine/ops/scatter_elements_update.cpp
index 19f63dbf3a3..487587a2afa 100644
--- a/inference-engine/src/cldnn_engine/ops/scatter_elements_update.cpp
+++ b/inference-engine/src/cldnn_engine/ops/scatter_elements_update.cpp
@@ -54,10 +54,11 @@ void CreateScatterElementsUpdateOp(Program& p, const std::shared_ptrcast_vector()[0];
auto primitive = cldnn::scatter_elements_update(layerName,
- inputPrimitives[0],
- inputPrimitives[1],
- inputPrimitives[2],
- GetScatterElementsUpdateAxis(axis, rank));
+ inputPrimitives[0],
+ inputPrimitives[1],
+ inputPrimitives[2],
+ GetScatterElementsUpdateAxis(axis, rank),
+ op->get_friendly_name());
p.AddPrimitive(primitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/scatter_nd_update.cpp b/inference-engine/src/cldnn_engine/ops/scatter_nd_update.cpp
index cf5d059772a..525cccfc32e 100644
--- a/inference-engine/src/cldnn_engine/ops/scatter_nd_update.cpp
+++ b/inference-engine/src/cldnn_engine/ops/scatter_nd_update.cpp
@@ -19,10 +19,11 @@ void CreateScatterNDUpdateOp(Program& p, const std::shared_ptrget_input_shape(1).size();
auto primitive = cldnn::scatter_nd_update(layerName,
- inputPrimitives[0],
- inputPrimitives[1],
- inputPrimitives[2],
- indices_rank);
+ inputPrimitives[0],
+ inputPrimitives[1],
+ inputPrimitives[2],
+ indices_rank,
+ op->get_friendly_name());
p.AddPrimitive(primitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/scatter_update.cpp b/inference-engine/src/cldnn_engine/ops/scatter_update.cpp
index c6fb4e9c0aa..913ed452b5f 100644
--- a/inference-engine/src/cldnn_engine/ops/scatter_update.cpp
+++ b/inference-engine/src/cldnn_engine/ops/scatter_update.cpp
@@ -57,7 +57,8 @@ void CreateScatterUpdateOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(primitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/select.cpp b/inference-engine/src/cldnn_engine/ops/select.cpp
index 6b3866ac5db..b47a04b5e56 100644
--- a/inference-engine/src/cldnn_engine/ops/select.cpp
+++ b/inference-engine/src/cldnn_engine/ops/select.cpp
@@ -40,7 +40,13 @@ void CreateSelectOp(Program& p, const std::shared_ptr& o
if (targetFormat.value != DefaultFormatForDims(inputDimsN).value) {
auto reorderName = layerName + "_cldnn_in" + std::to_string(i) + "_reorder";
auto targetDatatype = DataTypeFromPrecision(op->get_input_element_type(i));
- auto reorderPrim = cldnn::reorder(reorderName, inputPrimitives[i], targetFormat, targetDatatype);
+ auto reorderPrim = cldnn::reorder(reorderName,
+ inputPrimitives[i],
+ targetFormat,
+ targetDatatype,
+ std::vector(),
+ cldnn::reorder_mean_mode::subtract,
+ op->get_friendly_name());
p.AddPrimitive(reorderPrim);
p.AddInnerPrimitiveToProfiler(reorderName, layerName, op);
@@ -57,7 +63,7 @@ void CreateSelectOp(Program& p, const std::shared_ptr& o
auto targetShape = CldnnTensorFromIEDims(inputDims);
- auto reshapePrim = cldnn::reshape(reshapeName, inputPrimitives[i], targetShape);
+ auto reshapePrim = cldnn::reshape(reshapeName, inputPrimitives[i], targetShape, op->get_friendly_name());
p.AddPrimitive(reshapePrim);
p.AddInnerPrimitiveToProfiler(reshapeName, layerName, op);
@@ -73,6 +79,7 @@ void CreateSelectOp(Program& p, const std::shared_ptr& o
inputPrimitives[0],
inputPrimitives[1],
inputPrimitives[2],
+ op->get_friendly_name(),
cldnn::padding(),
bc_string);
diff --git a/inference-engine/src/cldnn_engine/ops/shuffle_channels.cpp b/inference-engine/src/cldnn_engine/ops/shuffle_channels.cpp
index f3066ace26a..42976ffbc37 100644
--- a/inference-engine/src/cldnn_engine/ops/shuffle_channels.cpp
+++ b/inference-engine/src/cldnn_engine/ops/shuffle_channels.cpp
@@ -36,7 +36,8 @@ void CreateShuffleChannelsOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(shuffleChannelsPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/softmax.cpp b/inference-engine/src/cldnn_engine/ops/softmax.cpp
index cbaffc04acc..c8049e5800e 100644
--- a/inference-engine/src/cldnn_engine/ops/softmax.cpp
+++ b/inference-engine/src/cldnn_engine/ops/softmax.cpp
@@ -41,7 +41,8 @@ void CreateSoftmaxOp(Program& p, const std::shared_ptr&
std::string layerName = layer_type_name_ID(op);
auto softmaxPrim = cldnn::softmax(layerName,
inputPrimitives[0],
- GetSoftmaxAxis(op->get_axis(), op->get_input_shape(0).size()));
+ GetSoftmaxAxis(op->get_axis(), op->get_input_shape(0).size()),
+ op->get_friendly_name());
p.AddPrimitive(softmaxPrim);
p.AddPrimitiveToProfiler(op);
}
@@ -58,9 +59,10 @@ void CreateLogSoftmaxOp(Program& p, const std::shared_ptr(axis), op->get_input_shape(0).size()));
+ GetSoftmaxAxis(static_cast(axis), op->get_input_shape(0).size()),
+ op->get_friendly_name());
- auto logPrim = cldnn::activation(layerName, layerNameSoftmax, cldnn::activation_func::log);
+ auto logPrim = cldnn::activation(layerName, layerNameSoftmax, cldnn::activation_func::log, {(0.0F), (0.0F)}, op->get_friendly_name());
p.AddPrimitive(softmaxPrim);
p.AddPrimitive(logPrim);
diff --git a/inference-engine/src/cldnn_engine/ops/space_to_batch.cpp b/inference-engine/src/cldnn_engine/ops/space_to_batch.cpp
index fa57d178038..2f51da29776 100644
--- a/inference-engine/src/cldnn_engine/ops/space_to_batch.cpp
+++ b/inference-engine/src/cldnn_engine/ops/space_to_batch.cpp
@@ -42,7 +42,8 @@ void CreateSpaceToBatchOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(batchToSpacePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/space_to_depth.cpp b/inference-engine/src/cldnn_engine/ops/space_to_depth.cpp
index df4a25b4698..ccdb4f6bd39 100644
--- a/inference-engine/src/cldnn_engine/ops/space_to_depth.cpp
+++ b/inference-engine/src/cldnn_engine/ops/space_to_depth.cpp
@@ -27,7 +27,8 @@ void CreateSpaceToDepthOp(Program& p, const std::shared_ptrget_mode()),
- op->get_block_size());
+ op->get_block_size(),
+ op->get_friendly_name());
p.AddPrimitive(spaceToDepthPrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/split.cpp b/inference-engine/src/cldnn_engine/ops/split.cpp
index 33b48c6d17f..247739c274a 100644
--- a/inference-engine/src/cldnn_engine/ops/split.cpp
+++ b/inference-engine/src/cldnn_engine/ops/split.cpp
@@ -40,8 +40,7 @@ void CreateCommonSplitOp(Program& p, const std::shared_ptr& op) {
auto outTensor = CldnnTensorFromIEDims(outLayerDims, 1);
auto offsetTensor = CldnnTensorFromIEDims(startOffset, 0);
- auto cropPrim = cldnn::crop(outLayerName, inputPrimitives[0], outTensor, offsetTensor);
- p.primitivesToIRLayersMap[outLayerName] = { op->get_friendly_name() };
+ auto cropPrim = cldnn::crop(outLayerName, inputPrimitives[0], outTensor, offsetTensor, op->get_friendly_name());
p.primitiveIDs[outLayerName] = outLayerName;
p.AddPrimitive(cropPrim);
diff --git a/inference-engine/src/cldnn_engine/ops/strided_slice.cpp b/inference-engine/src/cldnn_engine/ops/strided_slice.cpp
index 8c796290a74..695612b073f 100644
--- a/inference-engine/src/cldnn_engine/ops/strided_slice.cpp
+++ b/inference-engine/src/cldnn_engine/ops/strided_slice.cpp
@@ -189,7 +189,7 @@ void CreateStridedSliceOp(Program& p, const std::shared_ptrget_friendly_name() + "/Reshape_before";
- auto reshapePrim = cldnn::reshape(reshapeInName, inputPrimitives[0], targetShape);
+ auto reshapePrim = cldnn::reshape(reshapeInName, inputPrimitives[0], targetShape, op->get_friendly_name());
p.AddPrimitive(reshapePrim);
p.AddInnerPrimitiveToProfiler(reshapeInName, layerName, op);
inPrimitive = reshapeInName;
@@ -215,7 +215,7 @@ void CreateStridedSliceOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(cropPrim);
p.AddPrimitiveToProfiler(layerName, op);
@@ -223,7 +223,7 @@ void CreateStridedSliceOp(Program& p, const std::shared_ptrget_friendly_name() + "/Crop";
- auto reshapePrim = cldnn::reshape(reshapeOutName, layerName, targetShape);
+ auto reshapePrim = cldnn::reshape(reshapeOutName, layerName, targetShape, op->get_friendly_name());
p.AddPrimitive(reshapePrim);
p.AddInnerPrimitiveToProfiler(reshapeOutName, layerName, op);
}
@@ -258,7 +258,8 @@ void CreateStridedSliceOp(Program& p, const std::shared_ptrget_friendly_name());
p.AddPrimitive(stridedSlicePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/tensor_iterator.cpp b/inference-engine/src/cldnn_engine/ops/tensor_iterator.cpp
index d9843481979..53fb5939ccb 100644
--- a/inference-engine/src/cldnn_engine/ops/tensor_iterator.cpp
+++ b/inference-engine/src/cldnn_engine/ops/tensor_iterator.cpp
@@ -27,11 +27,11 @@ using TensorIterator = ngraph::op::v0::TensorIterator;
namespace CLDNNPlugin {
template
-static DATA_TYPE CreateScalarData(Program &p, const cldnn::primitive_id& id, int64_t num) {
+static DATA_TYPE CreateScalarData(Program &p, const cldnn::primitive_id& id, int64_t num, const cldnn::primitive_id& ext_prim_id) {
auto mem = p.GetEngine().allocate_memory({ cldnn::data_types::i64, cldnn::format::bfyx, { 1, 1, 1, 1 } });
cldnn::mem_lock ptr{mem, p.GetEngine().get_program_stream()};
*ptr.begin() = num;
- return {id, mem};
+ return {id, mem, ext_prim_id};
}
static cldnn::mutable_data CreateAdditionalOutputData(Program &p, const std::shared_ptr& op,
@@ -42,7 +42,7 @@ static cldnn::mutable_data CreateAdditionalOutputData(Program &p, const std::sha
const auto tensor = CldnnTensorFromIEDims(op->get_output_shape(output_idx));
cldnn::layout output_layout = cldnn::layout(precision, format, tensor);
auto mem = p.GetEngine().allocate_memory(output_layout);
- auto md = cldnn::mutable_data(id, {input}, mem); // cldnn::data cannot set dependency
+ auto md = cldnn::mutable_data(id, {input}, mem, op->get_friendly_name()); // cldnn::data cannot set dependency
return md;
}
@@ -122,24 +122,21 @@ void CreateTensorIteratorOp(Program &p, const std::shared_ptr &o
throw std::runtime_error("tensor iterator's num_iteration cannot be negative");
}
{
- cldnn::data trip_count = CreateScalarData(p, trip_count_id, num_iterations);
- p.primitivesToIRLayersMap[trip_count_id] = { op->get_friendly_name() };
+ cldnn::data trip_count = CreateScalarData(p, trip_count_id, num_iterations, op->get_friendly_name());
p.primitiveIDs[trip_count_id] = trip_count_id;
p.AddPrimitive(trip_count);
p.AddInnerPrimitiveToProfiler(trip_count_id, layerName, op);
}
const cldnn::primitive_id execution_condition_id = layerName + "_initialExecutionCondition";
{
- cldnn::mutable_data execution_condition = CreateScalarData(p, execution_condition_id, 1);
- p.primitivesToIRLayersMap[execution_condition_id] = { op->get_friendly_name() };
+ cldnn::mutable_data execution_condition = CreateScalarData(p, execution_condition_id, 1, op->get_friendly_name());
p.primitiveIDs[execution_condition_id] = execution_condition_id;
p.AddPrimitive(execution_condition);
p.AddInnerPrimitiveToProfiler(execution_condition_id, layerName, op);
}
const cldnn::primitive_id num_iteration_id = layerName + "_numIteration";
{
- cldnn::mutable_data num_iteration = CreateScalarData(p, num_iteration_id, 0);
- p.primitivesToIRLayersMap[num_iteration_id] = { op->get_friendly_name() };
+ cldnn::mutable_data num_iteration = CreateScalarData(p, num_iteration_id, 0, op->get_friendly_name());
p.primitiveIDs[num_iteration_id] = num_iteration_id;
p.AddPrimitive(num_iteration);
p.AddInnerPrimitiveToProfiler(num_iteration_id, layerName, op);
@@ -191,7 +188,10 @@ void CreateTensorIteratorOp(Program &p, const std::shared_ptr &o
input_primitive_maps, /* input mappings connecting outer network and inner network */
output_primitive_maps, /* output mappings connecting outer network and inner network */
back_edges, /* back edge mapping */
- num_iterations); /* max iteration, i.e. length of iteration axis */
+ num_iterations, /* max iteration, i.e. length of iteration axis */
+ "",
+ "",
+ op->get_friendly_name());
p.AddPrimitive(loopPrimitive);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/tile.cpp b/inference-engine/src/cldnn_engine/ops/tile.cpp
index aa91fbd3d5a..4d35ff0c647 100644
--- a/inference-engine/src/cldnn_engine/ops/tile.cpp
+++ b/inference-engine/src/cldnn_engine/ops/tile.cpp
@@ -18,7 +18,8 @@ void CreateTileOp(Program& p, const std::shared_ptr& op) {
auto tilePrim = cldnn::tile(layerName,
inputPrimitives[0],
- CldnnTensorFromIEDims(op->get_output_shape(0)));
+ CldnnTensorFromIEDims(op->get_output_shape(0)),
+ op->get_friendly_name());
p.AddPrimitive(tilePrim);
p.AddPrimitiveToProfiler(op);
diff --git a/inference-engine/src/cldnn_engine/ops/topk.cpp b/inference-engine/src/cldnn_engine/ops/topk.cpp
index 3d8f7e6521a..fe9ae95550b 100644
--- a/inference-engine/src/cldnn_engine/ops/topk.cpp
+++ b/inference-engine/src/cldnn_engine/ops/topk.cpp
@@ -9,6 +9,7 @@
#include "cldnn/primitives/arg_max_min.hpp"
#include "cldnn/primitives/mutable_data.hpp"
+#include "cldnn/runtime/debug_configuration.hpp"
namespace CLDNNPlugin {
@@ -71,11 +72,16 @@ void CreateTopKOp(Program& p, const std::shared_ptr& op) {
DefaultFormatForDims(op->get_output_shape(1).size()),
CldnnTensorFromIEDims(op->get_output_shape(1)));
+ GPU_DEBUG_GET_INSTANCE(debug_config);
+ GPU_DEBUG_IF(debug_config->verbose >= 2) {
+ GPU_DEBUG_COUT << "[" << layer_type_name_ID(op) << ": mutable data]" << std::endl;
+ }
auto shared_memory = p.GetEngine().allocate_memory(mutableLayout);
cldnn::primitive_id argmax_mutable_id_w = layer_type_name_ID(op) + "_md_write";
- auto argmax_mutable_prim = cldnn::mutable_data(argmax_mutable_id_w, shared_memory);
- p.primitivesToIRLayersMap[argmax_mutable_id_w] = {op->get_friendly_name()};
+ auto argmax_mutable_prim = cldnn::mutable_data(argmax_mutable_id_w,
+ shared_memory,
+ op->get_friendly_name());
p.primitiveIDs[argmax_mutable_id_w] = argmax_mutable_id_w;
p.AddPrimitive(argmax_mutable_prim);
inputPrimitives.push_back(argmax_mutable_id_w);
@@ -88,14 +94,17 @@ void CreateTopKOp(Program& p, const std::shared_ptr& op) {
chosen_axis,
stype,
true,
+ op->get_friendly_name(),
cldnn::padding({0, 0, 0, 0}, 0),
DataTypeFromPrecision(op->get_output_element_type(0)));
p.AddPrimitive(argmaxPrim);
cldnn::primitive_id argmax_mutable_id_r = layerName + ".1";
- auto argmax_mutable_prim_r = cldnn::mutable_data(argmax_mutable_id_r, {ArgMaxLayerName}, shared_memory);
- p.primitivesToIRLayersMap[argmax_mutable_id_r] = {op->get_friendly_name()};
+ auto argmax_mutable_prim_r = cldnn::mutable_data(argmax_mutable_id_r,
+ { ArgMaxLayerName },
+ shared_memory,
+ op->get_friendly_name());
p.primitiveIDs[argmax_mutable_id_r] = argmax_mutable_id_r;
p.AddPrimitive(argmax_mutable_prim_r);
p.InitProfileInfo(ArgMaxLayerName, layer_type_lower(op));
@@ -108,6 +117,7 @@ void CreateTopKOp(Program& p, const std::shared_ptr