diff --git a/.github/dockerfiles/docker_tag b/.github/dockerfiles/docker_tag
index e764c498736e46..61dd89f6e199f0 100644
--- a/.github/dockerfiles/docker_tag
+++ b/.github/dockerfiles/docker_tag
@@ -1 +1 @@
-pr-26336
\ No newline at end of file
+pr-26588
\ No newline at end of file
diff --git a/.github/dockerfiles/ov_test/ubuntu_22_04_x64/Dockerfile b/.github/dockerfiles/ov_test/ubuntu_22_04_x64/Dockerfile
index 0e52f067fbd089..410a3f401949f2 100644
--- a/.github/dockerfiles/ov_test/ubuntu_22_04_x64/Dockerfile
+++ b/.github/dockerfiles/ov_test/ubuntu_22_04_x64/Dockerfile
@@ -28,6 +28,8 @@ RUN apt-get update && \
python3.11-venv \
python3.11-distutils \
libhdf5-dev \
+ # For TF Models tests
+ wget \
&& \
rm -rf /var/lib/apt/lists/*
diff --git a/.github/labeler.yml b/.github/labeler.yml
index 08db04658daa48..310eb2d88a66f8 100644
--- a/.github/labeler.yml
+++ b/.github/labeler.yml
@@ -151,7 +151,8 @@
- 'tests/layer_tests/tensorflow2_keras_tests/**/*'
- 'tests/layer_tests/jax_tests/**/*'
- any: ['tests/model_hub_tests/**',
- '!tests/model_hub_tests/pytorch/**/*']
+ '!tests/model_hub_tests/pytorch/**/*',
+ '!tests/model_hub_tests/jax/**/*']
'category: TFL FE':
- 'src/frontends/tensorflow_lite/**/*'
@@ -165,12 +166,16 @@
- 'tests/layer_tests/py_frontend_tests/test_torch_decoder.py'
- 'tests/layer_tests/py_frontend_tests/test_torch_frontend.py'
- any: ['tests/model_hub_tests/**',
- '!tests/model_hub_tests/tensorflow/**/*']
+ '!tests/model_hub_tests/tensorflow/**/*',
+ '!tests/model_hub_tests/jax/**/*']
'category: JAX FE':
- 'src/frontends/jax/**/*'
- 'src/bindings/python/src/openvino/frontend/jax/**/*'
- 'tests/layer_tests/jax_tests/**/*'
+- any: ['tests/model_hub_tests/**',
+ '!tests/model_hub_tests/tensorflow/**/*',
+ '!tests/model_hub_tests/pytorch/**/*']
'category: tools':
- any: ['tools/**',
diff --git a/.github/workflows/android_x64.yml b/.github/workflows/android_x64.yml
index 4dd48ac1c1a28c..e8fb4902e37612 100644
--- a/.github/workflows/android_x64.yml
+++ b/.github/workflows/android_x64.yml
@@ -15,6 +15,9 @@ concurrency:
permissions: read-all
+env:
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
+
jobs:
Smart_CI:
runs-on: ubuntu-latest
@@ -84,6 +87,7 @@ jobs:
SCCACHE_ERROR_LOG: /__w/openvino/sccache_log.txt
SCCACHE_LOG: warn
OPENVINO_REPO: '/__w/openvino/openvino/openvino'
+ OPENVINO_GENAI_REPO: '/__w/openvino/openvino/openvino.genai'
BUILD_DIR: '/__w/openvino/openvino/build'
ANDROID_TOOLS: '/deps/android_tools'
ANDROID_NDK_HOME: '/deps/android_tools/ndk-bundle'
@@ -98,6 +102,14 @@ jobs:
path: 'openvino'
submodules: 'true'
+ - name: Clone OpenVINO GenAI
+ uses: actions/checkout@692973e3d937129bcbf40652eb9f2f61becf3332 # v4.1.7
+ with:
+ repository: 'openvinotoolkit/openvino.genai'
+ path: ${{ env.OPENVINO_GENAI_REPO }}
+ submodules: 'true'
+ ref: ${{ env.TARGET_BRANCH }}
+
#
# Print system info
#
@@ -117,13 +129,13 @@ jobs:
-DANDROID_STL=c++_shared \
-DANDROID_PLATFORM=${{ env.ANDROID_SDK_VERSION }} \
-DCMAKE_COMPILE_WARNING_AS_ERROR=OFF \
- -DCMAKE_BUILD_TYPE=Release \
-DENABLE_STRICT_DEPENDENCIES=OFF \
-DCMAKE_VERBOSE_MAKEFILE=ON \
-DCMAKE_CXX_COMPILER_LAUNCHER=${{ env.CMAKE_CXX_COMPILER_LAUNCHER }} \
-DCMAKE_C_COMPILER_LAUNCHER=${{ env.CMAKE_C_COMPILER_LAUNCHER }} \
-DENABLE_LTO=ON \
-DENABLE_PYTHON=OFF \
+ -DOPENVINO_EXTRA_MODULES=${{ env.OPENVINO_GENAI_REPO }} \
-S ${OPENVINO_REPO} \
-B ${BUILD_DIR}
diff --git a/.github/workflows/build_doc.yml b/.github/workflows/build_doc.yml
index 4ea3cf36aaa725..7b380530cfaecd 100644
--- a/.github/workflows/build_doc.yml
+++ b/.github/workflows/build_doc.yml
@@ -50,6 +50,10 @@ jobs:
tar -xzf doxygen-$DOXY_VER.linux.bin.tar.gz
echo "$(pwd)/doxygen-$DOXY_VER/bin/" >> $GITHUB_PATH
+ - name: Validate benchmarks files
+ run: |
+ python3 docs/scripts/tests/validate_benchmarks.py docs/sphinx_setup/_static/benchmarks_files/
+
- name: Build docs
run: |
rm -rf build && mkdir build && cd build
diff --git a/.github/workflows/coverity.yml b/.github/workflows/coverity.yml
index dcee9bce15b99b..1d2f8e3ff54820 100644
--- a/.github/workflows/coverity.yml
+++ b/.github/workflows/coverity.yml
@@ -5,6 +5,9 @@ on:
openvinoRef:
description: 'Branch, tag or commit hash to clone openvino from. Taken from event context if not set'
type: string
+ openvinoContribRef:
+ description: 'Branch, tag or commit hash to clone openvino_contrib from. Taken from event context if not set'
+ type: string
schedule:
# run daily at 00:00
- cron: '0 0 * * *'
@@ -19,6 +22,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Build:
@@ -58,7 +62,7 @@ jobs:
repository: 'openvinotoolkit/openvino_contrib'
path: ${{ env.OPENVINO_CONTRIB_REPO }}
submodules: 'true'
- ref: 'master'
+ ref: ${{ inputs.openvinoContribRef || env.TARGET_BRANCH }}
#
# Dependencies
diff --git a/.github/workflows/job_build_linux.yml b/.github/workflows/job_build_linux.yml
index 6466685387cee6..0b76af69ffb0ec 100644
--- a/.github/workflows/job_build_linux.yml
+++ b/.github/workflows/job_build_linux.yml
@@ -56,6 +56,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Build:
@@ -110,7 +111,7 @@ jobs:
repository: 'openvinotoolkit/openvino_contrib'
path: ${{ env.OPENVINO_CONTRIB_REPO }}
submodules: 'true'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
- name: Generate product manifest and set CI_BUILD_NUMBER & CI_BUILD_DEV_TAG
id: create_manifest
@@ -282,7 +283,7 @@ jobs:
- name: Upload openvino RPM packages
if: ${{ inputs.build-rpm-packages }}
- uses: actions/upload-artifact@0b2256b8c012f0828dc542b3febcab082c67f72b # v4.3.4
+ uses: actions/upload-artifact@50769540e7f4bd5e21e526ee35c689e35e0d6874 # v4.4.0
with:
name: openvino_rpm_packages
path: ${{ env.BUILD_DIR }}/*.rpm
diff --git a/.github/workflows/job_build_windows.yml b/.github/workflows/job_build_windows.yml
index cc3e93c3325e74..e5ed6c74df3964 100644
--- a/.github/workflows/job_build_windows.yml
+++ b/.github/workflows/job_build_windows.yml
@@ -19,6 +19,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/win
PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Build:
@@ -56,7 +57,7 @@ jobs:
with:
repository: 'openvinotoolkit/openvino_contrib'
path: 'openvino_contrib'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
- name: Set CCACHE_REMOTE_DIR based on event
shell: bash
diff --git a/.github/workflows/job_jax_models_tests.yml b/.github/workflows/job_jax_models_tests.yml
new file mode 100644
index 00000000000000..0d1a2944bf8ccf
--- /dev/null
+++ b/.github/workflows/job_jax_models_tests.yml
@@ -0,0 +1,116 @@
+name: JAX/Flax Models tests
+
+on:
+ workflow_call:
+ inputs:
+ runner:
+ description: 'Machine on which the tests would run'
+ type: string
+ required: true
+ container:
+ description: 'JSON to be converted to the value of the "container" configuration for the job'
+ type: string
+ required: false
+ default: '{"image": null}'
+ model_scope:
+ description: 'Scope of models for testing.'
+ type: string
+ required: true
+
+permissions: read-all
+
+jobs:
+ JAX_Models_Tests:
+ name: JAX/Flax Models tests
+ timeout-minutes: ${{ inputs.model_scope == 'precommit' && 35 || 35 }}
+ runs-on: ${{ inputs.runner }}
+ container: ${{ fromJSON(inputs.container) }}
+ defaults:
+ run:
+ shell: bash
+ env:
+ DEBIAN_FRONTEND: noninteractive # to prevent apt-get from waiting user input
+ OPENVINO_REPO: ${{ github.workspace }}/openvino
+ INSTALL_DIR: ${{ github.workspace }}/install
+ INSTALL_TEST_DIR: ${{ github.workspace }}/install/tests
+ MODEL_HUB_TESTS_INSTALL_DIR: ${{ github.workspace }}/install/tests/model_hub_tests
+ steps:
+ - name: Download OpenVINO package
+ uses: actions/download-artifact@fa0a91b85d4f404e444e00e005971372dc801d16 # v4.1.8
+ with:
+ name: openvino_package
+ path: ${{ env.INSTALL_DIR }}
+
+ - name: Download OpenVINO tokenizers extension
+ uses: actions/download-artifact@fa0a91b85d4f404e444e00e005971372dc801d16 # v4.1.8
+ with:
+ name: openvino_tokenizers_wheel
+ path: ${{ env.INSTALL_DIR }}
+
+ - name: Download OpenVINO tests package
+ uses: actions/download-artifact@fa0a91b85d4f404e444e00e005971372dc801d16 # v4.1.8
+ with:
+ name: openvino_tests
+ path: ${{ env.INSTALL_TEST_DIR }}
+
+ # Needed as ${{ github.workspace }} is not working correctly when using Docker
+ - name: Setup Variables
+ run: |
+ echo "OPENVINO_REPO=$GITHUB_WORKSPACE/openvino" >> "$GITHUB_ENV"
+ echo "INSTALL_DIR=$GITHUB_WORKSPACE/install" >> "$GITHUB_ENV"
+ echo "INSTALL_TEST_DIR=$GITHUB_WORKSPACE/install/tests" >> "$GITHUB_ENV"
+ echo "MODEL_HUB_TESTS_INSTALL_DIR=$GITHUB_WORKSPACE/install/tests/model_hub_tests" >> "$GITHUB_ENV"
+
+ - name: Extract OpenVINO packages
+ run: |
+ pushd ${INSTALL_DIR}
+ tar -xzf openvino_package.tar.gz -C ${INSTALL_DIR}
+ popd
+
+ pushd ${INSTALL_TEST_DIR}
+ tar -xzf openvino_tests.tar.gz -C ${INSTALL_DIR}
+ popd
+
+ - name: Fetch setup_python action
+ uses: actions/checkout@692973e3d937129bcbf40652eb9f2f61becf3332 # v4.1.7
+ with:
+ sparse-checkout: |
+ .github/actions/setup_python/action.yml
+ sparse-checkout-cone-mode: false
+ path: 'openvino'
+
+ - name: Setup Python 3.11
+ uses: ./openvino/.github/actions/setup_python
+ with:
+ version: '3.11'
+ should-setup-pip-paths: 'false'
+ self-hosted-runner: ${{ contains(inputs.runner, 'aks') }}
+
+ - name: Install OpenVINO Python wheels
+ run: |
+ # To enable pytest parallel features
+ python3 -m pip install pytest-xdist[psutil]
+ python3 -m pip install ${INSTALL_DIR}/tools/openvino-*
+ python3 -m pip install ${INSTALL_DIR}/openvino_tokenizers-*
+
+ - name: Install JAX tests requirements for precommit
+ run: |
+ python3 -m pip install -r ${MODEL_HUB_TESTS_INSTALL_DIR}/jax/requirements.txt
+
+ - name: JAX/Flax Models Tests from Hugging Face
+ if: ${{ inputs.model_scope == 'precommit' || inputs.model_scope == 'nightly' }}
+ run: |
+ export PYTHONPATH=${MODEL_HUB_TESTS_INSTALL_DIR}:$PYTHONPATH
+ python3 -m pytest ${MODEL_HUB_TESTS_INSTALL_DIR}/jax/ -m ${TYPE} --html=${INSTALL_TEST_DIR}/TEST-jax_model_${{ inputs.model_scope }}_tests.html --self-contained-html -v
+ env:
+ TYPE: ${{ inputs.model_scope == 'precommit' && 'precommit' || 'nightly' }}
+ TEST_DEVICE: CPU
+
+ - name: Upload Test Results
+ uses: actions/upload-artifact@50769540e7f4bd5e21e526ee35c689e35e0d6874 # v4.4.0
+ if: ${{ !cancelled() }}
+ with:
+ name: test-results-jax-models-${{ inputs.model_scope }}
+ path: |
+ ${{ env.INSTALL_TEST_DIR }}/TEST*.html
+ if-no-files-found: 'error'
diff --git a/.github/workflows/job_python_unit_tests.yml b/.github/workflows/job_python_unit_tests.yml
index f793860958f31a..c4ab208c54e6a8 100644
--- a/.github/workflows/job_python_unit_tests.yml
+++ b/.github/workflows/job_python_unit_tests.yml
@@ -16,12 +16,15 @@ on:
description: 'Components that are affected by changes in the commit defined by the Smart CI Action'
type: string
required: true
+ python-version:
+ description: 'Python version to setup. E.g., "3.11"'
+ type: string
+ required: true
permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
- PYTHON_VERSION: '3.11'
jobs:
Python_Unit_Tests:
@@ -77,10 +80,10 @@ jobs:
sparse-checkout-cone-mode: false
path: 'action_root'
- - name: Setup Python ${{ env.PYTHON_VERSION }}
+ - name: Setup Python ${{ inputs.python-version }}
uses: ./action_root/.github/actions/setup_python
with:
- version: ${{ env.PYTHON_VERSION }}
+ version: ${{ inputs.python-version }}
pip-cache-path: ${{ runner.os == 'Linux' && env.PIP_CACHE_PATH || '' }}
should-setup-pip-paths: ${{ runner.os == 'Linux' }}
self-hosted-runner: ${{ runner.os == 'Linux' }}
@@ -174,7 +177,7 @@ jobs:
export LD_PRELOAD=${GOMP_LIB}
fi
- python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/mo_python_api_tests --junitxml=${INSTALL_TEST_DIR}/TEST-test_mo_convert.xml
+ python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/mo_python_api_tests -n logical --junitxml=${INSTALL_TEST_DIR}/TEST-test_mo_convert.xml
env:
TEST_DEVICE: CPU
TEST_PRECISION: FP16
@@ -192,7 +195,7 @@ jobs:
export LD_PRELOAD=${GOMP_LIB}
fi
- python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/ovc_python_api_tests --junitxml=${INSTALL_TEST_DIR}/TEST-test_ovc_convert.xml
+ python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/ovc_python_api_tests -n logical --junitxml=${INSTALL_TEST_DIR}/TEST-test_ovc_convert.xml
env:
TEST_DEVICE: CPU
TEST_PRECISION: FP16
@@ -231,7 +234,7 @@ jobs:
PYTORCH_TRACING_MODE: TORCHFX
- name: ONNX Layer Tests
- if: fromJSON(inputs.affected-components).ONNX_FE.test
+ if: ${{ fromJSON(inputs.affected-components).ONNX_FE.test }}
run: |
# requires 'unit_tests' from 'tools/mo'
export PYTHONPATH=${INSTALL_TEST_DIR}/mo:$PYTHONPATH
@@ -296,7 +299,7 @@ jobs:
python3 ${OPENVINO_REPO}/docs/articles_en/assets/snippets/main.py
- name: Python API Tests -- numpy>=2.0.0
- if: ${{ fromJSON(inputs.affected-components).Python_API.test }}
+ if: ${{ fromJSON(inputs.affected-components).Python_API.test && inputs.python-version != '3.12' }} # Ticket: 152242
run: |
python3 -m pip uninstall -y numpy
python3 -m pip install "numpy>=2.0.0,<2.1.0"
diff --git a/.github/workflows/job_tokenizers.yml b/.github/workflows/job_tokenizers.yml
index 4238cf04f67e64..7bb8c1fcae4b82 100644
--- a/.github/workflows/job_tokenizers.yml
+++ b/.github/workflows/job_tokenizers.yml
@@ -26,6 +26,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Openvino_tokenizers:
@@ -70,7 +71,7 @@ jobs:
with:
repository: 'openvinotoolkit/openvino_tokenizers'
path: ${{ env.OPENVINO_TOKENIZERS_REPO }}
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
- name: Download OpenVINO package
uses: actions/download-artifact@fa0a91b85d4f404e444e00e005971372dc801d16 # v4.1.8
diff --git a/.github/workflows/linux_arm64.yml b/.github/workflows/linux_arm64.yml
index a447c41897792d..ab9fab0313fb7e 100644
--- a/.github/workflows/linux_arm64.yml
+++ b/.github/workflows/linux_arm64.yml
@@ -17,7 +17,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
- PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Smart_CI:
@@ -122,7 +122,7 @@ jobs:
repository: 'openvinotoolkit/openvino_contrib'
path: ${{ env.OPENVINO_CONTRIB_REPO }}
submodules: 'true'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
- name: Generate product manifest and set CI_BUILD_NUMBER & CI_BUILD_DEV_TAG
id: create_manifest
@@ -388,6 +388,7 @@ jobs:
runner: 'aks-linux-16-cores-arm'
container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_20_04_arm64 }}", "volumes": ["/mount:/mount"]}'
affected-components: ${{ needs.smart_ci.outputs.affected_components }}
+ python-version: '3.11'
TensorFlow_Layer_Tests:
name: TensorFlow Layer Tests
diff --git a/.github/workflows/linux_conditional_compilation.yml b/.github/workflows/linux_conditional_compilation.yml
index f037fb28022ace..f0ce141e8c004f 100644
--- a/.github/workflows/linux_conditional_compilation.yml
+++ b/.github/workflows/linux_conditional_compilation.yml
@@ -18,6 +18,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Smart_CI:
@@ -118,7 +119,7 @@ jobs:
repository: 'openvinotoolkit/testdata'
path: ${{ env.MODELS_PATH }}
lfs: 'true'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
#
# Print system info
@@ -291,7 +292,7 @@ jobs:
repository: 'openvinotoolkit/testdata'
path: ${{ env.MODELS_PATH }}
lfs: 'true'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
- name: Download selective build statistics package
uses: actions/download-artifact@fa0a91b85d4f404e444e00e005971372dc801d16 # v4.1.8
diff --git a/.github/workflows/linux_sanitizers.yml b/.github/workflows/linux_sanitizers.yml
index 23dcf1d78c05e1..23d6eb26256ae3 100644
--- a/.github/workflows/linux_sanitizers.yml
+++ b/.github/workflows/linux_sanitizers.yml
@@ -16,6 +16,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Build:
@@ -75,7 +76,7 @@ jobs:
repository: 'openvinotoolkit/openvino_contrib'
path: ${{ env.OPENVINO_CONTRIB_REPO }}
submodules: 'true'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
#
# Print system info
diff --git a/.github/workflows/mac.yml b/.github/workflows/mac.yml
index ca1d804a0c4e1f..715380811d6870 100644
--- a/.github/workflows/mac.yml
+++ b/.github/workflows/mac.yml
@@ -267,6 +267,7 @@ jobs:
with:
runner: 'macos-13'
affected-components: ${{ needs.smart_ci.outputs.affected_components }}
+ python-version: '3.11'
TensorFlow_Layer_Tests:
name: TensorFlow Layer Tests
diff --git a/.github/workflows/mac_arm64.yml b/.github/workflows/mac_arm64.yml
index efcbc56fb2c9b5..2615fe16316ea7 100644
--- a/.github/workflows/mac_arm64.yml
+++ b/.github/workflows/mac_arm64.yml
@@ -266,6 +266,7 @@ jobs:
with:
runner: 'macos-13-xlarge'
affected-components: ${{ needs.smart_ci.outputs.affected_components }}
+ python-version: '3.11'
TensorFlow_Layer_Tests:
name: TensorFlow Layer Tests
diff --git a/.github/workflows/send_workflows_to_opentelemetry.yml b/.github/workflows/send_workflows_to_opentelemetry.yml
index c90d951eea88a4..3bda0df32c79a9 100644
--- a/.github/workflows/send_workflows_to_opentelemetry.yml
+++ b/.github/workflows/send_workflows_to_opentelemetry.yml
@@ -37,6 +37,7 @@ jobs:
otel-export-trace:
name: Export finished workflow metrics
runs-on: aks-linux-2-cores-8gb
+ if: github.repository == 'openvinotoolkit/openvino'
steps:
- name: Checkout
diff --git a/.github/workflows/ubuntu_20.yml b/.github/workflows/ubuntu_20.yml
index 7be3e4033e7a6d..96a42ab197207f 100644
--- a/.github/workflows/ubuntu_20.yml
+++ b/.github/workflows/ubuntu_20.yml
@@ -132,7 +132,8 @@ jobs:
runner: "[ 'self-hosted', 'igpu' ]"
container: '{"image": "ubuntu:20.04", "volumes": ["/dev/dri:/dev/dri"], "options": "--group-add 109 --group-add 44
--device /dev/dri:/dev/dri"}'
- if: fromJSON(needs.smart_ci.outputs.affected_components).GPU
+ # if: fromJSON(needs.smart_ci.outputs.affected_components).GPU
+ if: ${{ 'false' }} # Ticket: 152280
dGPU:
name: dGPU Tests
@@ -149,11 +150,12 @@ jobs:
runner: "[ 'self-hosted', 'dgpu' ]"
container: '{"image": "ubuntu:20.04", "volumes": ["/dev/dri:/dev/dri"], "options": "--group-add 109 --group-add 44
--device /dev/dri/card0:/dev/dri/card0 --device /dev/dri/renderD128:/dev/dri/renderD128"}'
- if: ${{ github.event_name == 'schedule' }}
+ # if: ${{ github.event_name == 'schedule' }}
+ if: ${{ 'false' }} # Ticket: 152280
Overall_Status:
name: ci/gha_overall_status_ubuntu_20
- needs: [Smart_CI, Build, iGPU, Debian_Packages, Samples]
+ needs: [Smart_CI, Build, Debian_Packages, Samples]
if: ${{ always() }}
runs-on: ubuntu-latest
steps:
diff --git a/.github/workflows/ubuntu_22.yml b/.github/workflows/ubuntu_22.yml
index 9714c129b8d5ce..b2a2f78410e9f7 100644
--- a/.github/workflows/ubuntu_22.yml
+++ b/.github/workflows/ubuntu_22.yml
@@ -21,6 +21,7 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Smart_CI:
@@ -277,7 +278,7 @@ jobs:
uses: ./.github/workflows/job_onnx_models_tests.yml
with:
runner: 'aks-linux-16-cores-64gb'
- container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_build.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
CXX_Unit_Tests:
name: C++ unit tests
@@ -294,8 +295,9 @@ jobs:
uses: ./.github/workflows/job_python_unit_tests.yml
with:
runner: 'aks-linux-4-cores-16gb'
- container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_build.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
affected-components: ${{ needs.smart_ci.outputs.affected_components }}
+ python-version: '3.11'
TensorFlow_Layer_Tests:
name: TensorFlow Layer Tests
@@ -304,7 +306,7 @@ jobs:
with:
runner: 'aks-linux-4-cores-16gb'
shell: bash
- container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_build.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
affected-components: ${{ needs.smart_ci.outputs.affected_components }}
CPU_Functional_Tests:
@@ -325,7 +327,7 @@ jobs:
with:
runner: 'aks-linux-8-cores-16gb'
model_scope: 'precommit'
- container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_build.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
TensorFlow_Models_Tests_Nightly_TF_HUB:
name: TensorFlow TF Hub Models tests
@@ -335,7 +337,7 @@ jobs:
with:
runner: 'aks-linux-8-cores-64gb'
model_scope: 'nightly_tf_hub'
- container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_build.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
TensorFlow_Models_Tests_Nightly_HF:
name: TensorFlow Hugging Face Models tests
@@ -345,7 +347,7 @@ jobs:
with:
runner: 'aks-linux-8-cores-64gb'
model_scope: 'nightly_hf'
- container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_build.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
# TODO: Switch back to self-hosted runners
# container:
@@ -379,6 +381,16 @@ jobs:
runner: 'ubuntu-22.04-16-cores'
model_scope: 'nightly_scope2'
+ JAX_Models_Tests_Precommit:
+ name: JAX/Flax Models tests
+ if: fromJSON(needs.smart_ci.outputs.affected_components).JAX_FE.test
+ needs: [ Docker, Build, Smart_CI, Openvino_tokenizers ]
+ uses: ./.github/workflows/job_jax_models_tests.yml
+ with:
+ runner: 'aks-linux-8-cores-16gb'
+ model_scope: 'precommit'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_22_04_x64 }}", "volumes": ["/mount:/mount"]}'
+
NVIDIA_Plugin:
name: NVIDIA plugin
needs: [ Docker, Build, Smart_CI ]
@@ -439,7 +451,7 @@ jobs:
with:
repository: 'openvinotoolkit/openvino_contrib'
path: ${{ env.OPENVINO_CONTRIB_REPO }}
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
#
# Build
@@ -508,7 +520,7 @@ jobs:
Overall_Status:
name: ci/gha_overall_status
needs: [Smart_CI, Build, Debian_Packages, Samples, Conformance, ONNX_Runtime, CXX_Unit_Tests, Python_Unit_Tests, TensorFlow_Layer_Tests,
- CPU_Functional_Tests, TensorFlow_Models_Tests_Precommit, PyTorch_Models_Tests, NVIDIA_Plugin, Openvino_tokenizers, iGPU]
+ CPU_Functional_Tests, TensorFlow_Models_Tests_Precommit, PyTorch_Models_Tests, JAX_Models_Tests_Precommit, NVIDIA_Plugin, Openvino_tokenizers, iGPU]
if: ${{ always() }}
runs-on: ubuntu-latest
steps:
diff --git a/.github/workflows/ubuntu_24.yml b/.github/workflows/ubuntu_24.yml
index ce55afe426ba5a..a0e1b314391b24 100644
--- a/.github/workflows/ubuntu_24.yml
+++ b/.github/workflows/ubuntu_24.yml
@@ -17,7 +17,6 @@ permissions: read-all
env:
PIP_CACHE_PATH: /mount/caches/pip/linux
- PYTHON_VERSION: '3.11'
jobs:
Smart_CI:
@@ -115,9 +114,19 @@ jobs:
container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_24_04_x64 }}", "volumes": ["/mount:/mount"]}'
affected-components: ${{ needs.smart_ci.outputs.affected_components }}
+ Python_Unit_Tests:
+ name: Python unit tests
+ needs: [ Docker, Build, Smart_CI ]
+ uses: ./.github/workflows/job_python_unit_tests.yml
+ with:
+ runner: 'aks-linux-4-cores-16gb'
+ container: '{"image": "${{ fromJSON(needs.docker.outputs.images).ov_test.ubuntu_24_04_x64 }}", "volumes": ["/mount:/mount"]}'
+ affected-components: ${{ needs.smart_ci.outputs.affected_components }}
+ python-version: '3.12'
+
Overall_Status:
name: ci/gha_overall_status_ubuntu_24
- needs: [Smart_CI, Build, Debian_Packages, Samples]
+ needs: [Smart_CI, Build, Debian_Packages, Samples, Python_Unit_Tests]
if: ${{ always() }}
runs-on: ubuntu-latest
steps:
diff --git a/.github/workflows/windows_conditional_compilation.yml b/.github/workflows/windows_conditional_compilation.yml
index 07ec15cae62795..e6ea006c83f657 100644
--- a/.github/workflows/windows_conditional_compilation.yml
+++ b/.github/workflows/windows_conditional_compilation.yml
@@ -20,6 +20,7 @@ permissions: read-all
env:
PYTHON_VERSION: '3.11'
+ TARGET_BRANCH: ${{ github.base_ref || github.event.merge_group.base_ref || github.ref }}
jobs:
Smart_CI:
@@ -83,7 +84,7 @@ jobs:
repository: 'openvinotoolkit/testdata'
path: 'testdata'
lfs: 'true'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
#
# Print system info
@@ -291,7 +292,7 @@ jobs:
repository: 'openvinotoolkit/testdata'
path: 'testdata'
lfs: 'true'
- ref: 'master'
+ ref: ${{ env.TARGET_BRANCH }}
- name: Download selective build statistics package
uses: actions/download-artifact@fa0a91b85d4f404e444e00e005971372dc801d16 # v4.1.8
diff --git a/docs/articles_en/documentation/legacy-features/install-dev-tools.rst b/docs/articles_en/documentation/legacy-features/install-dev-tools.rst
index c9496238b3984f..4bb672c376185e 100644
--- a/docs/articles_en/documentation/legacy-features/install-dev-tools.rst
+++ b/docs/articles_en/documentation/legacy-features/install-dev-tools.rst
@@ -19,7 +19,7 @@ Python developer, it only takes a few simple steps to install the tools with PyP
are developing in C/C++, OpenVINO Runtime must be installed separately before installing
OpenVINO Development Tools.
-In both cases, Python 3.8 - 3.11 needs to be installed on your machine before starting.
+In both cases, Python 3.9 - 3.12 needs to be installed on your system before starting.
.. note::
diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst b/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst
index 035cafbef56c09..511ecc627d45ad 100644
--- a/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst
+++ b/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst
@@ -34,7 +34,7 @@ Install Intel® Distribution of OpenVINO™ Toolkit for Linux Using APT Reposito
* `CMake 3.13 or higher, 64-bit `__
* GCC 7.5.0 (for Ubuntu 18.04), GCC 9.3.0 (for Ubuntu 20.04) or GCC 11.3.0 (for Ubuntu 22.04)
- * `Python 3.8 - 3.11, 64-bit `__
+ * `Python 3.9 - 3.12, 64-bit `__
Installing OpenVINO Runtime
diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-archive-linux.rst b/docs/articles_en/get-started/install-openvino/install-openvino-archive-linux.rst
index f12a82a77d0d8f..53649345c062e4 100644
--- a/docs/articles_en/get-started/install-openvino/install-openvino-archive-linux.rst
+++ b/docs/articles_en/get-started/install-openvino/install-openvino-archive-linux.rst
@@ -48,7 +48,7 @@ Install OpenVINO™ Runtime on Linux from an Archive File
:sync: software
* `CMake 3.13 or higher, 64-bit `__
- * `Python 3.8 - 3.11, 64-bit `__
+ * `Python 3.9 - 3.12, 64-bit `__
* GCC:
.. tab-set::
diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-archive-macos.rst b/docs/articles_en/get-started/install-openvino/install-openvino-archive-macos.rst
index 4879c20f45d4e0..e42f4f3bde8aac 100644
--- a/docs/articles_en/get-started/install-openvino/install-openvino-archive-macos.rst
+++ b/docs/articles_en/get-started/install-openvino/install-openvino-archive-macos.rst
@@ -29,7 +29,7 @@ Install OpenVINO™ Runtime on macOS from an Archive File
:sync: software-requirements
* `CMake 3.13 or higher `__ (choose "macOS 10.13 or later"). Add ``/Applications/CMake.app/Contents/bin`` to path (for default install).
- * `Python 3.8 - 3.11 `__ (choose 3.8 - 3.11). Install and add to path.
+ * `Python 3.9 - 3.12 `__ (choose 3.9 - 3.12). Install and add to path.
* Apple Xcode Command Line Tools. In the terminal, run ``xcode-select --install`` from any directory
* (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-archive-windows.rst b/docs/articles_en/get-started/install-openvino/install-openvino-archive-windows.rst
index bbce587cabd627..9f243928aba2b5 100644
--- a/docs/articles_en/get-started/install-openvino/install-openvino-archive-windows.rst
+++ b/docs/articles_en/get-started/install-openvino/install-openvino-archive-windows.rst
@@ -38,7 +38,7 @@ System Requirements
* `Microsoft Visual Studio 2019 with MSBuild `__ or `Microsoft Visual Studio 2022 `__
* `CMake 3.14 or higher, 64-bit `__ (optional, only required for building sample applications)
- * `Python 3.8 - 3.11, 64-bit `__
+ * `Python 3.9 - 3.12, 64-bit `__
.. note::
diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-brew.rst b/docs/articles_en/get-started/install-openvino/install-openvino-brew.rst
index c96665928e7d65..f111c0f18e3fec 100644
--- a/docs/articles_en/get-started/install-openvino/install-openvino-brew.rst
+++ b/docs/articles_en/get-started/install-openvino/install-openvino-brew.rst
@@ -40,14 +40,14 @@ Install OpenVINO™ Runtime via Homebrew
* `Homebrew `_
* `CMake 3.13 or higher, 64-bit `__
* GCC 7.5.0 (for Ubuntu 18.04), GCC 9.3.0 (for Ubuntu 20.04) or GCC 11.3.0 (for Ubuntu 22.04)
- * `Python 3.8 - 3.10, 64-bit `__
+ * `Python 3.9 - 3.12, 64-bit `__
.. tab-item:: macOS
:sync: macos
* `Homebrew `_
* `CMake 3.13 or higher `__ (choose "macOS 10.13 or later"). Add ``/Applications/CMake.app/Contents/bin`` to path (for default installation).
- * `Python 3.8 - 3.11 `__ . Install and add it to path.
+ * `Python 3.9 - 3.12 `__ . Install and add it to path.
* Apple Xcode Command Line Tools. In the terminal, run ``xcode-select --install`` from any directory to install it.
* (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst b/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst
index 95c0de7f9e4d14..6775495fcd2a30 100644
--- a/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst
+++ b/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst
@@ -48,7 +48,7 @@ Install OpenVINO™ Runtime on Linux From YUM Repository
* `CMake 3.13 or higher, 64-bit `_
* GCC 8.2.0
- * `Python 3.8 - 3.11, 64-bit `_
+ * `Python 3.9 - 3.12, 64-bit `_
Install OpenVINO Runtime
diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst b/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst
index d1c6c39896cb0b..8a1ceff7271187 100644
--- a/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst
+++ b/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst
@@ -40,7 +40,7 @@ Install OpenVINO™ Runtime on Linux From ZYPPER Repository
* `CMake 3.13 or higher, 64-bit `_
* GCC 8.2.0
- * `Python 3.8 - 3.11, 64-bit `_
+ * `Python 3.9 - 3.12, 64-bit `_
Install OpenVINO Runtime
diff --git a/docs/articles_en/get-started/troubleshooting-install-config.rst b/docs/articles_en/get-started/troubleshooting-install-config.rst
index 1e518609f57bd6..8f5c338af160a3 100644
--- a/docs/articles_en/get-started/troubleshooting-install-config.rst
+++ b/docs/articles_en/get-started/troubleshooting-install-config.rst
@@ -59,7 +59,7 @@ Troubleshooting Guide for OpenVINO™ Installation & Configuration
.. dropdown:: Check the versions of Python and PIP
To check your Python version, run ``python -VV`` or ``python --version``. The supported
- Python versions are 64-bit, between 3.8 and 3.11. If your Python version does not meet the
+ Python versions are 64-bit, between 3.9 and 3.12. If your Python version does not meet the
requirements, you need to upgrade:
* For Windows, **do not install Python from the Windows Store** as it can cause issues.
diff --git a/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-installation.rst b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-installation.rst
index 6c56110411a708..eb02caa06852fd 100644
--- a/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-installation.rst
+++ b/docs/articles_en/learn-openvino/interactive-tutorials-python/notebooks-installation.rst
@@ -1,8 +1,6 @@
Installation of OpenVINO™ Notebooks
=====================================
-
-
.. meta::
:description: An installation guide for Jupyter notebooks on which Python
tutorials run. The tutorials serve as introduction to the
@@ -30,20 +28,20 @@ The table below lists the supported operating systems and Python versions.
| | (64-bit |
| | ) `__ |
+=====================================+================================+
-| Ubuntu 20.04 LTS, 64-bit | 3.8, 3.9, 3.10. 3.11 |
+| Ubuntu 20.04 LTS, 64-bit | 3.9, 3.10, 3.11, 3.12 |
+-------------------------------------+--------------------------------+
-| Ubuntu 22.04 LTS, 64-bit | 3.8, 3.9, 3.10, 3.11 |
+| Ubuntu 22.04 LTS, 64-bit | 3.9, 3.10, 3.11, 3.12 |
+-------------------------------------+--------------------------------+
-| Red Hat Enterprise Linux 8 | 3.8, 3.9, 3.10, 3.11 |
+| Red Hat Enterprise Linux 8 | 3.9, 3.10, 3.11, 3.12 |
+-------------------------------------+--------------------------------+
-| CentOS 7, 64 bit | 3.8, 3.9, 3.10, 3.11 |
+| CentOS 7, 64 bit | 3.9, 3.10, 3.11, 3.12 |
+-------------------------------------+--------------------------------+
-| macOS 10.15.x versions or higher | 3.8, 3.9, 3.10, 3.11 |
+| macOS 10.15.x versions or higher | 3.9, 3.10, 3.11, 3.12 |
+-------------------------------------+--------------------------------+
-| Windows 10, 64-bit Pro, Enterprise | 3.8, 3.9, 3.10, 3.11 |
+| Windows 10, 64-bit Pro, Enterprise | 3.9, 3.10, 3.11, 3.12 |
| or Education editions | |
+-------------------------------------+--------------------------------+
-| Windows Server 2016 or higher | 3.8, 3.9, 3.10, 3.11 |
+| Windows Server 2016 or higher | 3.9, 3.10, 3.11, 3.12 |
+-------------------------------------+--------------------------------+
OpenVINO Notebooks also require Git. Follow the guide below for your
@@ -59,7 +57,7 @@ Installing prerequisites
1. **Install Python**
- Download 64 bit version of Python software (3.8, 3.9, 3.10, 3.11) from `python.org `__
+ Download 64 bit version of Python software (3.9 - 3.12) from `python.org `__
Run the installer by double clicking it. Follow the installation steps to set up the software.
@@ -76,13 +74,7 @@ Installing prerequisites
Run the installer by double clicking it. Follow the installation steps to set up the software.
- 3. **Install C++ Redistributable (For Python 3.8 only)**
-
- Download 64 bit version of C++ Redistributable from `here `__
-
- Run the installer by double clicking it. Follow the installation steps to set up the software.
-
- 4. (Optional) Install FFMPEG
+ 3. Install FFMPEG (Optional)
Download FFMPEG binary from `here `__
@@ -91,7 +83,7 @@ Installing prerequisites
.. tab-item:: Linux
:sync: linux
- 1. **Install Python and GIT**
+ 4. **Install Python and GIT**
.. note::
@@ -464,7 +456,7 @@ Installing notebooks
.. code-block:: sh
- conda create --name openvino_env python=3.8 -y
+ conda create --name openvino_env python=3.9 -y
2. Activate the environment
diff --git a/docs/dev/build_linux.md b/docs/dev/build_linux.md
index 732c01d12b56b6..09afc6fbcfaf7d 100644
--- a/docs/dev/build_linux.md
+++ b/docs/dev/build_linux.md
@@ -11,7 +11,7 @@ The software was validated on:
- [CMake](https://cmake.org/download/) 3.13 or higher
- GCC 7.5 or higher to build OpenVINO Runtime
-- Python 3.8 - 3.11 for OpenVINO Runtime Python API
+- Python 3.9 - 3.12 for OpenVINO Runtime Python API
- (Optional) Install Intel® Graphics Compute Runtime for OpenCL™ Driver package to enable inference on Intel integrated GPUs.
## How to build
@@ -39,7 +39,7 @@ The software was validated on:
mkdir build && cd build
```
-> **NOTE**: It is recommended to disable the oneAPI environment before compiling OpenVINO from source on Linux, as it may cause build failures.
+> **NOTE**: It is recommended to disable the oneAPI environment before compiling OpenVINO from source on Linux, as it may cause build failures.
4. OpenVINO Runtime uses a CMake-based build system. In the created `build` directory, run `cmake` to fetch project dependencies and create Unix makefiles, then run `make` to build the project:
```sh
@@ -66,7 +66,7 @@ You can use the following additional build options:
- To build the OpenVINO Runtime Python API:
1. Enable the `-DENABLE_PYTHON=ON` option in the CMake step above (Step 4). To specify an exact Python version, use the following options (requires cmake 3.16 and higher):
```
- -DPython3_EXECUTABLE=/usr/bin/python3.8
+ -DPython3_EXECUTABLE=/usr/bin/python3.9
```
2. To build a wheel package (.whl), enable the `-DENABLE_WHEEL=ON` option in the CMake step above (Step 4), and install requirements:
```sh
diff --git a/docs/dev/build_mac_arm.md b/docs/dev/build_mac_arm.md
index 1225aad63622c7..5a1a3698568f95 100644
--- a/docs/dev/build_mac_arm.md
+++ b/docs/dev/build_mac_arm.md
@@ -14,7 +14,7 @@ The software was validated on:
- [brew](https://brew.sh) package manager to install additional dependencies. Use [install brew](https://brew.sh) guide to achieve this.
- Installation step for python and python libraries varies depending on the host architecture:
- - **arm64** Python 3.8 - 3.11 for the OpenVINO Runtime Python API, Development tools (Model Optimizer, POT and others):
+ - **arm64** Python 3.9 - 3.12 for the OpenVINO Runtime Python API, Development tools (Model Optimizer, POT and others):
```sh
% # let's have a look what python versions are available in brew
% brew search python
diff --git a/docs/dev/build_mac_intel_cpu.md b/docs/dev/build_mac_intel_cpu.md
index 0df64188537edb..f5b70d73709c20 100644
--- a/docs/dev/build_mac_intel_cpu.md
+++ b/docs/dev/build_mac_intel_cpu.md
@@ -12,7 +12,7 @@ The software was validated on:
- [brew](https://brew.sh) package manager to install additional dependencies. Use [install brew](https://brew.sh) guide to achieve this.
- Installation step for python and python libraries varies depending on the host architecture:
- - **x86_64** Python 3.8 - 3.11 for the OpenVINO Runtime Python API, Development tools (Model Optimizer, POT and others):
+ - **x86_64** Python 3.9 - 3.12 for the OpenVINO Runtime Python API, Development tools (Model Optimizer, POT and others):
```sh
% # let's have a look what python versions are available in brew
% brew search python
diff --git a/docs/dev/build_windows.md b/docs/dev/build_windows.md
index c73dd6239c36c7..eea95fa441cc63 100644
--- a/docs/dev/build_windows.md
+++ b/docs/dev/build_windows.md
@@ -11,7 +11,7 @@ Supported configurations:
- [CMake](https://cmake.org/download/) 3.13 or higher
- Microsoft Visual Studio 2019 or higher, version 16.3 or later
> **NOTE**: Native Microsoft Visual Studio for WoA has been available since version 3.11.
-- Python 3.8 - 3.11 for OpenVINO Runtime Python API
+- Python 3.9 - 3.12 for OpenVINO Runtime Python API
> **NOTE**: Python for ARM64 is available since [3.11](https://www.python.org/downloads/windows/) version.
- [Git for Windows*]
- (Windows on ARM only) [LLVM for Windows on ARM (WoA)](https://github.com/llvm/llvm-project/releases/download/llvmorg-15.0.6/LLVM-15.0.6-woa64.exe)
diff --git a/docs/requirements.txt b/docs/requirements.txt
index 84813255ac7694..0e5e94bd98cf61 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,6 +1,6 @@
alabaster==0.7.14
atomicwrites==1.4.0
-attrs==22.1.0
+attrs==22.2.0
Babel==2.11.0
beautifulsoup4==4.9.3
breathe==4.35.0
@@ -14,6 +14,7 @@ importlib-metadata==4.8.0
iniconfig==1.1.1
ipython==8.10.0
Jinja2==3.1.4
+jsonschema==4.23.0
lxml>=4.9.2
MarkupSafe==2.1.1
mistune==2.0.3
diff --git a/docs/scripts/tests/validate_benchmarks.py b/docs/scripts/tests/validate_benchmarks.py
new file mode 100644
index 00000000000000..8876a09dc58db2
--- /dev/null
+++ b/docs/scripts/tests/validate_benchmarks.py
@@ -0,0 +1,80 @@
+import os
+import json
+import requests
+import argparse
+from jsonschema import Draft7Validator
+import sys
+
+
+def load_json(file_path):
+ """Load JSON data from a file."""
+ with open(file_path, 'r') as file:
+ return json.load(file)
+
+def validate_json_files(benchmarks_dir):
+ """Validate all JSON files in the 'data' subdirectory against the schema."""
+ # Define the path to the schema file
+ schema_path = os.path.join(benchmarks_dir, 'schema', 'graph-data-schema.json')
+
+ # Fetch the schema
+ schema = load_json(schema_path)
+ validator = Draft7Validator(schema)
+
+ # Define the path to the 'data' subdirectory containing the JSON files
+ data_dir = os.path.join(benchmarks_dir, 'data')
+
+ # Get all JSON files in the directory
+ json_files = [f for f in os.listdir(data_dir) if f.endswith('.json')]
+
+ invalid_count = 0 # Track the number of invalid JSON objects
+
+ # Iterate through each JSON file and validate
+ for json_file in json_files:
+ json_file_path = os.path.join(data_dir, json_file)
+ print(f"Validating {json_file_path}...")
+
+ try:
+ json_data = load_json(json_file_path)
+ except Exception as e:
+ print(f"Error loading JSON file {json_file}: {e}")
+ invalid_count += 1
+ continue
+
+ # Check if the JSON data is a list of objects
+ if isinstance(json_data, list):
+ # Iterate through each object in the list
+ for idx, item in enumerate(json_data):
+ errors = list(validator.iter_errors(item))
+ if errors:
+ print(f"Validation failed for object {idx} in {json_file}:")
+ for error in errors:
+ print(f"Error: {error.message}")
+ invalid_count += 1
+ else:
+ # Validate the JSON object itself if it's not a list
+ errors = list(validator.iter_errors(json_data))
+ if errors:
+ print(f"Validation failed for {json_file}:")
+ for error in errors:
+ print(f"Error: {error.message}")
+ invalid_count += 1
+
+ return invalid_count
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser(description="Validate JSON files against a schema.")
+ parser.add_argument(
+ "benchmarks_dir",
+ type=str,
+ help="Path to the directory containing the benchmark JSON files"
+ )
+ args = parser.parse_args()
+ invalid_jsons = validate_json_files(args.benchmarks_dir)
+
+ if invalid_jsons > 0:
+ print(f"{invalid_jsons} JSON object(s) are invalid. Failing the build.")
+ sys.exit(1) # Exit with a non-zero status to fail Jenkins/GitHub Actions
+ else:
+ print("All JSON objects are valid.")
+ sys.exit(0) # Exit with zero status for success
+
diff --git a/docs/sphinx_setup/_static/benchmarks_files/OV-benchmark-data.csv b/docs/sphinx_setup/_static/benchmarks_files/OV-benchmark-data.csv
deleted file mode 100644
index 8422cd5fd89e90..00000000000000
--- a/docs/sphinx_setup/_static/benchmarks_files/OV-benchmark-data.csv
+++ /dev/null
@@ -1,529 +0,0 @@
-Network model,Release,IE-Type,Platform name,Throughput-INT8,Throughput-FP16,Throughput-FP32,Value,Efficiency,Price,TDP,Sockets,Price/Socket,TDP/Socket,Latency_int8,UOM_T,UOM_V,UOM_E,UOM_L,Latency_FP16,Latency_FP32,Latency_int4,Throughput_INT4,Latency_BF16,Throughput_BF16
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,3.26,,2.02,0.049,0.272,67,12,1,67,12,315.92,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,11.76,,4.3,0.11,0.784,107,15,1,107,15,88.1,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,21.35,,15.07,0.182,0.328,117,65,1,117,65,49.16,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,32.86,,21.97,0.154,0.939,214,35,1,214,35,35.85,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,120.78,,47.23,0.367,0.966,329,125,1,329,125,13.44,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,33.55,,22.8,0.175,0.516,192,65,1,192,65,31.48,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,50.9,,18.49,0.119,1.818,426,28,1,426,28,22.7,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,39.95,,13.98,0.082,2.663,490,15,1,490,15,27.82,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,82.93,,33.49,0.165,1.843,502,45,1,502,45,17.18,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,63.56,,25.38,0.132,2.27,480,28,1,480,28,23.81,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,27.49,,18.24,0.091,0.785,303,35,1,303,35,43.18,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,33.21,,21.5,0.068,0.949,488,35,1,488,35,37.87,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,170.19,,67.84,0.284,1.362,599,125,1,599,125,10.91,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,52.74,,35.77,0.089,0.422,594,125,1,594,125,27.29,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,20.85,,14.82,0.084,0.294,249,71,1,249,71,49.89,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,218.84,,80.13,0.07,1.042,3144,210,2,1572,105,14.48,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,601.48,,223.67,0.026,1.467,22920,410,2,11460,205,9.04,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,894.22,,337.83,0.048,1.656,18718,540,2,9359,270,5.5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,2972.17,,475.27,0.139,4.246,21420,700,2,10710,350,4.28,FPS,FPS/$,FPS/TDP,msec.,,,,,5.04,1927.46
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,4715.55,,570.04,0.22,6.737,21420,700,2,10710,350,3.95,FPS,FPS/$,FPS/TDP,msec.,,,,,4.61,3260.84
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,209.23,,76.51,0.103,0.996,2022,210,2,1011,105,15.48,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,438.44,,166.69,0.193,1.461,2274,300,2,1137,150,8.25,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,50.56,,20.03,0.11,1.806,460,28,1,460,28,40.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,839.85,706.25,,0.42,5.599,2000,150,1,2000,150,3.38,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,711.34,624.16,,2.216,4.742,321,150,1,321,150,5.26,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,192.09,148.4,,0.108,2.561,1780,75,1,1780,75,5.51,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,81.73,66.02,,0.178,2.919,460,28,1,460,28,13.37,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,12.93,16.41,,0.193,1.078,67,12,1,67,12,83.83,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,44.9,33,,0.42,2.993,107,15,1,107,15,25.9,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,66.66,53.08,,0.156,2.381,426,28,1,426,28,16.82,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,47.84,40.41,,0.098,3.189,490,15,1,490,15,22.5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,86.13,68.36,,0.172,1.914,502,45,1,502,45,13.13,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,92.13,72.41,,0.192,3.29,480,28,1,480,28,12.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,,108.57,,0,0,460,28,1,460,28,6.96,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,14.64,,9.88,0.219,1.22,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,46.11,,,0.431,3.074,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,87.03,,38.2,0.204,3.108,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,51.43,,20.84,0.105,3.429,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,143.22,,60.62,0.285,3.183,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,100.13,,42.71,0.209,3.576,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-base-cased,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,138.11,,48.42,0.3,4.933,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,0.31,,0.18,0.005,0.026,67,12,1,67,12,3304.37,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,1.17,,0.38,0.011,0.078,107,15,1,107,15,858.92,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,2.08,,1.29,0.018,0.032,117,65,1,117,65,491.91,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,2.98,,1.86,0.014,0.085,214,35,1,214,35,347.44,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,10.75,,3.94,0.033,0.086,329,125,1,329,125,124.32,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,3.21,,1.97,0.017,0.049,192,65,1,192,65,302.72,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,5.04,,1.64,0.012,0.18,426,28,1,426,28,200.02,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,3.74,,1.22,0.008,0.249,490,15,1,490,15,264.44,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,7.87,,2.9,0.016,0.175,502,45,1,502,45,161.59,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,5.91,,2.25,0.012,0.211,480,28,1,480,28,226.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,2.69,,1.6,0.009,0.077,303,35,1,303,35,415.02,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,3.26,,1.94,0.007,0.093,488,35,1,488,35,330,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,15.74,,6.01,0.026,0.126,599,125,1,599,125,92.96,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,4.66,,3.14,0.008,0.037,594,125,1,594,125,223.46,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,2.1,,1.32,0.008,0.03,249,71,1,249,71,485.4,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,21.82,,6.91,0.007,0.104,3144,210,2,1572,105,104.99,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,50.81,,17.69,0.002,0.124,22920,410,2,11460,205,58.04,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,59.07,,28.92,0.003,0.109,18718,540,2,9359,270,39.71,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,241.7,,41.73,0.011,0.345,21420,700,2,10710,350,27.25,FPS,FPS/$,FPS/TDP,msec.,,,,,30.1,217.47
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,307.34,,51.82,0.014,0.439,21420,700,2,10710,350,20.71,FPS,FPS/$,FPS/TDP,msec.,,,,,28.7,275.75
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,20.82,,6.54,0.01,0.099,2022,210,2,1011,105,110.67,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,39.18,,14.68,0.017,0.131,2274,300,2,1137,150,64.75,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,4.98,,1.7,0.011,0.178,460,28,1,460,28,262.35,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,,113.52,,0,0,2000,150,1,2000,150,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,148.65,111.77,,0.463,0.991,321,150,1,321,150,12.72,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,,20.57,,0,0,1780,75,1,1780,75,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,8.71,6.61,,0.019,0.311,460,28,1,460,28,115.92,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,1.45,1.5,,0.022,0.121,67,12,1,67,12,696.86,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,5.06,3.47,,0.047,0.337,107,15,1,107,15,205.3,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,8.48,6.31,,0.02,0.303,426,28,1,426,28,111.11,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,5.15,4.2,,0.011,0.343,490,15,1,490,15,189.18,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,11.21,8.07,,0.022,0.249,502,45,1,502,45,91.51,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,11.03,8.36,,0.023,0.394,480,28,1,480,28,93.15,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,21.19,14.02,,0.046,0.757,460,28,1,460,28,42.33,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,1.1,,0.91,0.016,0.092,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,5.19,,2.26,0.049,0.346,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,8.97,,3.65,0.021,0.32,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,4.5,,1.92,0.009,0.3,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,12.56,,5.39,0.025,0.279,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,8.35,,3.98,0.017,0.298,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-bert-large-uncased-whole-word-masking-squad-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,11.88,,4.18,0.026,0.424,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,7.26,,5.15,0.108,0.605,67,12,1,67,12,140.45,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,18.96,,11.35,0.177,1.264,107,15,1,107,15,56.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,37.43,,27.82,0.32,0.576,117,65,1,117,65,27.61,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,59.59,,32.99,0.278,1.703,214,35,1,214,35,20.7,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,155.55,,92.92,0.473,1.244,329,125,1,329,125,8.99,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,59.54,,42.2,0.31,0.916,192,65,1,192,65,17.66,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,74.71,,41.04,0.175,2.668,426,28,1,426,28,14.74,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,54.64,,21.7,0.112,3.643,490,15,1,490,15,20.45,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,107.81,,60.86,0.215,2.396,502,45,1,502,45,11.68,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,86.06,,44.28,0.179,3.074,480,28,1,480,28,16.19,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,52.67,,38.13,0.174,1.505,303,35,1,303,35,23.68,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,65.21,,41.42,0.134,1.863,488,35,1,488,35,18.82,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,227.72,,124.76,0.38,1.822,599,125,1,599,125,7.26,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,97.26,,46.42,0.164,0.778,594,125,1,594,125,13.55,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,35.94,,30.25,0.144,0.506,249,71,1,249,71,28.6,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,269.14,,167.12,0.086,1.282,3144,210,2,1572,105,10.93,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,576.93,,324.65,0.025,1.407,22920,410,2,11460,205,6.88,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,,,428.13,0,0,18718,540,2,9359,270,4.53,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,1376.84,,816.11,0.064,1.967,21420,700,2,10710,350,5.1,FPS,FPS/$,FPS/TDP,msec.,,,,,5.66,966.53
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,1648.95,,1113.69,0.077,2.356,21420,700,2,10710,350,4.49,FPS,FPS/$,FPS/TDP,msec.,,,,,5,1297.47
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,260.84,,161.22,0.129,1.242,2022,210,2,1011,105,11.32,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,486.64,,288.91,0.214,1.622,2274,300,2,1137,150,5.87,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,38.03,34.74,,0.083,1.358,460,28,1,460,28,27.73,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,858.75,827.7,,0.429,5.725,2000,150,1,2000,150,3.1,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,716.41,667.32,,2.232,4.776,321,150,1,321,150,5.9,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,144.21,128.22,,0.081,1.923,1780,75,1,1780,75,10.8,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,38.03,34.74,,0.083,1.358,460,28,1,460,28,27.73,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,22.31,26.35,,0.333,1.859,67,12,1,67,12,62.81,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,73.74,61.76,,0.689,4.916,107,15,1,107,15,25.31,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,94.77,77.86,,0.222,3.385,426,28,1,426,28,17.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,57.23,41.63,,0.117,3.815,490,15,1,490,15,23.64,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,129.68,103.42,,0.258,2.882,502,45,1,502,45,12.64,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,114.87,91.51,,0.239,4.103,480,28,1,480,28,13.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,178.27,144.02,,0.388,6.367,460,28,1,460,28,10.65,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,23.65,,16.47,0.353,1.971,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,57.12,,33.46,0.534,3.808,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,104.58,,51.73,0.245,3.735,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,58.71,,20.32,0.12,3.914,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,158.02,,60.95,0.315,3.512,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,111.7,,45.07,0.233,3.989,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-efficientdet-d0,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,128.77,,80.73,0.28,4.599,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,0.04,,0.02,0.001,0.003,67,12,1,67,12,20756.21,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,0.16,,0.04,0.001,0.011,107,15,1,107,15,6100.66,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,0.29,,0.14,0.002,0.004,117,65,1,117,65,3391.27,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,0.42,,0.18,0.002,0.012,214,35,1,214,35,2647.63,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,1.59,,0.5,0.005,0.013,329,125,1,329,125,798.54,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,0.46,,0.22,0.002,0.007,192,65,1,192,65,2205.11,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,0.7,,0.19,0.002,0.025,426,28,1,426,28,1430.37,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,0.51,,0.13,0.001,0.034,490,15,1,490,15,1869.06,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,1.19,,0.35,0.002,0.026,502,45,1,502,45,1054.16,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,0.94,,0.27,0.002,0.034,480,28,1,480,28,1410.81,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,0.35,,0.15,0.001,0.01,303,35,1,303,35,3146.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,0.45,,0.17,0.001,0.013,488,35,1,488,35,2494.71,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,2.44,,0.71,0.004,0.02,599,125,1,599,125,654.67,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,0.7,,0.28,0.001,0.006,594,125,1,594,125,1654.57,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,0.28,,0.15,0.001,0.004,249,71,1,249,71,3531.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,3.03,,0.89,0.001,0.014,3144,210,2,1572,105,986.61,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,8.03,,2.27,0,0.02,22920,410,2,11460,205,466.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,13.25,,3.5,0.001,0.025,18718,540,2,9359,270,409.23,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,51.24,,5.16,0.002,0.073,21420,700,2,10710,350,240.56,FPS,FPS/$,FPS/TDP,msec.,,,,,83.34,37.23
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,58.77,,6.46,0.003,0.084,21420,700,2,10710,350,221.12,FPS,FPS/$,FPS/TDP,msec.,,,,,74.8,47.45
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,2.97,,0.86,0.001,0.014,2022,210,2,1011,105,892.99,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,7.05,,1.77,0.003,0.024,2274,300,2,1137,150,487.5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,0.82,,0.2,0.002,0.029,460,28,1,460,28,1606.03,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,32.33,19.72,,0.016,0.216,2000,150,1,2000,150,53.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,28.22,18.49,,0.088,0.188,321,150,1,321,150,54.13,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,5.37,3.35,,0.003,0.072,1780,75,1,1780,75,208.2,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,0.17,0.17,,0.003,0.014,67,12,1,67,12,5905.58,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,,0.54,,0,0,107,15,1,107,15,2140.48,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,,0.92,,0,0,426,28,1,426,28,1142.45,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,,0.59,,0,0,490,15,1,490,15,1640.85,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,,1.18,,0,0,502,45,1,502,45,988.72,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,1.07,1.21,,0.002,0.038,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,1.94,1.52,,0.004,0.069,460,28,1,460,28,492.61,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,0.16,,0.09,0.002,0.013,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,,,0.28,0,0,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,0.44,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,0.66,,0.2,0.001,0.044,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,1.94,,0.65,0.004,0.043,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,1.4,,0.44,0.003,0.05,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,1.57,,0.4,0.003,0.056,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,134.09,,81.38,2.001,11.174,67,12,1,67,12,7.82,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,300.81,,134.07,2.811,20.054,107,15,1,107,15,3.63,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,535.79,,416.49,4.579,8.243,117,65,1,117,65,2.03,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,893.34,,461.21,4.174,25.524,214,35,1,214,35,1.62,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,3001.04,,1342.8,9.122,24.008,329,125,1,329,125,0.7,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,853.9,,639.54,4.447,13.137,192,65,1,192,65,1.38,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,1350.97,,512.94,3.171,48.249,426,28,1,426,28,0.96,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,993.18,,314.6,2.027,66.212,490,15,1,490,15,1.19,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,1884.45,,987.13,3.754,41.877,502,45,1,502,45,0.97,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,1517.61,,735.72,3.162,54.2,480,28,1,480,28,1.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,741.68,,493.25,2.448,21.191,303,35,1,303,35,1.88,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,910.15,,577.75,1.865,26.004,488,35,1,488,35,1.55,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,4268.14,,2048.84,7.125,34.145,599,125,1,599,125,0.61,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,1454,,694.12,2.448,11.632,594,125,1,594,125,1.25,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,520.08,,431.7,2.089,7.325,249,71,1,249,71,2.08,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,5418.66,,1941.13,1.723,25.803,3144,210,2,1572,105,1.48,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,15107.32,,4722.19,0.659,36.847,22920,410,2,11460,205,1.01,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,22868.7,,6891.94,1.222,42.349,18718,540,2,9359,270,0.62,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,38006.61,,10188.1,1.774,54.295,21420,700,2,10710,350,0.74,FPS,FPS/$,FPS/TDP,msec.,,,,,0.72,25079.31
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,41393.18,,16310.7,1.932,59.133,21420,700,2,10710,350,0.7,FPS,FPS/$,FPS/TDP,msec.,,,,,0.77,31297
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,5179.69,,1872.68,2.562,24.665,2022,210,2,1011,105,1.56,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,12253.52,,3580.59,5.389,40.845,2274,300,2,1137,150,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,1462.73,,586.28,3.18,52.24,460,28,1,460,28,1.6,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,6845.46,6005.09,,3.423,45.636,2000,150,1,2000,150,0.6,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,5081.93,4669.96,,15.832,33.88,321,150,1,321,150,1.26,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,1869.24,1581.04,,1.05,24.923,1780,75,1,1780,75,0.75,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,2009.22,1366.26,,4.368,71.758,460,28,1,460,28,0.77,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,189.04,227.15,,2.821,15.753,67,12,1,67,12,7.78,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,679.78,503.94,,6.353,45.319,107,15,1,107,15,2.74,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,805.68,595.56,,1.891,28.774,426,28,1,426,28,1.9,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,618.91,421.77,,1.263,41.261,490,15,1,490,15,1.89,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,1308.79,905.9,,2.607,29.084,502,45,1,502,45,1.08,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,1350.91,873.2,,2.814,48.247,480,28,1,480,28,1.17,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,1435.15,1321.41,,3.12,51.255,460,28,1,460,28,1.22,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,237.42,,163.72,3.544,19.785,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,528.85,,305.77,4.943,35.257,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,1429.38,,604,3.355,51.049,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,1033.83,,276.37,2.11,68.922,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,2409.93,,1066.75,4.801,53.554,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,1673.8,,720.7,3.487,59.779,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-mobilenet-v2,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,3172.02,,1085.69,6.896,113.286,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,19.86,,8.15,0.296,1.655,67,12,1,67,12,51.96,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,51.59,,14.43,0.482,3.439,107,15,1,107,15,19.86,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,96.7,,49.85,0.826,1.488,117,65,1,117,65,10.71,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,144.75,,72.2,0.676,4.136,214,35,1,214,35,8.22,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,545.91,,152.32,1.659,4.367,329,125,1,329,125,2.7,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,151.12,,75.85,0.787,2.325,192,65,1,192,65,7.09,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,224.68,,61.27,0.527,8.024,426,28,1,426,28,4.95,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,175.98,,46.03,0.359,11.732,490,15,1,490,15,6.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,404.07,,103.46,0.805,8.979,502,45,1,502,45,3.42,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,305.86,,81.39,0.637,10.924,480,28,1,480,28,5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,122.06,,60.45,0.403,3.487,303,35,1,303,35,10.02,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,152.83,,71.65,0.313,4.367,488,35,1,488,35,7.68,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,769.05,,235.48,1.284,6.152,599,125,1,599,125,2.15,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,245.47,,121.76,0.413,1.964,594,125,1,594,125,5.29,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,92.48,,49.64,0.371,1.303,249,71,1,249,71,11.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,971.13,,267.05,0.309,4.624,3144,210,2,1572,105,2.97,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,2977.5,,752.45,0.13,7.262,22920,410,2,11460,205,1.63,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,4952.07,,1153.35,0.265,9.171,18718,540,2,9359,270,1.08,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,19173.9,,1590.33,0.895,27.391,21420,700,2,10710,350,1.08,FPS,FPS/$,FPS/TDP,msec.,,,,,1.3,7385.28
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,22488.98,,2013.94,1.05,32.127,21420,700,2,10710,350,1.19,FPS,FPS/$,FPS/TDP,msec.,,,,,1.26,13865.08
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,923.93,,255.78,0.457,4.4,2022,210,2,1011,105,3.15,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,2264.18,,573.77,0.996,7.547,2274,300,2,1137,150,1.55,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,284.64,,69.12,0.619,10.166,460,28,1,460,28,7.65,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,3596.47,2235.26,,1.798,23.976,2000,150,1,2000,150,0.78,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,2926.34,1900.76,,9.116,19.509,321,150,1,321,150,1.45,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,827.25,520.03,,0.465,11.03,1780,75,1,1780,75,1.38,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,779.54,384.38,,1.695,27.841,460,28,1,460,28,1.55,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,48.54,52.54,,0.724,4.045,67,12,1,67,12,22.82,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,208.42,117.48,,1.948,13.895,107,15,1,107,15,6.2,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,282,178.59,,0.662,10.071,426,28,1,426,28,4.5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,202.08,121.5,,0.412,13.472,490,15,1,490,15,5.49,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,385.97,222.58,,0.769,8.577,502,45,1,502,45,3.22,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,395.74,235.71,,0.824,14.134,480,28,1,480,28,3.38,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,,359.69,,0,0,460,28,1,460,28,2.24,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,59.83,,31.4,0.893,4.986,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,200.06,,71.3,1.87,13.337,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,381.34,,121.02,0.895,13.619,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,227.97,,67.08,0.465,15.198,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,610.51,,190.17,1.216,13.567,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,453.08,,138.39,0.944,16.181,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-resnet-50,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,698.6,,171,1.519,24.95,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,0.89,,0.23,0.008,0.059,107,15,1,107,15,19.86,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,1.66,,0.88,0.014,0.026,117,65,1,117,65,10.71,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,2.41,,1.29,0.011,0.069,214,35,1,214,35,8.22,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,8.99,,2.51,0.027,0.072,329,125,1,329,125,2.7,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,2.6,,1.33,0.014,0.04,192,65,1,192,65,7.09,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,3.96,,1.01,0.009,0.141,426,28,1,426,28,4.95,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,3,,0.78,0.006,0.2,490,15,1,490,15,6.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,6.59,,1.87,0.013,0.146,502,45,1,502,45,3.42,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,5.2,,1.48,0.011,0.186,480,28,1,480,28,5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,2.01,,1.06,0.007,0.057,303,35,1,303,35,10.02,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,2.58,,1.29,0.005,0.074,488,35,1,488,35,7.68,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,13.16,,3.9,0.022,0.105,599,125,1,599,125,2.15,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,4.34,,2.29,0.007,0.035,594,125,1,594,125,5.29,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,1.59,,0.86,0.006,0.022,249,71,1,249,71,11.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,17.66,,4.59,0.006,0.084,3144,210,2,1572,105,2.97,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,58.59,,15.11,0.003,0.143,22920,410,2,11460,205,1.63,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,74.84,,20.76,0.004,0.139,18718,540,2,9359,270,1.08,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,430.22,,30.43,0.02,0.615,21420,700,2,10710,350,1.08,FPS,FPS/$,FPS/TDP,msec.,,,,,15.25,204.52
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,518.34,,35.33,0.024,0.74,21420,700,2,10710,350,1.19,FPS,FPS/$,FPS/TDP,msec.,,,,,11.71,246.74
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,16.79,,4.36,0.008,0.08,2022,210,2,1011,105,3.15,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,42.5,,10.54,0.019,0.142,2274,300,2,1137,150,1.55,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,4.76,,1.19,0.01,0.17,460,28,1,460,28,7.65,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,214.75,111.25,,0.107,1.432,2000,150,1,2000,150,0.78,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,154.96,82.83,,0.483,1.033,321,150,1,321,150,1.45,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,33.91,16.76,,0.019,0.452,1780,75,1,1780,75,1.38,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,1.18,1.18,,0.018,0.098,67,12,1,67,12,855.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,5.16,2.78,,0.048,0.344,107,15,1,107,15,207.52,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,8.33,4.69,,0.02,0.298,426,28,1,426,28,116.72,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,5.4,2.99,,0.011,0.36,490,15,1,490,15,163.28,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,10.51,6.1,,0.021,0.234,502,45,1,502,45,99.47,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,11.21,6.38,,0.023,0.4,480,28,1,480,28,94.2,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,19.17,10.55,,0.042,0.685,460,28,1,460,28,55.94,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,1.18,,0.6,0.018,0.098,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,5.41,,1.52,0.051,0.361,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,8.85,,2.46,0.021,0.316,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,4.5,,1.27,0.009,0.3,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,15.75,,4.19,0.031,0.35,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,11.23,,3.17,0.023,0.401,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd-resnet34-1200,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,,,3.22,0,0,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,45.83,,21.64,0.684,3.819,67,12,1,67,12,22.75,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,114.86,,37.01,1.073,7.657,107,15,1,107,15,9.08,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,211.48,,121.15,1.808,3.254,117,65,1,117,65,4.95,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,329.01,,168.64,1.537,9.4,214,35,1,214,35,3.62,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,1090.8,,388.63,3.316,8.726,329,125,1,329,125,1.31,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,335.45,,181.84,1.747,5.161,192,65,1,192,65,3.13,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,516.15,,147.47,1.212,18.434,426,28,1,426,28,2.19,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,395.84,,101.77,0.808,26.389,490,15,1,490,15,2.8,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,800.51,,284.49,1.595,17.789,502,45,1,502,45,1.77,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,636.22,,224.11,1.325,22.722,480,28,1,480,28,2.33,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,276.57,,152.33,0.913,7.902,303,35,1,303,35,4.35,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,354.15,,185.14,0.726,10.119,488,35,1,488,35,3.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,1616.95,,591.05,2.699,12.936,599,125,1,599,125,1.09,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,577.47,,275.24,0.972,4.62,594,125,1,594,125,2.32,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,202.5,,121.7,0.813,2.852,249,71,1,249,71,5.11,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,2063.32,,632.9,0.656,9.825,3144,210,2,1572,105,1.64,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,5992.44,,1641.01,0.261,14.616,22920,410,2,11460,205,1.27,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,10277.09,,1830.01,0.549,19.032,18718,540,2,9359,270,0.72,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,23876.29,,3409.72,1.115,34.109,21420,700,2,10710,350,0.82,FPS,FPS/$,FPS/TDP,msec.,,,,,0.96,12061.06
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,28083.47,,4751.84,1.311,40.119,21420,700,2,10710,350,0.79,FPS,FPS/$,FPS/TDP,msec.,,,,,0.98,17065.33
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,1974.45,,614.94,0.976,9.402,2022,210,2,1011,105,1.79,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,4825.11,,1232.09,2.122,16.084,2274,300,2,1137,150,1.02,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,532.96,,173.77,1.159,19.034,460,28,1,460,28,3.47,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,4086.84,3482.16,,2.043,27.246,2000,150,1,2000,150,0.81,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,3596.27,3019.02,,11.203,23.975,321,150,1,321,150,1.5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,957.79,771.34,,0.538,12.771,1780,75,1,1780,75,1.31,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,761.67,346.76,,1.656,27.203,460,28,1,460,28,1.57,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,92.9,95.58,,1.387,7.742,67,12,1,67,12,13.73,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,404.78,220.86,,3.783,26.985,107,15,1,107,15,4.26,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,498.95,311.82,,1.171,17.82,426,28,1,426,28,3.15,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,375.66,224.2,,0.767,25.044,490,15,1,490,15,3.48,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,767.65,413.05,,1.529,17.059,502,45,1,502,45,1.84,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,740.83,416.8,,1.543,26.458,480,28,1,480,28,2.05,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,954.6,,,2.075,34.093,460,28,1,460,28,1.46,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,112.56,,64.18,1.68,9.38,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,318.86,,138.61,2.98,21.257,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,682.17,,245.09,1.601,24.363,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,473.18,,132.74,0.966,31.545,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,1133.14,,400.02,2.257,25.181,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,837.11,,290.83,1.744,29.897,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-ssd_mobilenet_v1_coco,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,,,332.61,0,0,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,0.39,,0.05,0.006,0.033,67,12,1,67,12,2586.58,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,1.49,,0.37,0.014,0.099,107,15,1,107,15,675.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,2.55,,1.37,0.022,0.039,117,65,1,117,65,397.3,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,3.63,,2.01,0.017,0.104,214,35,1,214,35,315.78,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,12.74,,3.3,0.039,0.102,329,125,1,329,125,93.41,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,3.95,,2.11,0.021,0.061,192,65,1,192,65,248.78,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,6.52,,1.66,0.015,0.233,426,28,1,426,28,156.16,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,5,,1.25,0.01,0.333,490,15,1,490,15,204.41,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,9.34,,2.22,0.019,0.208,502,45,1,502,45,124.12,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,7.34,,1.53,0.015,0.262,480,28,1,480,28,178.78,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,3.07,,1.66,0.01,0.088,303,35,1,303,35,373.06,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,3.8,,1.92,0.008,0.109,488,35,1,488,35,282.41,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,18.7,,4.28,0.031,0.15,599,125,1,599,125,72.13,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,6.15,,3.29,0.01,0.049,594,125,1,594,125,175.44,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,2.45,,1.35,0.01,0.035,249,71,1,249,71,414.33,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,28.77,,7.41,0.009,0.137,3144,210,2,1572,105,71.86,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,97,,22.61,0.004,0.237,22920,410,2,11460,205,24.04,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,123.99,,32.68,0.007,0.23,18718,540,2,9359,270,34.66,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,503.54,,48.03,0.024,0.719,21420,700,2,10710,350,8.3,FPS,FPS/$,FPS/TDP,msec.,,,,,11.83,269.79
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,574.9,,56.8,0.027,0.821,21420,700,2,10710,350,7.98,FPS,FPS/$,FPS/TDP,msec.,,,,,10.02,324.93
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,27.41,,7.05,0.014,0.131,2022,210,2,1011,105,75.55,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,69.98,,16.57,0.031,0.233,2274,300,2,1137,150,31.17,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,6.58,,1.52,0.014,0.235,460,28,1,460,28,182.05,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,,204.99,,0,0,2000,150,1,2000,150,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,277.7,188.53,,0.865,1.851,321,150,1,321,150,6.58,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,,32.84,,0,0,1780,75,1,1780,75,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,,10.36,,0,0,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,1.97,1.98,,0.029,0.164,67,12,1,67,12,508.94,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,8.33,4.34,,0.078,0.555,107,15,1,107,15,121.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,14.8,7.5,,0.035,0.529,426,28,1,426,28,63.56,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,10.19,4.83,,0.021,0.679,490,15,1,490,15,91.36,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,18.34,9.49,,0.037,0.408,502,45,1,502,45,54.7,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,19.51,10.16,,0.041,0.697,480,28,1,480,28,51.82,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,33.4,19.65,,0.073,1.193,460,28,1,460,28,30.63,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,1.19,,0.79,0.018,0.099,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,8.89,,2.56,0.083,0.593,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,15.92,,4.11,0.037,0.569,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,8.06,,2.12,0.016,0.537,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,25.02,,6.11,0.05,0.556,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,19.79,,5.61,0.041,0.707,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-unet-camvid-onnx-0001,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,20.56,,5.59,0.045,0.734,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,22.86,,10.29,0.341,1.905,67,12,1,67,12,45.04,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,55.22,,18.25,0.516,3.681,107,15,1,107,15,18.42,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,111.32,,60.15,0.951,1.713,117,65,1,117,65,9.04,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,167.08,,82.37,0.781,4.774,214,35,1,214,35,6.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,639.9,,199.71,1.945,5.119,329,125,1,329,125,2.36,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,173.16,,90.77,0.902,2.664,192,65,1,192,65,6.04,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,248.01,,77.06,0.582,8.858,426,28,1,426,28,4.26,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,191.62,,56.35,0.391,12.775,490,15,1,490,15,5.59,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,474.39,,139.26,0.945,10.542,502,45,1,502,45,3.03,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,351.38,,107.02,0.732,12.549,480,28,1,480,28,4.16,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,137.3,,67.93,0.453,3.923,303,35,1,303,35,8.23,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,178.48,,72.58,0.366,5.099,488,35,1,488,35,6.35,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,892.12,,279.24,1.489,7.137,599,125,1,599,125,1.83,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,299.22,,120.67,0.504,2.394,594,125,1,594,125,3.93,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,105.72,,60,0.425,1.489,249,71,1,249,71,9.47,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,1040.04,,335.89,0.331,4.953,3144,210,2,1572,105,2.56,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,2865.88,,902.08,0.125,6.99,22920,410,2,11460,205,1.35,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,4537.14,,1352.78,0.242,8.402,18718,540,2,9359,270,0.94,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,10748.45,,2025.44,0.502,15.355,21420,700,2,10710,350,0.93,FPS,FPS/$,FPS/TDP,msec.,,,,,0.86,8380.97
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,14774.31,,2514.85,0.69,21.106,21420,700,2,10710,350,0.89,FPS,FPS/$,FPS/TDP,msec.,,,,,0.95,13583.75
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,1000.57,,320.98,0.495,4.765,2022,210,2,1011,105,2.75,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,2213.65,,697.48,0.973,7.379,2274,300,2,1137,150,1.36,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,315.22,,88.73,0.685,11.258,460,28,1,460,28,5.28,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,3877.32,2885.68,,1.939,25.849,2000,150,1,2000,150,0.89,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,,2516.27,,0,0,321,150,1,321,150,1.34,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,752.44,662.4,,0.423,10.033,1780,75,1,1780,75,1.62,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,390,286.75,,0.848,13.929,460,28,1,460,28,2.87,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,66.76,66.65,,0.996,5.563,67,12,1,67,12,16.51,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,287.41,156.61,,2.686,19.161,107,15,1,107,15,4.91,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,430.76,249.88,,1.011,15.384,426,28,1,426,28,2.94,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,308.4,158.12,,0.629,20.56,490,15,1,490,15,3.4,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,594.39,318.47,,1.184,13.209,502,45,1,502,45,1.97,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,624.53,340.9,,1.301,22.305,480,28,1,480,28,2.15,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,826.33,515.76,,1.796,29.512,460,28,1,460,28,1.38,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,77.4,,40.77,1.155,6.45,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,,,94.11,0,0,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,454.12,,153.66,1.066,16.219,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,267.05,,84.85,0.545,17.803,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,734.88,,260.65,1.464,16.331,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,533.62,,181.41,1.112,19.058,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v3_tiny,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,720.83,,195.52,1.567,25.744,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,atom,Intel® Atom® X6425E CPU-only,10.3,,5.12,0.154,0.858,67,12,1,67,12,99.85,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,atom,Intel® Celeron® 6305E CPU-only,25.81,,9.63,0.241,1.721,107,15,1,107,15,40.3,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i3-8100 CPU-only,53.97,,32.08,0.461,0.83,117,65,1,117,65,18.96,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i5-10500TE CPU-only,82.7,,44.79,0.386,2.363,214,35,1,214,35,13.46,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i5-13600K CPU-only,268.83,,103.8,0.817,2.151,329,125,1,329,125,5.08,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i5-8500 CPU-only,85.16,,49.25,0.444,1.31,192,65,1,192,65,11.75,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i7-1185G7 CPU-only,111.26,,40.73,0.261,3.974,426,28,1,426,28,10.25,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i7-1185GRE CPU-only,78.35,,28.15,0.16,5.223,490,15,1,490,15,13.3,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i7-12700H CPU-only,198.57,,74.1,0.396,4.413,502,45,1,502,45,6.57,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i7-1360P CPU-only,151.4,,58.36,0.315,5.407,480,28,1,480,28,9,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i7-8700T CPU-only,71.72,,41.13,0.237,2.049,303,35,1,303,35,16.37,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i9-10900TE CPU-only,91.39,,49.68,0.187,2.611,488,35,1,488,35,12.63,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,395.18,,157.27,0.66,3.161,599,125,1,599,125,4.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® W1290P CPU-only,142.7,,75.18,0.24,1.142,594,125,1,594,125,8.74,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® E-2124G CPU-only,52.52,,32.77,0.211,0.74,249,71,1,249,71,19.24,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® Gold 5218T CPU-only,445.19,,174.6,0.142,2.12,3144,210,2,1572,105,6.01,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8280 CPU-only,978.66,,462.01,0.043,2.387,22920,410,2,11460,205,3.42,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,1694.55,,504.03,0.091,3.138,18718,540,2,9359,270,2.44,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,2416.63,,952.15,0.113,3.452,21420,700,2,10710,350,3.38,FPS,FPS/$,FPS/TDP,msec.,,,,,2.74,2430.94
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,3263.49,,1247.31,0.152,4.662,21420,700,2,10710,350,3.11,FPS,FPS/$,FPS/TDP,msec.,,,,,2.67,3626.01
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® Silver 4216R CPU-only,425.71,,166.79,0.211,2.027,2022,210,2,1011,105,6.27,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,xeon,Intel® Xeon® Silver 4316 CPU-only,847.39,,339.42,0.373,2.825,2274,300,2,1137,150,3.39,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core,Intel® Core™ Ultra 7 processor 165H CPU-only,128.91,,46.36,0.28,4.604,460,28,1,460,28,15.02,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,1594.8,1469.53,,0.797,10.632,2000,150,1,2000,150,2.07,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,1291.62,1245.08,,4.024,8.611,321,150,1,321,150,3.33,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,329.34,305.95,,0.185,4.391,1780,75,1,1780,75,3.55,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H NPU-only,128.65,131.43,,0.28,4.595,460,28,1,460,28,9.04,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,atom-iGPU,Intel® Atom® X6425E iGPU-only,32.18,33.83,,0.48,2.682,67,12,1,67,12,35.38,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,atom-iGPU,Intel® Celeron® 6305E iGPU-only,122.99,82.4,,1.149,8.199,107,15,1,107,15,10.3,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,168.83,115.09,,0.396,6.03,426,28,1,426,28,7.56,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1185GRE iGPU-only,117.74,77.76,,0.24,7.849,490,15,1,490,15,9.25,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-iGPU,Intel® Core™ i7-12700H iGPU-only,219.9,149.14,,0.438,4.887,502,45,1,502,45,5.5,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,220.96,151.34,,0.46,7.891,480,28,1,480,28,5.62,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,,,,0,0,460,28,1,460,28,3.14,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,atom-CPU+iGPU,Intel® Atom® X6425E CPU+iGPU,36.79,,21.99,0.549,3.066,67,12,1,67,12,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,atom-CPU+iGPU,Intel® Celeron® 6305E CPU+iGPU,114.47,,50.69,1.07,7.631,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,190.89,,80.49,0.448,6.818,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,104.87,,41.37,0.214,6.991,490,15,1,490,15,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-12700H CPU+iGPU,329.58,,122.97,0.657,7.324,502,45,1,502,45,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ i7-1360P CPU+iGPU,238.3,,86.52,0.496,8.511,480,28,1,480,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-yolo_v8n,OV-2024.3.0,core-CPU+iGPU,Intel® Core™ Ultra 7 processor 165H CPU+iGPU,237.05,,105.2,0.515,8.466,460,28,1,460,28,,FPS,FPS/$,FPS/TDP,msec.,,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,,,,
-chatglm2-6b,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,10.3,5.3,,,,599,125,1,599,125,97.07,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,189,,68,14.7,,
-chatglm2-6b,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,22.8,12.6,,,,18718,540,2,18718,270,43.78,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,79,,33,30.3,,
-chatglm2-6b,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,25.8,16.2,,,,21420,350,2,21420,175,38.79,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,62,,29,33.9,,
-chatglm2-6b,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,29.5,18.9,,,,21420,700,2,21420,350,33.86,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,53,,25,39.4,,
-chatglm2-6b,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,39.7,26.3,,,,2000,150,1,2000,150,25.18,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,38,,21,47.9,,
-chatglm2-6b,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,35.4,23.7,,,,321,150,1,321,150,28.26,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,42,,24,42.1,,
-chatglm2-6b,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,,,,,,1900,75,1,1900,75,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,,,,
-chatglm2-6b,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,4.6,,,,,480,28,1,480,28,219.66,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,157,6.4,,
-chatglm2-6b,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,11.2,5.7,,,,460,28,1,460,28,89.29,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,177,,68,14.6,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,,,,
-falcon-7b-instruct,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,9.1,4.6,,,,599,125,1,599,125,109.47,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,217,,69.37,14.4,,
-falcon-7b-instruct,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,19.2,10.7,,,,18718,540,2,18718,270,52.14,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,93,,35.95,27.8,,
-falcon-7b-instruct,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,20.8,13.8,,,,21420,350,2,21420,175,48.13,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,72,,35,28.6,,
-falcon-7b-instruct,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,24,15.6,,,,21420,700,2,21420,350,41.64,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,64,,30.21,33.1,,
-falcon-7b-instruct,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,31.3,20.2,,,,2000,150,1,2000,150,31.9,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,50,,23.45,42.6,,
-falcon-7b-instruct,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,27,18.1,,,,321,150,1,321,150,37.05,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,55,,27.64,36.2,,
-falcon-7b-instruct,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,,,,,,1900,75,1,1900,75,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,176.53,5.7,,
-falcon-7b-instruct,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,,,,,,480,28,1,480,28,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,148.7,6.7,,
-falcon-7b-instruct,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,9.7,5,,,,460,28,1,460,28,102.88,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,198,,70.82,14.1,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,,,,
-llama-2-7b-chat,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,8.7,4.6,,,,599,125,1,599,125,114.85,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,216.88,,77.38,12.9,,
-llama-2-7b-chat,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,18.4,10.5,,,,18718,540,2,18718,270,54.45,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,95.19,,40.46,24.7,,
-llama-2-7b-chat,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,19.6,13.3,,,,21420,350,2,21420,175,51.07,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,74.92,,39.42,25.4,,
-llama-2-7b-chat,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,23.1,15.7,,,,21420,700,2,21420,350,43.3,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,63.79,,31.84,31.4,,
-llama-2-7b-chat,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,33.2,22.5,,,,2000,150,1,2000,150,30.1,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,44.46,,25.04,39.9,,
-llama-2-7b-chat,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,29.3,20.4,,,,321,150,1,321,150,34.09,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,49.06,,28.36,35.3,,
-llama-2-7b-chat,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,3.8,,,,,480,28,1,480,28,263.65,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,180.14,5.6,,
-llama-2-7b-chat,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,9.5,,,,,460,28,1,460,28,105.41,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,78.62,12.7,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,,,,
-mistral-7b-v0.1,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,8.5,4.4,,,,599,125,1,599,125,117.89,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,229.22,,71.71,13.9,,
-mistral-7b-v0.1,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,18,10.1,,,,18718,540,2,18718,270,55.46,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,98.79,,38.25,26.1,,
-mistral-7b-v0.1,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,18.5,12.9,,,,21420,350,2,21420,175,54,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,77.32,,40.07,25,,
-mistral-7b-v0.1,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,21.6,14.7,,,,21420,700,2,21420,350,46.29,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,67.9,,32.48,30.8,,
-mistral-7b-v0.1,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,31.9,19.4,,,,2000,150,1,2000,150,31.34,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,51.61,,24.57,40.7,,
-mistral-7b-v0.1,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,28.1,17.7,,,,321,150,1,321,150,35.58,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,56.57,,27.97,35.8,,
-mistral-7b-v0.1,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,3.8,,,,,480,28,1,480,28,265.63,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,165.02,6.1,,
-mistral-7b-v0.1,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,9.3,4.4,,,,460,28,1,460,28,107.87,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,226.2,,74.39,13.4,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec,,,,,,,,,,,,,,,,,,,,,,,,
-phi3-4k-mini-instruct,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,,,,,,2000,150,1,2000,150,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,19.3,51.9,,
-phi3-4k-mini-instruct,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,,,,,,1900,75,1,1900,75,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,,,53.4,18.7,,
-phi3-4k-mini-instruct,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,,16.8,,,,18718,540,2,9359,270,,tokens/sec,tokens/sec/$,tokens/sec/TDP,msec/token,59.4,,24.7,40.7,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
-begin_rec, , , ,,,,,,,,,,,,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,core,Intel® Core™ i9-13900K CPU-only,,,,,,599,125,1,599,125,41.19,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",39.89,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8380 CPU-only,,,,,,18718,540,2,18718,270,14.84,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",15.48,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8480+ CPU-only,,,,,,21420,350,2,21420,175,3.79,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",3.77,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,xeon,Intel® Xeon® Platinum 8580 CPU-only,,,,,,21420,700,2,21420,350,3.47,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",3.66,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,accel,Intel® Data Center GPU Flex 170 dGPU,,,,,,2000,150,1,2000,150,2.51,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",2.4,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,accel,Intel® Arc™ A770M dGPU,,,,,,321,150,1,321,150,2.87,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",2.72,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,accel,Intel® Data Center GPU Flex 140 dGPU,,,,,,1900,75,1,1900,75,13.59,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",13.31,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,core-iGPU,Intel® Core™ i7-1360P iGPU-only,,,,,,480,28,1,480,28,20.85,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",19.95,,,,,
-stable-diffusion-v2-1,OV-2024.3.0,core-iGPU,Intel® Core™ Ultra 7 processor 165H iGPU-only,,,,,,460,28,1,460,28,12.98,"Generation time, sec.",Generation time/$,Generation time/TDP,"Generation time, sec.",12.41,,,,,
-end_rec,,,,,,,,,,,,,,,,,,,,,,,,
\ No newline at end of file
diff --git a/docs/sphinx_setup/_static/benchmarks_files/OVMS-benchmark-data.csv b/docs/sphinx_setup/_static/benchmarks_files/OVMS-benchmark-data.csv
deleted file mode 100644
index 10f573d9140388..00000000000000
--- a/docs/sphinx_setup/_static/benchmarks_files/OVMS-benchmark-data.csv
+++ /dev/null
@@ -1,78 +0,0 @@
-Network model,Release,IE-Type,Platform name,Throughput-OVMS-INT8,Throughput-OV-INT8,Throughput-OVMS-FP32,Throughput-OV-FP32,UOM_T
-begin_rec,,,,,,,,
-bert-base-cased,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,479.649,482.878,180.7,179.541,FPS
-bert-base-cased,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,428.173,430.397,156.73,159.276,FPS
-bert-base-cased,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,100.783,101.983,35.711,36.35,FPS
-bert-base-cased,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,98.441,102.62,34.303,36.096,FPS
-bert-base-cased,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,26.185,26.436,17.108,17.395,FPS
-end_rec,,,,,,,,
-begin_rec,,,,,,,,
-bert-large-uncased,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,41.872,42.401,14.949,14.473,FPS
-bert-large-uncased,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,37.05,37.864,13.075,13.031,FPS
-bert-large-uncased,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,10.047,10.111,3.259,3.237,FPS
-bert-large-uncased,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,9.961,10.167,3.236,3.224,FPS
-bert-large-uncased,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,2.43,2.427,1.447,1.428,FPS
-end_rec,,,,,,,,
-begin_rec,,,,,,,,
-Efficientdet-D0,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,439.435,485.287,274.772,272.856,FPS
-Efficientdet-D0,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,376.1,415.275,253.829,259.188,FPS
-Efficientdet-D0,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,131.735,148.558,57.036,59.907,FPS
-Efficientdet-D0,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,119.798,140.129,,,FPS
-Efficientdet-D0,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,47.382,50.573,30.226,31.492,FPS
-end_rec,,,,,,,,
-begin_rec,,,,,,,,
-mask_rcnn_resnet50_atrous_coco,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,6.306,6.364,1.96,1.868,FPS
-mask_rcnn_resnet50_atrous_coco,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,5.652,5.771,1.714,1.639,FPS
-mask_rcnn_resnet50_atrous_coco,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,1.309,1.267,0.396,0.371,FPS
-mask_rcnn_resnet50_atrous_coco,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,1.293,1.271,0.355,0.346,FPS
-mask_rcnn_resnet50_atrous_coco,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,0.38,0.352,0.182,0.151,FPS
-end_rec,,,,,,,,
-begin_rec,,,,,,,,
-Mobilenet-V2 ,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,7563.199,12406.597,3336.015,3972.673,FPS
-Mobilenet-V2 ,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,7475.62,10373.146,2934.976,3381.725,FPS
-Mobilenet-V2 ,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,2158.818,2742.363,740.988,874.037,FPS
-Mobilenet-V2 ,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,2042.633,2809.471,631.59,759.984,FPS
-Mobilenet-V2 ,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,614.174,718.416,381.882,455.793,FPS
-end_rec,,,,,,,,
-begin_rec,,,,,,,,
-Resnet-50,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,2356.238,2483.3,628.616,635.411,FPS
-Resnet-50,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,2071.836,2202.317,568.945,575.057,FPS
-Resnet-50,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,440.533,458.665,113.442,116.116,FPS
-Resnet-50,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,441.7,469.848,107.395,113.605,FPS
-Resnet-50,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,114.045,118.024,57.165,58.366,FPS
-end_rec,,,,,,,,
-begin_rec,,,,,,,,
-SSD-Resnet34-1200 ,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,44.499,47.251,12.074,12.167,FPS
-SSD-Resnet34-1200 ,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,38.714,40.662,10.504,10.653,FPS
-SSD-Resnet34-1200 ,OV-2024.3,core,Intel® Core™ i9-11900K CPU-only,7.756,7.818,2.029,2.005,FPS
-SSD-Resnet34-1200 ,OV-2024.3,core,Intel® Core™ i7-11700K CPU-only,7.929,8.032,2.072,2.054,FPS
-SSD-Resnet34-1200 ,OV-2024.3,core,Intel® Core™ i3-10100 CPU-only,1.947,1.937,1.037,1.008,FPS
-end_rec,,,,,,,,
-begin_rec,,,,,,,,
-SSD_Mobilenet_V1_Coco,OV-2024.3,xeon,Intel® Xeon® 8260M CPU-only,4732.691,4875.291,1362.268,1375.237,FPS
-SSD_Mobilenet_V1_Coco,OV-2024.3,xeon,Intel® Xeon® Gold 6238M CPU-only,4168.575,4279.825,1199.883,1226.189,FPS
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diff --git a/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ov.json b/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ov.json
new file mode 100644
index 00000000000000..68f155fdc1dc6c
--- /dev/null
+++ b/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ov.json
@@ -0,0 +1,23904 @@
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diff --git a/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ovms.json b/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ovms.json
new file mode 100644
index 00000000000000..8457e2be7a6f4a
--- /dev/null
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+ {
+ "Platform": "Intel® Core™ i3-10100 CPU-only",
+ "Model": "Yolo_V8n",
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+]
\ No newline at end of file
diff --git a/docs/sphinx_setup/_static/benchmarks_files/graph-config.json b/docs/sphinx_setup/_static/benchmarks_files/graph-config.json
index 8c71e304f7b6ea..df371e23c8e6eb 100644
--- a/docs/sphinx_setup/_static/benchmarks_files/graph-config.json
+++ b/docs/sphinx_setup/_static/benchmarks_files/graph-config.json
@@ -1,8 +1,8 @@
{
"PrecisionsMap": {
- "OV-INT8 (reference)": "ovmsint8",
- "OV-FP32 (reference)": "ovmsfp32",
+ "OVMSINT8": "ovmsint8",
+ "OVMSFP32": "ovmsfp32",
"INT4": "int4",
"INT8": "int8",
"FP16": "fp16",
@@ -28,27 +28,37 @@
"int4": {
"data": null,
"color": "#5bd0f0",
- "label": "int4"
+ "label": "INT4"
},
"int8": {
"data": null,
"color": "#00C7FD",
- "label": "int8"
+ "label": "INT8"
},
"fp16": {
"data": null,
"color": "#009fca",
- "label": "fp16"
+ "label": "FP16"
},
"fp32": {
"data": null,
"color": "#007797",
- "label": "fp32"
+ "label": "FP32"
},
"bf16": {
"data": null,
"color": "#00536a",
- "label": "bf16"
+ "label": "BF16"
+ },
+ "ovmsint8": {
+ "data": null,
+ "color": "#009fca",
+ "label": "FPS( OV Ref. INT8)"
+ },
+ "ovmsfp32": {
+ "data": null,
+ "color": "#00536a",
+ "label": "BF16"
}
},
"Filters": [
diff --git a/docs/sphinx_setup/_static/benchmarks_files/graph-data-ov.json b/docs/sphinx_setup/_static/benchmarks_files/graph-data-ov.json
deleted file mode 100644
index 03b3830103eeba..00000000000000
--- a/docs/sphinx_setup/_static/benchmarks_files/graph-data-ov.json
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@@ -1,22170 +0,0 @@
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diff --git a/docs/sphinx_setup/_static/benchmarks_files/graph-data-ovms.json b/docs/sphinx_setup/_static/benchmarks_files/graph-data-ovms.json
deleted file mode 100644
index 03b3830103eeba..00000000000000
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- "Checked": true,
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- "fp32": 617.19,
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- "Unit": "FPS",
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- "Unit": "ms",
- "UnitDesc": "lower is better"
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- "fp16": "",
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- "fp16": "",
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- "bf16": ""
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- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 500.81,
- "fp16": "",
- "fp32": 302.76,
- "bf16": ""
- }
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- "Unit": "FPS",
- "UnitDesc": "higher is better"
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- "latency": {
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- {
- "int4": "",
- "int8": 5.83,
- "fp16": "",
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- "bf16": ""
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- "Unit": "ms",
- "UnitDesc": "lower is better"
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- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
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- "fp32": 1.76,
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- ],
- "Unit": "FPS",
- "UnitDesc": "higher is better"
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- "latency": {
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- {
- "int4": "",
- "int8": 281.71,
- "fp16": "",
- "fp32": "",
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- }
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- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
- "Model": "mobilenet-v2",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 12272.08,
- "fp16": "",
- "fp32": 3591.32,
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- }
- ],
- "Unit": "FPS",
- "UnitDesc": "higher is better"
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- "latency": {
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- "int8": 0.63,
- "fp16": "",
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- "bf16": ""
- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
- "Model": "resnet-50",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 2264.37,
- "fp16": "",
- "fp32": 569.28,
- "bf16": ""
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- "Unit": "FPS",
- "UnitDesc": "higher is better"
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- "fp16": "",
- "fp32": "",
- "bf16": ""
- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
- "Model": "ssd-resnet34-1200",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": "",
- "fp16": "",
- "fp32": 10.56,
- "bf16": ""
- }
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- "Unit": "FPS",
- "UnitDesc": "higher is better"
- },
- "latency": {
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- {
- "int4": "",
- "int8": "",
- "fp16": "",
- "fp32": "",
- "bf16": ""
- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
- "Model": "ssd_mobilenet_v1_coco",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 4708.99,
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- ],
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- },
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- {
- "int4": "",
- "int8": 1.01,
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- "fp32": "",
- "bf16": ""
- }
- ],
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- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
- "Model": "unet-camvid-onnx-0001",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 70.37,
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- "Unit": "FPS",
- "UnitDesc": "higher is better"
- },
- "latency": {
- "Precisions": [
- {
- "int4": "",
- "int8": 29.89,
- "fp16": "",
- "fp32": "",
- "bf16": ""
- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
- "Model": "yolo_v3_tiny",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 2232.73,
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- },
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- {
- "int4": "",
- "int8": 1.39,
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- "bf16": ""
- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® Silver 4316 CPU-only",
- "Model": "yolo_v8n",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 868.1,
- "fp16": "",
- "fp32": 341.49,
- "bf16": ""
- }
- ],
- "Unit": "FPS",
- "UnitDesc": "higher is better"
- },
- "latency": {
- "Precisions": [
- {
- "int4": "",
- "int8": 3.33,
- "fp16": "",
- "fp32": "",
- "bf16": ""
- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "bert-base-cased",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
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- {
- "int4": "",
- "int8": 52.43,
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- "fp32": 36.18,
- "bf16": ""
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- ],
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- "UnitDesc": "higher is better"
- },
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- {
- "int4": "",
- "int8": 27.41,
- "fp16": "",
- "fp32": "",
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- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "bert-large-uncased-whole-word-masking-squad-0001",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 5.15,
- "fp16": "",
- "fp32": 3.32,
- "bf16": ""
- }
- ],
- "Unit": "FPS",
- "UnitDesc": "higher is better"
- },
- "latency": {
- "Precisions": [
- {
- "int4": "",
- "int8": 257.26,
- "fp16": "",
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- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "efficientdet-d0",
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- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- "throughput": {
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- },
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- "int8": 13.55,
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- }
- ],
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- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "mask_rcnn_resnet50_atrous_coco",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
- "Precisions": [
- {
- "int4": "",
- "int8": 0.75,
- "fp16": "",
- "fp32": 0.28,
- "bf16": ""
- }
- ],
- "Unit": "FPS",
- "UnitDesc": "higher is better"
- },
- "latency": {
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- {
- "int4": "",
- "int8": 1441.58,
- "fp16": "",
- "fp32": "",
- "bf16": ""
- }
- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "mobilenet-v2",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
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- "fp32": 663.43,
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- },
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- "int8": 1.28,
- "fp16": "",
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- "UnitDesc": "lower is better"
- }
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- },
- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- "throughput": {
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- "int8": 244.84,
- "fp16": "",
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- "bf16": ""
- }
- ],
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- "UnitDesc": "higher is better"
- },
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- {
- "int4": "",
- "int8": 5.34,
- "fp16": "",
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- "UnitDesc": "lower is better"
- }
- }
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- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "ssd-resnet34-1200",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- },
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- "UnitDesc": "lower is better"
- }
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- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
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- "UnitDesc": "higher is better"
- },
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- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
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- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- "fp32": 3.31,
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- "UnitDesc": "lower is better"
- }
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- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "yolo_v3_tiny",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
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- {
- "int4": "",
- "int8": 298.95,
- "fp16": "",
- "fp32": 120.89,
- "bf16": ""
- }
- ],
- "Unit": "FPS",
- "UnitDesc": "higher is better"
- },
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- {
- "int4": "",
- "int8": 3.96,
- "fp16": "",
- "fp32": "",
- "bf16": ""
- }
- ],
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- "UnitDesc": "lower is better"
- }
- }
- },
- {
- "Platform": "Intel® Xeon® W1290P CPU-only",
- "Model": "yolo_v8n",
- "Checked": true,
- "PlatformType": "Server Platforms (Intel® Xeon®)",
- "Parameters": {
- "throughput": {
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- {
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- "int8": 134.9,
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- "fp32": 72.23,
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- "Unit": "FPS",
- "UnitDesc": "higher is better"
- },
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- "fp16": "",
- "fp32": "",
- "bf16": ""
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- ],
- "Unit": "ms",
- "UnitDesc": "lower is better"
- }
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- }
-]
\ No newline at end of file
diff --git a/docs/sphinx_setup/_static/css/custom.css b/docs/sphinx_setup/_static/css/custom.css
index f13dc0706f56c0..0c0a1b421b91da 100644
--- a/docs/sphinx_setup/_static/css/custom.css
+++ b/docs/sphinx_setup/_static/css/custom.css
@@ -779,7 +779,7 @@ div.highlight {
.modal-content-grid {
max-height: 400px;
- ;
+ margin-bottom: 20px;
display: grid;
padding-top: .5rem;
grid-template-columns: 1fr;
diff --git a/docs/sphinx_setup/_static/js/graphs.js b/docs/sphinx_setup/_static/js/graphs.js
index e745eca17c2504..62224cedd3b3fb 100644
--- a/docs/sphinx_setup/_static/js/graphs.js
+++ b/docs/sphinx_setup/_static/js/graphs.js
@@ -171,7 +171,8 @@ class ChartDisplay {
$(document).ready(function () {
- $('.ov-toolkit-benchmark-results').on('click', () => showModal());
+ $('.ov-toolkit-benchmark-results').on('click', () => showModal("graph-data-ov.json"));
+ $('.ovms-toolkit-benchmark-results').on('click', () => showModal("graph-data-ovms.json"));
function clickBuildGraphs(graph, appConfig, networkModels, ieTypes, platforms, kpis, precisions) {
renderData(graph, appConfig, networkModels, ieTypes, platforms, kpis, precisions);
$('.modal-footer').show();
@@ -203,10 +204,10 @@ $(document).ready(function () {
$('body').css('overflow', 'auto');
}
- function showModal() {
+ function showModal(file) {
$('body').css('overflow', 'hidden');
- fetch('../_static/benchmarks_files/graph-data-ov.json')
+ fetch('../_static/benchmarks_files/data/'+ file)
.then((response) => response.json())
.then((jsonData) => {
fetch('../_static/benchmarks_files/graph-config.json')
diff --git a/src/bindings/js/node/include/core_wrap.hpp b/src/bindings/js/node/include/core_wrap.hpp
index 29149aaf157ea8..556857ea362311 100644
--- a/src/bindings/js/node/include/core_wrap.hpp
+++ b/src/bindings/js/node/include/core_wrap.hpp
@@ -68,6 +68,8 @@ class CoreWrap : public Napi::ObjectWrap {
Napi::Value set_property(const Napi::CallbackInfo& info);
Napi::Value get_property(const Napi::CallbackInfo& info);
+ Napi::Value query_model(const Napi::CallbackInfo& info);
+
void add_extension(const Napi::CallbackInfo& info);
protected:
Napi::Value compile_model_sync(const Napi::CallbackInfo& info,
diff --git a/src/bindings/js/node/lib/addon.ts b/src/bindings/js/node/lib/addon.ts
index 9ea694c154a641..c2ba1d9c61f1f9 100644
--- a/src/bindings/js/node/lib/addon.ts
+++ b/src/bindings/js/node/lib/addon.ts
@@ -205,6 +205,19 @@ interface Core {
deviceName: string,
properties: { [key: string]: string | number | boolean },
): void;
+ /**
+ * It queries the device if it supports specified model with the specified
+ * properties.
+ * @param model The passed model to query the property.
+ * @param deviceName The name of a device.
+ * @param properties An object with the property name - property value pairs.
+ * An object with the key-value pairs. (property name, property value).
+ */
+ queryModel(
+ model: Model,
+ deviceName: string,
+ properties?: {[key: string]: string | number | boolean},
+ ): {[key: string]: string | number | boolean};
}
interface CoreConstructor {
new(): Core;
diff --git a/src/bindings/js/node/src/core_wrap.cpp b/src/bindings/js/node/src/core_wrap.cpp
index 20422b7d683d3d..12a916b6e77659 100644
--- a/src/bindings/js/node/src/core_wrap.cpp
+++ b/src/bindings/js/node/src/core_wrap.cpp
@@ -57,6 +57,7 @@ Napi::Function CoreWrap::get_class(Napi::Env env) {
InstanceMethod("getVersions", &CoreWrap::get_versions),
InstanceMethod("setProperty", &CoreWrap::set_property),
InstanceMethod("getProperty", &CoreWrap::get_property),
+ InstanceMethod("queryModel", &CoreWrap::query_model),
InstanceMethod("addExtension", &CoreWrap::add_extension)});
}
@@ -463,3 +464,29 @@ void CoreWrap::add_extension(const Napi::CallbackInfo& info) {
reportError(info.Env(), err.what());
}
}
+
+Napi::Value CoreWrap::query_model(const Napi::CallbackInfo& info) {
+ std::vector allowed_signatures;
+ try {
+ if (ov::js::validate(info, allowed_signatures) ||
+ ov::js::validate(info, allowed_signatures)) {
+ ov::AnyMap properties;
+ auto model = Napi::ObjectWrap::Unwrap(info[0].ToObject())->get_model();
+ auto device_name = info[1].ToString();
+ if (info.Length() == 3) {
+ properties = to_anyMap(info.Env(), info[2]);
+ }
+ auto query_result = _core.query_model(model, device_name, properties);
+ Napi::Object result = Napi::Object::New(info.Env());
+ for (const auto& elem : query_result) {
+ result.Set(elem.first, elem.second);
+ }
+ return result;
+ } else {
+ OPENVINO_THROW("'queryModel'", ov::js::get_parameters_error_msg(info, allowed_signatures));
+ }
+ } catch (std::exception& err) {
+ reportError(info.Env(), err.what());
+ return info.Env().Undefined();
+ }
+}
diff --git a/src/bindings/js/node/tests/unit/core.test.js b/src/bindings/js/node/tests/unit/core.test.js
index bec05980c18d6f..fac64e489273b5 100644
--- a/src/bindings/js/node/tests/unit/core.test.js
+++ b/src/bindings/js/node/tests/unit/core.test.js
@@ -4,15 +4,19 @@
const { addon: ov } = require('../..');
const assert = require('assert');
-const { describe, it, beforeEach } = require('node:test');
+const { describe, it, before, beforeEach } = require('node:test');
+const { testModels, isModelAvailable, getModelPath } = require('./utils.js');
describe('ov.Core tests', () => {
-
let core = null;
+ before(async () => {
+ await isModelAvailable(testModels.testModelFP32);
+ });
+
beforeEach(() => {
core = new ov.Core();
});
-
+
it('Core.setProperty()', () => {
const tmpDir = '/tmp';
@@ -72,4 +76,33 @@ describe('ov.Core tests', () => {
/Cannot load library 'not_exists'/
);
});
+
+ it('Core.queryModel() with empty parameters should throw an error', () => {
+ assert.throws(
+ () => core.queryModel().then(),
+ /'queryModel' method called with incorrect parameters./
+ )
+ });
+
+ it('Core.queryModel() with less arguments should throw an error', () => {
+ assert.throws(
+ () => core.queryModel("Unexpected Argument").then(),
+ /'queryModel' method called with incorrect parameters./
+ )
+ });
+
+ it('Core.queryModel() with incorrect arguments should throw an error', () => {
+ const model = core.readModelSync(getModelPath().xml);
+ assert.throws(
+ () => core.queryModel(model, "arg1", "arg2").then(),
+ /'queryModel' method called with incorrect parameters./
+ )
+ });
+
+ it('Core.queryModel() should have device in the result values', () => {
+ const model = core.readModelSync(getModelPath().xml);
+ const device = 'CPU';
+ const query_model = core.queryModel(model, device);
+ assert(Object.values(query_model).includes(device));
+ });
});
diff --git a/src/bindings/python/CMakeLists.txt b/src/bindings/python/CMakeLists.txt
index 666b6bcd0d6969..871eed07ab17d0 100644
--- a/src/bindings/python/CMakeLists.txt
+++ b/src/bindings/python/CMakeLists.txt
@@ -79,7 +79,14 @@ function(ov_check_python_build_conditions)
set(python_debug OFF)
endif()
- if((Python3_Development.Module_FOUND OR Python3_Development_FOUND) AND NOT python_debug)
+ set(is_compiler_supported ON)
+ # Python bindings compiled with the 14.28 toolset (19.28 compiler) could not be imported by another Pybind module linked with OpenVINO
+ if(CMAKE_CXX_COMPILER_ID STREQUAL "MSVC" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 19.29)
+ set(is_compiler_supported OFF)
+ message(${message_mode} "MSVC toolset version 14.28 or lower (19.28 compiler) is not supported. Please update your toolset (${CMAKE_CXX_COMPILER_VERSION}).")
+ endif()
+
+ if((Python3_Development.Module_FOUND OR Python3_Development_FOUND) AND NOT python_debug AND is_compiler_supported)
set(ENABLE_PYTHON_DEFAULT ON PARENT_SCOPE)
else()
set(ENABLE_PYTHON_DEFAULT OFF PARENT_SCOPE)
diff --git a/src/bindings/python/src/openvino/frontend/jax/utils.py b/src/bindings/python/src/openvino/frontend/jax/utils.py
index aa57c6f6836424..4535265d6de082 100644
--- a/src/bindings/python/src/openvino/frontend/jax/utils.py
+++ b/src/bindings/python/src/openvino/frontend/jax/utils.py
@@ -142,21 +142,25 @@ def ivalue_to_constant(ivalue, shared_memory=True):
if ov_type.is_static():
return op.Constant(ov_type, Shape([]), [ivalue]).outputs()
if isinstance(ivalue, (list, tuple)):
+ # TODO 150596: remove this workaround
+ if len(ivalue) == 0:
+ return op.Constant(OVType.i64, Shape([0]), []).outputs()
assert len(ivalue) > 0, "Can't deduce type for empty list"
- if isinstance(ivalue[0], (list, tuple)):
- second_len = len(ivalue[0])
- flattened_ivalue = []
- for value in ivalue:
- assert isinstance(value, (list, tuple)), "Can't deduce type for a list with both list and basic types."
- assert len(value) == second_len or len(value) == 0, "Can't deduce type for nested list with different lengths."
- flattened_ivalue.extend([filter_element(item) for item in value])
- flattened_ivalue = [item for sublist in ivalue for item in sublist]
- ov_type = _get_ov_type_from_value(flattened_ivalue[0])
- assert ov_type.is_static(), f"Can't deduce type {flattened_ivalue[0].__class__} for list"
- return op.Constant(ov_type, Shape([len(ivalue), second_len]), flattened_ivalue).outputs()
- ivalue = [filter_element(item) for item in ivalue]
- ov_type = _get_ov_type_from_value(ivalue[0])
try:
+ if isinstance(ivalue[0], (list, tuple)):
+ second_len = len(ivalue[0])
+ flattened_ivalue = []
+ for value in ivalue:
+ assert isinstance(value, (list, tuple)), "Can't deduce type for a list with both list and basic types."
+ assert len(value) == second_len or len(
+ value) == 0, "Can't deduce type for nested list with different lengths."
+ flattened_ivalue.extend([filter_element(item) for item in value])
+ flattened_ivalue = [item for sublist in ivalue for item in sublist]
+ ov_type = _get_ov_type_from_value(flattened_ivalue[0])
+ assert ov_type.is_static(), f"Can't deduce type {flattened_ivalue[0].__class__} for list"
+ return op.Constant(ov_type, Shape([len(ivalue), second_len]), flattened_ivalue).outputs()
+ ivalue = [filter_element(item) for item in ivalue]
+ ov_type = _get_ov_type_from_value(ivalue[0])
assert ov_type.is_static(), f"Can't deduce type {ivalue[0].__class__} for list"
except:
# TODO 150596: remove this workaround
diff --git a/src/common/transformations/include/transformations/common_optimizations/nop_elimination.hpp b/src/common/transformations/include/transformations/common_optimizations/nop_elimination.hpp
index ce07b9bd93020d..76190906d157e2 100644
--- a/src/common/transformations/include/transformations/common_optimizations/nop_elimination.hpp
+++ b/src/common/transformations/include/transformations/common_optimizations/nop_elimination.hpp
@@ -15,6 +15,7 @@ class TRANSFORMATIONS_API EliminateConvert;
class TRANSFORMATIONS_API EliminateConvertNonZero;
class TRANSFORMATIONS_API EliminateEltwise;
class TRANSFORMATIONS_API EliminateScatterUpdate;
+class TRANSFORMATIONS_API EliminateReduceReshape;
class TRANSFORMATIONS_API EliminatePad;
class TRANSFORMATIONS_API EliminateSplit;
class TRANSFORMATIONS_API EliminateSplitConcat;
@@ -32,6 +33,16 @@ class TRANSFORMATIONS_API PrepareShapeOpsForEliminationAroundBE;
} // namespace pass
} // namespace ov
+/**
+ * @ingroup ov_transformation_common_api
+ * @brief EliminateReduceReshape eliminates Reshape from Reduce -> Reshape pattern
+ */
+class ov::pass::EliminateReduceReshape : public ov::pass::MatcherPass {
+public:
+ OPENVINO_RTTI("EliminateReduceReshape", "0");
+ EliminateReduceReshape();
+};
+
/**
* @ingroup ov_transformation_common_api
* @brief EliminatePad eliminates pad that does nothing
diff --git a/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp b/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp
index 782c25c2bf03ae..b5527d8672effe 100644
--- a/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp
+++ b/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp
@@ -36,6 +36,7 @@
#include "openvino/op/tile.hpp"
#include "openvino/op/transpose.hpp"
#include "openvino/op/unsqueeze.hpp"
+#include "openvino/op/util/arithmetic_reductions_keep_dims.hpp"
#include "openvino/op/util/binary_elementwise_comparison.hpp"
#include "openvino/op/util/binary_elementwise_logical.hpp"
#include "openvino/op/util/op_types.hpp"
@@ -345,6 +346,59 @@ SIMPLE_MATCHER_PASS_DEFINITION(EliminateGather,
ov::op::v7::Gather,
ov::op::v8::Gather);
+pass::EliminateReduceReshape::EliminateReduceReshape() {
+ MATCHER_SCOPE(EliminateReduceReshape);
+ using namespace pass::pattern;
+ auto axes = wrap_type();
+ auto reduce_pattern = wrap_type({any_input(), axes});
+ auto requested_shape_pattern = wrap_type();
+ auto reshape_pattern =
+ wrap_type({reduce_pattern, requested_shape_pattern}, consumers_count(1));
+
+ matcher_pass_callback callback = [=](Matcher& m) {
+ auto pattern_map = m.get_pattern_map();
+ auto reshape_node = m.get_match_root();
+ auto reduce_node = pattern_map.at(reduce_pattern);
+
+ auto reshape = ov::as_type_ptr(reshape_node);
+ auto reduce = ov::as_type_ptr(reduce_node);
+ if (!reshape || !reduce) {
+ return false;
+ }
+
+ auto in_rank = reshape->get_input_partial_shape(0).rank();
+ auto out_rank = reshape->get_output_partial_shape(0).rank();
+ if (in_rank.is_dynamic() || out_rank.is_dynamic() || in_rank.get_length() != out_rank.get_length()) {
+ return false;
+ }
+
+ auto requested_shape = ov::as_type_ptr(pattern_map.at(requested_shape_pattern));
+ if (!requested_shape) {
+ return false;
+ }
+
+ auto requested_shape_vec = requested_shape->cast_vector();
+ auto axes = reduce->get_reduction_axes();
+
+ int cnt_dyn = 0;
+ for (size_t i = 0; i < requested_shape_vec.size(); ++i) {
+ // if we use reshape special zero or this dim was reduced
+ cnt_dyn += !((requested_shape_vec[i] == 0 && reshape->get_special_zero()) ||
+ (axes.count(i) && requested_shape_vec[i] == 1));
+ }
+
+ // if the number of dyn dims here is equal to 0 or 1, we can unambiguously define output shape
+ if (cnt_dyn <= 1) {
+ return replace_output_update_name(reshape->output(0), reshape->input_value(0));
+ } else {
+ return false;
+ }
+ };
+
+ auto m = make_shared(reshape_pattern, matcher_name);
+ this->register_matcher(m, callback);
+}
+
pass::EliminatePad::EliminatePad() {
MATCHER_SCOPE(EliminatePad);
auto pad_node_pattern = pattern::wrap_type();
@@ -1072,6 +1126,7 @@ ov::pass::PrepareShapeOpsForEliminationAroundBE::PrepareShapeOpsForEliminationAr
ov::pass::NopElimination::NopElimination(bool use_shape_for_elimination) {
// shape-agnostic transformations
ADD_MATCHER_FOR_THIS(EliminatePad)
+ ADD_MATCHER_FOR_THIS(EliminateReduceReshape)
ADD_MATCHER_FOR_THIS(EliminateConvert)
ADD_MATCHER_FOR_THIS(EliminateConvertNonZero)
ADD_MATCHER_FOR_THIS(EliminateConcat)
diff --git a/src/common/transformations/tests/common_optimizations/nop_elimination.cpp b/src/common/transformations/tests/common_optimizations/nop_elimination.cpp
index 9ee362104b24d0..19b5fefd79b9b0 100644
--- a/src/common/transformations/tests/common_optimizations/nop_elimination.cpp
+++ b/src/common/transformations/tests/common_optimizations/nop_elimination.cpp
@@ -233,7 +233,7 @@ TEST(nop_elimination, squeeze_unsqueeze_elimination_dynamic_without_squeeze_axis
EXPECT_NO_THROW(pass_manager.run_passes(f));
}
-TEST(nop_elimination, reshape_elimination_v1_dynamic) {
+TEST(nop_elimination, reshape_elimination_v1_dynamic_negative) {
auto arg = std::make_shared(element::i64, PartialShape::dynamic());
auto pattern = make_shared(element::i64, PartialShape::dynamic(1));
auto reshape_v1 = std::make_shared(arg, pattern, false);
@@ -245,6 +245,34 @@ TEST(nop_elimination, reshape_elimination_v1_dynamic) {
ASSERT_TRUE(count_ops_of_type(f) == 1);
}
+TEST(nop_elimination, reshape_arithmetical_reduce_elimination_dynamic) {
+ auto arg = std::make_shared(element::i64, PartialShape({-1, 96, 100, 100}));
+ auto reduce_axes = ov::op::v0::Constant::create(element::i64, Shape{2}, {2, 3});
+ auto reduce = std::make_shared(arg, reduce_axes, true);
+ auto pattern = op::v0::Constant::create(element::i64, Shape{4}, {0, 96, 1, 1});
+ auto reshape_v1 = std::make_shared(reduce, pattern, true);
+ auto abs = std::make_shared(reshape_v1);
+ auto f = std::make_shared(NodeVector{abs}, ParameterVector{arg});
+ pass::Manager pass_manager;
+ pass_manager.register_pass(false);
+ pass_manager.run_passes(f);
+ ASSERT_TRUE(count_ops_of_type(f) == 0);
+}
+
+TEST(nop_elimination, reshape_logical_reduce_elimination_dynamic) {
+ auto arg = std::make_shared(element::boolean, PartialShape({-1, 96, 100, 100}));
+ auto reduce_axes = ov::op::v0::Constant::create(element::i64, Shape{2}, {2, 3});
+ auto reduce = std::make_shared(arg, reduce_axes, true);
+ auto pattern = op::v0::Constant::create(element::i64, Shape{4}, {0, 96, 1, 1});
+ auto reshape_v1 = std::make_shared(reduce, pattern, true);
+ auto nz = std::make_shared(reshape_v1);
+ auto f = std::make_shared(NodeVector{nz}, ParameterVector{arg});
+ pass::Manager pass_manager;
+ pass_manager.register_pass(false);
+ pass_manager.run_passes(f);
+ ASSERT_TRUE(count_ops_of_type(f) == 0);
+}
+
TEST(nop_elimination, reshape_elimination_v1_check_consumer_count) {
std::shared_ptr f;
{
diff --git a/src/core/include/openvino/op/util/arithmetic_reduction.hpp b/src/core/include/openvino/op/util/arithmetic_reduction.hpp
index 365444418429b8..1def85392ebfc2 100644
--- a/src/core/include/openvino/op/util/arithmetic_reduction.hpp
+++ b/src/core/include/openvino/op/util/arithmetic_reduction.hpp
@@ -25,7 +25,7 @@ class OPENVINO_API ArithmeticReduction : public ReductionBase {
ArithmeticReduction(const Output& arg, const Output& reduction_axes);
public:
- OPENVINO_OP("ArithmeticReduction", "util");
+ OPENVINO_OP("ArithmeticReduction", "util", ReductionBase);
void validate_and_infer_types() override;
};
} // namespace util
diff --git a/src/core/include/openvino/op/util/arithmetic_reductions_keep_dims.hpp b/src/core/include/openvino/op/util/arithmetic_reductions_keep_dims.hpp
index 7eca3778f2760b..ced3382787f02d 100644
--- a/src/core/include/openvino/op/util/arithmetic_reductions_keep_dims.hpp
+++ b/src/core/include/openvino/op/util/arithmetic_reductions_keep_dims.hpp
@@ -21,7 +21,7 @@ class OPENVINO_API ArithmeticReductionKeepDims : public util::ArithmeticReductio
bool visit_attributes(AttributeVisitor& visitor) override;
public:
- OPENVINO_OP("ArithmeticReductionKeepDims", "util");
+ OPENVINO_OP("ArithmeticReductionKeepDims", "util", util::ArithmeticReduction);
void validate_and_infer_types() override;
/// \return If set to 1 it holds axes that are used for reduction.
diff --git a/src/core/include/openvino/op/util/logical_reduction.hpp b/src/core/include/openvino/op/util/logical_reduction.hpp
index 1059dd922fdc68..747a1af6401ee0 100644
--- a/src/core/include/openvino/op/util/logical_reduction.hpp
+++ b/src/core/include/openvino/op/util/logical_reduction.hpp
@@ -29,7 +29,7 @@ class OPENVINO_API LogicalReduction : public ReductionBase {
LogicalReduction(const Output& arg, const Output& reduction_axes);
public:
- OPENVINO_OP("LogicalReduction", "util");
+ OPENVINO_OP("LogicalReduction", "util", ReductionBase);
void validate_and_infer_types() override;
};
} // namespace util
diff --git a/src/core/include/openvino/op/util/logical_reduction_keep_dims.hpp b/src/core/include/openvino/op/util/logical_reduction_keep_dims.hpp
index cfa03130d44031..85ffae909a91f4 100644
--- a/src/core/include/openvino/op/util/logical_reduction_keep_dims.hpp
+++ b/src/core/include/openvino/op/util/logical_reduction_keep_dims.hpp
@@ -22,7 +22,7 @@ class OPENVINO_API LogicalReductionKeepDims : public util::LogicalReduction {
bool visit_attributes(AttributeVisitor& visitor) override;
public:
- OPENVINO_OP("LogicalReductionKeepDims", "util");
+ OPENVINO_OP("LogicalReductionKeepDims", "util", util::LogicalReduction);
void validate_and_infer_types() override;
/// \return If set to 1 it holds axes that are used for reduction.
diff --git a/src/frontends/jax/src/op_table.cpp b/src/frontends/jax/src/op_table.cpp
index 762d216e81e81c..f7db07afe67f36 100644
--- a/src/frontends/jax/src/op_table.cpp
+++ b/src/frontends/jax/src/op_table.cpp
@@ -6,6 +6,7 @@
#include "openvino/op/add.hpp"
#include "openvino/op/divide.hpp"
+#include "openvino/op/erf.hpp"
#include "openvino/op/exp.hpp"
#include "openvino/op/maximum.hpp"
#include "openvino/op/multiply.hpp"
@@ -59,6 +60,7 @@ const std::map get_supported_ops_jaxpr() {
{"device_put", op::skip_node},
{"div", op::translate_1to1_match_2_inputs},
{"dot_general", op::translate_dot_general},
+ {"erf", op::translate_1to1_match_1_input},
{"exp", op::translate_1to1_match_1_input},
{"integer_pow", op::translate_integer_pow},
{"max", op::translate_1to1_match_2_inputs},
diff --git a/src/frontends/tensorflow/docs/supported_ops.md b/src/frontends/tensorflow/docs/supported_ops.md
index 1affaa2640cbea..31f871aca4fdef 100644
--- a/src/frontends/tensorflow/docs/supported_ops.md
+++ b/src/frontends/tensorflow/docs/supported_ops.md
@@ -1130,7 +1130,7 @@ A "supported operation" is one that TensorFlow Frontend can convert to the OpenV
| SparseReduceSumSparse | NO | |
| SparseReorder | NO | |
| SparseReshape | YES | |
-| SparseSegmentMean | NO | |
+| SparseSegmentMean | YES | |
| SparseSegmentMeanGrad | NO | |
| SparseSegmentMeanGradV2 | NO | |
| SparseSegmentMeanWithNumSegments | NO | |
diff --git a/src/frontends/tensorflow/src/op_table.cpp b/src/frontends/tensorflow/src/op_table.cpp
index 0a1baf3034df42..c2bf460b02b19a 100644
--- a/src/frontends/tensorflow/src/op_table.cpp
+++ b/src/frontends/tensorflow/src/op_table.cpp
@@ -379,6 +379,7 @@ const std::map get_supported_ops() {
{"Softmax", CreatorFunction(translate_softmax_op)},
{"SpaceToDepth", CreatorFunction(translate_space_to_depth_op)},
{"SparseReshape", CreatorFunction(translate_sparse_reshape_op)},
+ {"SparseSegmentMean", CreatorFunction(translate_sparse_segment_mean_op)},
{"SparseTensorDenseAdd", CreatorFunction(translate_sparse_tensor_dense_add_op)},
{"SparseTensorDenseMatMul", CreatorFunction(translate_sparse_tensor_dense_mat_mul_op)},
{"SparseToDense", CreatorFunction(translate_sparse_to_dense_op)},
diff --git a/src/frontends/tensorflow_common/include/common_op_table.hpp b/src/frontends/tensorflow_common/include/common_op_table.hpp
index a59a5db7dfa080..1fa3386fce47af 100644
--- a/src/frontends/tensorflow_common/include/common_op_table.hpp
+++ b/src/frontends/tensorflow_common/include/common_op_table.hpp
@@ -148,6 +148,7 @@ OP_CONVERTER(translate_rsqrt_op);
OP_CONVERTER(translate_scatter_nd_op);
OP_CONVERTER(translate_segment_sum_op);
OP_CONVERTER(translate_space_to_batch_nd_op);
+OP_CONVERTER(translate_sparse_segment_mean_op);
OP_CONVERTER(translate_sparse_tensor_dense_add_op);
OP_CONVERTER(translate_sparse_tensor_dense_mat_mul_op);
OP_CONVERTER(translate_sparse_to_dense_op);
diff --git a/src/frontends/tensorflow_common/src/op/sparse_segment_mean.cpp b/src/frontends/tensorflow_common/src/op/sparse_segment_mean.cpp
new file mode 100644
index 00000000000000..d275f3a3460ce5
--- /dev/null
+++ b/src/frontends/tensorflow_common/src/op/sparse_segment_mean.cpp
@@ -0,0 +1,75 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "common_op_table.hpp"
+#include "openvino/op/add.hpp"
+#include "openvino/op/broadcast.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/convert.hpp"
+#include "openvino/op/divide.hpp"
+#include "openvino/op/embedding_segments_sum.hpp"
+#include "openvino/op/gather.hpp"
+#include "openvino/op/reshape.hpp"
+#include "openvino/op/scatter_update.hpp"
+#include "openvino/op/shape_of.hpp"
+#include "openvino/op/squeeze.hpp"
+#include "openvino/op/subtract.hpp"
+#include "openvino/op/transpose.hpp"
+#include "openvino/op/unique.hpp"
+#include "utils.hpp"
+
+using namespace std;
+using namespace ov::op;
+
+namespace ov {
+namespace frontend {
+namespace tensorflow {
+namespace op {
+OutputVector translate_sparse_segment_mean_op(const NodeContext& node) {
+ default_op_checks(node, 3, {"SparseSegmentMean"});
+ auto data = node.get_input(0);
+ auto indices = std::make_shared(node.get_input(1), element::i64);
+ auto segment_ids = std::make_shared(node.get_input(2), element::i64);
+ auto data_rank = std::make_shared(std::make_shared(node.get_input(0)));
+
+ // get the last index from segment_ids
+ auto segments_ids_size = std::make_shared(segment_ids, element::i64);
+ auto const_one = create_same_type_const(indices, vector{1}, Shape{1});
+ auto const_zero = create_same_type_const(indices, vector{0}, Shape{1});
+ auto last_idx = std::make_shared(segments_ids_size, const_one);
+
+ // segment_ids are always sorted, so the last index from segment_ids can be used to determine the number of output
+ // segments.
+ auto last_segment_idx = std::make_shared(segment_ids, last_idx, const_zero);
+ auto n_segments = std::make_shared(last_segment_idx, const_one);
+
+ // get sums of sparse segments
+ auto embedding_segments_sum =
+ make_shared(data, indices, segment_ids, std::make_shared(n_segments));
+
+ // get the sizes of each segment
+ auto unique_segment_ids = make_shared(segment_ids, true, element::i64, element::i64);
+ auto broadcast = make_shared(const_one, n_segments);
+ auto divisors = make_shared(broadcast,
+ unique_segment_ids->output(0),
+ unique_segment_ids->output(3),
+ const_zero);
+ auto divisors_with_correct_type = make_shared(divisors, data);
+ auto divisors_shape = make_shared(make_shared(const_one, data_rank),
+ const_zero,
+ n_segments,
+ const_zero);
+ auto divisors_with_correct_shape = std::make_shared(divisors_with_correct_type, divisors_shape, false);
+
+ // divide the sums by the size of the segments
+ auto mean = std::make_shared(embedding_segments_sum, divisors_with_correct_shape);
+
+ set_node_name(node.get_name(), mean);
+ return {mean};
+}
+
+} // namespace op
+} // namespace tensorflow
+} // namespace frontend
+} // namespace ov
diff --git a/src/plugins/intel_gpu/docs/gpu_plugin_driver_troubleshooting.md b/src/plugins/intel_gpu/docs/gpu_plugin_driver_troubleshooting.md
index ee97b2060ecae3..7e0accf1d07f36 100644
--- a/src/plugins/intel_gpu/docs/gpu_plugin_driver_troubleshooting.md
+++ b/src/plugins/intel_gpu/docs/gpu_plugin_driver_troubleshooting.md
@@ -71,8 +71,7 @@ $ ./hello_query_device.py
## 8. If you have errors with OpenCL headers in application build
OpenCL headers should be installed in your system to build application using OpenCL objects. OpenVINO source code distribution contains OpenCL headers thirdparty/ocl/cl_headers. Alternatively you can
-install them from [OpenCL Git](https://github.com/KhronosGroup/OpenCL-Headers)
-
+install them from [OpenCL Git](https://github.com/KhronosGroup/OpenCL-Headers). To ensure compatibility, make sure that the installed version of OpenCL headers had been released before the OpenVINO version you are using.
## See also
* [Overview for OpenCL on Linux and troubleshoot](https://bashbaug.github.io/opencl/2019/07/06/OpenCL-On-Linux.html)
diff --git a/src/plugins/intel_gpu/src/graph/impls/cpu/broadcast.cpp b/src/plugins/intel_gpu/src/graph/impls/cpu/broadcast.cpp
index 79a6b77f442cba..2701a57001eb93 100644
--- a/src/plugins/intel_gpu/src/graph/impls/cpu/broadcast.cpp
+++ b/src/plugins/intel_gpu/src/graph/impls/cpu/broadcast.cpp
@@ -45,14 +45,14 @@ struct broadcast_impl : public typed_primitive_impl {
void save(BinaryOutputBuffer& ob) const override {
parent::save(ob);
ob << make_data(&broadcast_mode, sizeof(ov::op::BroadcastModeSpec));
- ob << make_data(&target_shape, sizeof(ov::Shape));
+ ob << target_shape;
ob << axes_mapping;
}
void load(BinaryInputBuffer& ib) override {
parent::load(ib);
ib >> make_data(&broadcast_mode, sizeof(ov::op::BroadcastModeSpec));
- ib >> make_data(&target_shape, sizeof(ov::Shape));
+ ib >> target_shape;
ib >> axes_mapping;
}
diff --git a/src/plugins/intel_gpu/src/graph/impls/ocl/paged_attention.cpp b/src/plugins/intel_gpu/src/graph/impls/ocl/paged_attention.cpp
index 7b5df754023a4a..cfc1e17c87ac6e 100644
--- a/src/plugins/intel_gpu/src/graph/impls/ocl/paged_attention.cpp
+++ b/src/plugins/intel_gpu/src/graph/impls/ocl/paged_attention.cpp
@@ -52,6 +52,15 @@ struct paged_attention_impl : multi_stage_primitive {
PA_SDPA,
};
+ bool requires_update(primitive_inst& inst, const kernel_impl_params& impl_params) const override {
+ const auto stage = get_paged_attention_stage(impl_params);
+
+ // In case of MIXED mode execution Paged Attention may require dispatch data update and internal
+ // buffers reallocation even if the input shapes haven't been changed. Therefore, check the current execution
+ // mode and update parameters if needed
+ return stage == PagedAttentionStage::MIXED;
+ }
+
void load(BinaryInputBuffer& ib) override {
parent::load(ib);
if (is_dynamic()) {
@@ -90,7 +99,7 @@ struct paged_attention_impl : multi_stage_primitive {
return layouts;
}
- kernel_arguments_data get_arguments(const paged_attention_inst& instance, size_t stage, size_t kernel_idx) const {
+ kernel_arguments_data get_arguments(const paged_attention_inst& instance, size_t stage, size_t kernel_idx, bool is_mixed_mode) const {
const auto desc = instance.get_node().as().get_primitive();
kernel_arguments_data args;
@@ -129,7 +138,7 @@ struct paged_attention_impl : multi_stage_primitive {
instance.block_indices_memory_ptr(),
instance.block_indices_begins_memory_ptr() };
- if (kernel_idx == 1) {
+ if (is_mixed_mode) {
// Multi tokens kernel version has additional subsequence_begins_memory memory
// dependency
args.inputs.push_back(instance.subsequence_begins_memory_ptr());
@@ -140,6 +149,12 @@ struct paged_attention_impl : multi_stage_primitive {
}
} else {
args.inputs = { instance.past_lens_memory_ptr() };
+
+ if (is_mixed_mode) {
+ // Multi tokens kernel version has additional subsequence_begins_memory memory
+ // dependency
+ args.inputs.push_back(instance.subsequence_begins_memory_ptr());
+ }
}
args.outputs = { instance.output_memory_ptr(0) };
@@ -153,7 +168,11 @@ struct paged_attention_impl : multi_stage_primitive {
6, /* PA_SDPA multiple tokens mode */ };
};
- void execute_stage(const std::vector& events, paged_attention_inst& instance, std::vector& all_events, size_t stage) {
+ void execute_stage(const std::vector& events,
+ paged_attention_inst& instance,
+ std::vector& all_events,
+ size_t stage,
+ bool is_mixed_mode) {
stream& stream = instance.get_network().get_stream();
std::vector tmp_events(events);
size_t kernel_offset = 0;
@@ -181,7 +200,7 @@ struct paged_attention_impl : multi_stage_primitive {
auto& params = _kernels_data[stage].kernels[kd_idx].params;
- auto args = get_arguments(instance, stage, kd_idx);
+ auto args = get_arguments(instance, stage, kd_idx, is_mixed_mode);
args.scalars = ¶ms.scalars;
const auto& intermediate_memories = instance.get_intermediates_memories();
@@ -211,14 +230,15 @@ struct paged_attention_impl : multi_stage_primitive {
event::ptr execute_impl(const std::vector& events, paged_attention_inst& instance) override {
std::vector res_events;
const auto stage = get_paged_attention_stage(*instance.get_impl_params());
+ const auto is_mixed_mode = stage == PagedAttentionStage::MIXED;
- execute_stage(events, instance, res_events, Stage::KV_CACHE_UPDATE);
+ execute_stage(events, instance, res_events, Stage::KV_CACHE_UPDATE, is_mixed_mode);
std::vector dep_events(res_events.begin(), res_events.end());
if (stage == PagedAttentionStage::PREFILL) {
- execute_stage(dep_events, instance, res_events, Stage::SDPA);
+ execute_stage(dep_events, instance, res_events, Stage::SDPA, is_mixed_mode);
} else if (stage == PagedAttentionStage::GENERATE || stage == PagedAttentionStage::MIXED) {
- execute_stage(dep_events, instance, res_events, Stage::PA_SDPA);
+ execute_stage(dep_events, instance, res_events, Stage::PA_SDPA, is_mixed_mode);
}
return instance.get_network().get_stream().aggregate_events(res_events, res_events.size() > 1);
@@ -248,9 +268,45 @@ struct paged_attention_impl : multi_stage_primitive {
mem_lock subsequence_begins_mem_lock(subsequence_begins_mem, *impl_param.strm);
auto aligned_seq_len = 0;
- for (size_t i = 0; i < subsequence_begins_mem_lock.size() - 1; i++) {
- auto prompt_length = subsequence_begins_mem_lock[i + 1] - subsequence_begins_mem_lock[i];
- aligned_seq_len += align_to(prompt_length, target_seq_len_block_size);
+ if (stage == PagedAttentionStage::MIXED) {
+ const auto past_lens_idx = 5;
+ const auto past_lens_mem = input_mem.at(past_lens_idx);
+ mem_lock past_lens_mem_lock(past_lens_mem, *impl_param.strm);
+
+ for (size_t i = 0; i < subsequence_begins_mem_lock.size() - 1; i++) {
+ auto past_len = past_lens_mem_lock[i];
+ auto seq_length = subsequence_begins_mem_lock[i + 1] - subsequence_begins_mem_lock[i];
+
+ // Since in MIXED execution mode the present KV-cache can be appended to the past KV-cache at any offset inside block,
+ // to ensure proper alignment and update_kv_cache kernel scheduling, we need to account for the number of unaligned tokens
+ // in the first block
+ // For example, if we need to store values in the following slots:
+ //
+ // block0: |O|O|O|O|O|O|O|O|O|O|O|O|U|U|U|U|
+ // block1: |U|U|U|U|U|U|U|U|U|U|U|U|U|U|U|U|
+ // block2: |U|U|U|U|U|U|E|E|E|E|E|E|E|E|E|E|
+ // Where O - occupied slots, U - currently beeing updated slots, E - empty slots
+ //
+ // We need to schedule 3 update_kv_cache operations:
+ // - For ranges of block0: [12-15]
+ // - For ranges of block1: [0-15]
+ // - For ranges of block2: [0-5]
+ //
+ // Therefore, consider an additional increment of aligned_seq_len to properly process all the blocks
+
+ auto occupied_slots_num = past_len % target_seq_len_block_size;
+ if (past_len != 0 && seq_length + occupied_slots_num > target_seq_len_block_size) {
+ aligned_seq_len += target_seq_len_block_size;
+ seq_length -= target_seq_len_block_size - occupied_slots_num;
+ }
+
+ aligned_seq_len += align_to(seq_length, target_seq_len_block_size);
+ }
+ } else {
+ for (size_t i = 0; i < subsequence_begins_mem_lock.size() - 1; i++) {
+ auto prompt_length = subsequence_begins_mem_lock[i + 1] - subsequence_begins_mem_lock[i];
+ aligned_seq_len += align_to(prompt_length, target_seq_len_block_size);
+ }
}
return aligned_seq_len;
diff --git a/src/plugins/intel_gpu/src/graph/include/primitive_inst.h b/src/plugins/intel_gpu/src/graph/include/primitive_inst.h
index 6efb2c4c03644f..e4e00e75182bae 100644
--- a/src/plugins/intel_gpu/src/graph/include/primitive_inst.h
+++ b/src/plugins/intel_gpu/src/graph/include/primitive_inst.h
@@ -110,6 +110,11 @@ struct primitive_impl {
OPENVINO_ASSERT(false, "[GPU] update() is not implemented for dynamic implemenation ", _kernel_name);
}
+ virtual bool requires_update(primitive_inst& inst, const kernel_impl_params& impl_params) const {
+ OPENVINO_ASSERT(_is_dynamic, "[GPU] requires_update() is called for static shape implementation ", _kernel_name);
+ return false;
+ }
+
static kernel_impl_params static_canonicalize_shapes(const kernel_impl_params& impl_params);
virtual kernel_impl_params canonicalize_shapes(const kernel_impl_params& impl_params) const {
diff --git a/src/plugins/intel_gpu/src/graph/loop.cpp b/src/plugins/intel_gpu/src/graph/loop.cpp
index 51a7f5f0040a8f..57f52a412dfd17 100644
--- a/src/plugins/intel_gpu/src/graph/loop.cpp
+++ b/src/plugins/intel_gpu/src/graph/loop.cpp
@@ -445,8 +445,7 @@ void loop_inst::preprocess_output_memory(const int64_t num_iterations) {
auto memory_mapping_info = create_concat_memory_map(output_mapping, memory, num_iterations);
concatenated_output_mem_mappings.push_back(memory_mapping_info);
GPU_DEBUG_LOG << i << ") generate concat output memory mapping: " << memory_mapping_info->to_string() << std::endl;
- }
- GPU_DEBUG_IF(iter != concatenated_output_mem_mappings.end()) {
+ } else {
GPU_DEBUG_LOG << i << ") memory_mapping_info is already existed : " << (*iter)->to_string() << std::endl;
}
}
diff --git a/src/plugins/intel_gpu/src/graph/paged_attention.cpp b/src/plugins/intel_gpu/src/graph/paged_attention.cpp
index 037a6a1e8b04aa..787fd184f75b6a 100644
--- a/src/plugins/intel_gpu/src/graph/paged_attention.cpp
+++ b/src/plugins/intel_gpu/src/graph/paged_attention.cpp
@@ -93,6 +93,7 @@ void paged_attention_inst::on_execute() {
const auto blocks_indexes_end_idx = 1;
const auto blocked_gws_subseq_mapping_idx = 2;
+ const auto past_lens_mem = past_lens_memory_ptr();
auto subsequence_begins_mem = subsequence_begins_memory_ptr();
auto blocks_indexes_start_mem = _intermediates_memory[blocks_indexes_start_idx];
auto blocks_indexes_end_mem = _intermediates_memory[blocks_indexes_end_idx];
@@ -101,6 +102,7 @@ void paged_attention_inst::on_execute() {
OPENVINO_ASSERT(subsequence_begins_mem->get_layout().data_type == data_types::i32);
auto& stream = get_network().get_stream();
+ mem_lock past_lens_mem_lock(past_lens_mem, stream);
mem_lock subsequence_begins_mem_lock(subsequence_begins_mem, stream);
mem_lock blocks_indexes_start_lock(blocks_indexes_start_mem, stream);
mem_lock blocks_indexes_end_lock(blocks_indexes_end_mem, stream);
@@ -120,11 +122,28 @@ void paged_attention_inst::on_execute() {
size_t index = 0;
const auto target_seq_len_block_size = 16; // TODO: Get block size from the impl
for (size_t i = 0; i < subsequence_begins_mem_lock.size() - 1; i++) {
+ const auto past_len = past_lens_mem_lock[i];
const auto seq_start = subsequence_begins_mem_lock[i];
const auto seq_end = subsequence_begins_mem_lock[i + 1];
const auto seq_length = seq_end - seq_start;
- for (int32_t j = 0; j < seq_length; j += target_seq_len_block_size) {
+ int32_t j = 0;
+ if (past_len != 0) {
+ auto block_start_pos = seq_start;
+ auto empty_slots = target_seq_len_block_size - (past_len % target_seq_len_block_size);
+ auto block_end_pos = seq_start + std::min(empty_slots, seq_length);
+
+ blocks_indexes_start_lock[index] = block_start_pos;
+ blocks_indexes_end_lock[index] = block_end_pos;
+ blocked_gws_subseq_mapping_mem_lock[index] = static_cast(i);
+
+ index++;
+
+ auto added_slots = block_end_pos - block_start_pos;
+ j += added_slots;
+ }
+
+ for (; j < seq_length; j += target_seq_len_block_size) {
auto block_start_pos = subsequence_begins_mem_lock[i] + j;
auto block_end_pos = std::min(block_start_pos + target_seq_len_block_size, seq_end);
diff --git a/src/plugins/intel_gpu/src/graph/primitive_inst.cpp b/src/plugins/intel_gpu/src/graph/primitive_inst.cpp
index 2ebe53620161f8..af99500afb6225 100644
--- a/src/plugins/intel_gpu/src/graph/primitive_inst.cpp
+++ b/src/plugins/intel_gpu/src/graph/primitive_inst.cpp
@@ -1648,6 +1648,7 @@ event::ptr primitive_inst::execute(const std::vector& events) {
// Try update impl if current impl is dynamic because opt kernel may be added to impl cache through async compilation.
// Only try update weight and realloc when impl is updated.
const bool can_use_async_compilation = use_async_compilation();
+ bool is_updated = false;
if (shape_changed() || !_impl || (!shape_changed() && _impl->is_dynamic() && can_use_async_compilation)) {
if (update_impl(can_use_async_compilation)) {
need_args_update = true;
@@ -1657,9 +1658,22 @@ event::ptr primitive_inst::execute(const std::vector& events) {
auto ev_reset = realloc_if_needed();
if (ev_reset)
dependencies.push_back(ev_reset);
+
+ is_updated = true;
}
}
+ // Paged Attention may require dispatch data update and internal buffers reallocation
+ // even if the input shapes haven't been changed
+ if (_node->is_type() && !is_updated && _impl->requires_update(*this, *_impl_params)) {
+ _impl->update(*this, *_impl_params);
+
+ need_args_update = true;
+ auto ev_reset = realloc_if_needed();
+ if (ev_reset)
+ dependencies.push_back(ev_reset);
+ }
+
OPENVINO_ASSERT(_impl_params->get_output_layout().is_static(),
"[GPU] Can't execute ", primitive_id, " primitive as output layout is dynamic in runtime");
}
diff --git a/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_kv_cache_update_ref.cl b/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_kv_cache_update_ref.cl
index d41e3fd5fc9a80..ef2f78496b2cf2 100644
--- a/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_kv_cache_update_ref.cl
+++ b/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_kv_cache_update_ref.cl
@@ -4,6 +4,8 @@
#include "include/batch_headers/common.cl"
+REQD_SUB_GROUP_SIZE(SUBGROUP_SIZE)
+__attribute__((reqd_work_group_size(1, 1, SUBGROUP_SIZE)))
KERNEL(pa_kv_cache_update)(
OPTIONAL_SHAPE_INFO_ARG
__global const INPUT0_TYPE* key_data,
@@ -77,20 +79,25 @@ KERNEL(pa_kv_cache_update)(
const uint block_start_pos = blocked_indexes_start[block_idx];
const uint block_end_pos = blocked_indexes_end[block_idx];
const uint tokens_num = block_end_pos - block_start_pos;
+ const uint past_len = past_lens[subsequence_idx];
+
+ const uint token_start_pos = (past_len + block_start_pos - subsequence_begin_idx) % PAGED_ATTENTION_BLOCK_SIZE;
uint key_value_in_offset = block_start_pos * KV_HEADS_NUM * HEAD_SIZE +
head_idx * HEAD_SIZE;
- const uint cached_blocks_num = past_lens[subsequence_idx] / PAGED_ATTENTION_BLOCK_SIZE;
- const uint current_block_idx = (block_start_pos - subsequence_begin_idx) / PAGED_ATTENTION_BLOCK_SIZE;
+ const uint current_block_idx = (past_len + block_start_pos - subsequence_begin_idx) / PAGED_ATTENTION_BLOCK_SIZE;
- const uint block_offset = block_indices_begins[subsequence_idx] + cached_blocks_num + current_block_idx;
+ const uint block_offset = block_indices_begins[subsequence_idx] + current_block_idx;
uint key_out_offset = block_indices[block_offset] * KV_HEADS_NUM * HEAD_SIZE * PAGED_ATTENTION_BLOCK_SIZE +
head_idx * HEAD_SIZE * PAGED_ATTENTION_BLOCK_SIZE;
uint value_out_offset = key_out_offset;
+ key_out_offset += token_start_pos;
+ value_out_offset += token_start_pos * HEAD_SIZE;
+
if (tokens_num == PAGED_ATTENTION_BLOCK_SIZE) {
unroll_for (uint token_num = 0; token_num < PAGED_ATTENTION_BLOCK_SIZE; token_num++) {
uint head_idx_index = 0;
diff --git a/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_sdpa_opt.cl b/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_sdpa_opt.cl
index 06e83c5adb3e6b..22b561e3d78661 100644
--- a/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_sdpa_opt.cl
+++ b/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/pa_sdpa_opt.cl
@@ -215,7 +215,11 @@ KERNEL(pa_sdpa_opt)(
// TODO: const uint global_data_idx = partition_idx * SEQ_LEN_PARTITION_SIZE + local_data_idx
const uint global_data_idx = partition_idx * SEQ_LEN_PARTITION_SIZE + qk_idx * (SUBGROUPS_PER_WG * SUBGROUP_SIZE) + sgid * SUBGROUP_SIZE + sglid;
+#if SEQ_LEN_PARTITION_SIZE % SUBGROUPS_PER_WG * SUBGROUP_SIZE == 0
if (global_data_idx < seq_len) {
+#else
+ if (global_data_idx < seq_len && local_data_idx < SEQ_LEN_PARTITION_SIZE) {
+#endif
SOFTMAX_ACCUMULATOR_TYPE qk_new = native_exp(TO_SOFTMAX_ACCUMULATOR_TYPE(slm_qk_vals[local_data_idx]) - qk_max);
slm_qk_vals[local_data_idx] = TO_OUTPUT_TYPE(qk_new);
@@ -242,7 +246,11 @@ KERNEL(pa_sdpa_opt)(
const uint local_data_idx = qk_idx * (SUBGROUPS_PER_WG * SUBGROUP_SIZE) + sgid * SUBGROUP_SIZE + sglid;
const uint global_data_idx = partition_idx * SEQ_LEN_PARTITION_SIZE + qk_idx * (SUBGROUPS_PER_WG * SUBGROUP_SIZE) + sgid * SUBGROUP_SIZE + sglid;
+#if SEQ_LEN_PARTITION_SIZE % SUBGROUPS_PER_WG * SUBGROUP_SIZE == 0
if (global_data_idx < seq_len) {
+#else
+ if (global_data_idx < seq_len && local_data_idx < SEQ_LEN_PARTITION_SIZE) {
+#endif
SOFTMAX_ACCUMULATOR_TYPE qk_new = TO_SOFTMAX_ACCUMULATOR_TYPE(slm_qk_vals[local_data_idx]) / exp_sum;
slm_qk_vals[local_data_idx] = TO_OUTPUT_TYPE(qk_new);
}
@@ -351,17 +359,29 @@ KERNEL(pa_sdpa_opt)(
REQD_SUB_GROUP_SIZE(SUBGROUP_SIZE)
KERNEL(pa_sdpa_finalization_stage)(
const __global INPUT3_TYPE* past_lens,
+#if MULTI_TOKENS_PROCESSING
+ const __global INPUT6_TYPE* subsequence_begins,
+#endif
__global OUTPUT_TYPE* output,
const __global SOFTMAX_ACCUMULATOR_TYPE* exp_sums,
const __global SOFTMAX_ACCUMULATOR_TYPE* max_logits,
const __global OUTPUT_TYPE* tmp_out,
+#if MULTI_TOKENS_PROCESSING
+ const __global int* gws_subseq_mapping,
+#endif
const uint total_partitions_num) {
const uint seq_idx = get_global_id(0);
const uint head_num_idx = get_global_id(1);
const uint head_size_idx = get_global_id(2);
const uint sglid = get_sub_group_local_id();
+#if MULTI_TOKENS_PROCESSING
+ const int subsequence_idx = gws_subseq_mapping[seq_idx];
+ const int subsequence_begin = subsequence_begins[subsequence_idx];
+ const uint seq_len = past_lens[subsequence_idx] + 1 + (seq_idx - subsequence_begin);
+#else
const uint seq_len = past_lens[seq_idx] + 1;
+#endif
const uint num_of_partitions = CEIL_DIV(seq_len, SEQ_LEN_PARTITION_SIZE);
diff --git a/src/plugins/intel_gpu/src/kernel_selector/kernels/sdpa/pa_sdpa_kernel_opt.cpp b/src/plugins/intel_gpu/src/kernel_selector/kernels/sdpa/pa_sdpa_kernel_opt.cpp
index 2f8ced75052c4f..161c37ab3d3bf7 100644
--- a/src/plugins/intel_gpu/src/kernel_selector/kernels/sdpa/pa_sdpa_kernel_opt.cpp
+++ b/src/plugins/intel_gpu/src/kernel_selector/kernels/sdpa/pa_sdpa_kernel_opt.cpp
@@ -14,6 +14,7 @@ enum KernelsTypes {
SINGLE_TOKEN = 0,
MULTI_TOKENS,
FINALIZATION,
+ FINALIZATION_MULTI_TOKENS,
TOTAL_KERNELS_NUM
};
@@ -32,6 +33,8 @@ static std::string GetKernelName(std::string base_name, KernelsTypes type) {
kernel_name += "_multi_tokens_seq";
} else if (type == KernelsTypes::FINALIZATION) {
kernel_name += "_finalization";
+ } else if (type == KernelsTypes::FINALIZATION_MULTI_TOKENS) {
+ kernel_name += "_finalization_multi_tokens_seq";
}
return kernel_name;
@@ -45,7 +48,8 @@ KernelsData PagedAttentionSDPAKernelOpt::GetKernelsData(const Params& p) const {
const auto& params = static_cast(p);
const std::vector kernels_type = { KernelsTypes::SINGLE_TOKEN,
KernelsTypes::MULTI_TOKENS,
- KernelsTypes::FINALIZATION };
+ KernelsTypes::FINALIZATION,
+ KernelsTypes::FINALIZATION_MULTI_TOKENS };
KernelData kd = KernelData::Default(params, kernels_type.size());
kd.needs_sub_kernels_sync = true;
@@ -68,6 +72,9 @@ KernelsData PagedAttentionSDPAKernelOpt::GetKernelsData(const Params& p) const {
} else if (kernel_type == KernelsTypes::FINALIZATION) {
// FINALIZATION kernel uses only the past_lens data input
inputs_num = 1;
+ } else if (kernel_type == KernelsTypes::FINALIZATION_MULTI_TOKENS) {
+ // FINALIZATION_MULTI_TOKENS kernel uses past_lens data input and subsequence_begins
+ inputs_num = 2;
}
auto& kernel = kd.kernels[kd_kernels_idx++];
@@ -89,11 +96,13 @@ KernelsData PagedAttentionSDPAKernelOpt::GetKernelsData(const Params& p) const {
kernel.params.arguments.push_back({ArgumentDescriptor::Types::INTERNAL_BUFFER, 1});
kernel.params.arguments.push_back({ArgumentDescriptor::Types::INTERNAL_BUFFER, 2});
- if (kernel_type == KernelsTypes::MULTI_TOKENS) {
+ if (kernel_type == KernelsTypes::MULTI_TOKENS || kernel_type == KernelsTypes::FINALIZATION_MULTI_TOKENS) {
// MULTIPLE_TOKENS kernels needs additional information related to mapping
// launched kernel instances to subsequence indexes
kernel.params.arguments.push_back({ArgumentDescriptor::Types::INTERNAL_BUFFER, 3});
- } else if (kernel_type == KernelsTypes::FINALIZATION) {
+ }
+
+ if (kernel_type == KernelsTypes::FINALIZATION || kernel_type == KernelsTypes::FINALIZATION_MULTI_TOKENS) {
kernel.params.arguments.push_back({ArgumentDescriptor::Types::SCALAR, 0});
// Remove unused shape_info argument at finalization stage
@@ -164,7 +173,7 @@ JitConstants PagedAttentionSDPAKernelOpt::GetJitConstants(const pa_sdpa_params&
jit.AddConstant(MakeJitConstant("BROADCAST_GROUP_SIZE", config.group_size));
}
- auto sdpa_stage = kernel_idx == KernelsTypes::FINALIZATION ? 1 : 0;
+ auto sdpa_stage = kernel_idx == KernelsTypes::FINALIZATION || kernel_idx == KernelsTypes::FINALIZATION_MULTI_TOKENS ? 1 : 0;
jit.AddConstant(MakeJitConstant("SDPA_STAGE_" + std::to_string(sdpa_stage), 1));
if (config.has_scale_val)
@@ -173,7 +182,7 @@ JitConstants PagedAttentionSDPAKernelOpt::GetJitConstants(const pa_sdpa_params&
if (params.conf.has_alibi_input)
jit.AddConstant(MakeJitConstant("HAS_ALIBI", 1));
- if (kernel_idx == KernelsTypes::MULTI_TOKENS)
+ if (kernel_idx == KernelsTypes::MULTI_TOKENS || kernel_idx == KernelsTypes::FINALIZATION_MULTI_TOKENS)
jit.AddConstant(MakeJitConstant("MULTI_TOKENS_PROCESSING", 1));
jit.Merge(MakeTypeJitConstants(softmax_acc_dt, "SOFTMAX_ACCUMULATOR"));
@@ -211,7 +220,7 @@ void PagedAttentionSDPAKernelOpt::GetUpdateDispatchDataFunc(KernelData& kd) cons
kd.update_dispatch_data_func = [](const Params& params, KernelData& kd) {
const auto& prim_params = static_cast(params);
- const size_t expected_kernels_num = 3;
+ const size_t expected_kernels_num = 4;
OPENVINO_ASSERT(kd.kernels.size() == expected_kernels_num, "[GPU] Invalid kernels size for update dispatch data func of SDPA kernel");
auto dispatch_data1 = SetDefault(prim_params, KernelsTypes::SINGLE_TOKEN);
@@ -230,13 +239,19 @@ void PagedAttentionSDPAKernelOpt::GetUpdateDispatchDataFunc(KernelData& kd) cons
auto dispatch_data2 = SetDefault(prim_params, KernelsTypes::FINALIZATION);
kd.kernels[KernelsTypes::FINALIZATION].params.workGroups.global = dispatch_data2.gws;
kd.kernels[KernelsTypes::FINALIZATION].params.workGroups.local = dispatch_data2.lws;
- kd.kernels[KernelsTypes::FINALIZATION].skip_execution = num_of_partitions == 1;
+ kd.kernels[KernelsTypes::FINALIZATION].skip_execution = num_of_partitions == 1 || prim_params.multi_tokens_mode;
+
+ kd.kernels[KernelsTypes::FINALIZATION_MULTI_TOKENS].params.workGroups.global = dispatch_data2.gws;
+ kd.kernels[KernelsTypes::FINALIZATION_MULTI_TOKENS].params.workGroups.local = dispatch_data2.lws;
+ kd.kernels[KernelsTypes::FINALIZATION_MULTI_TOKENS].skip_execution = num_of_partitions == 1 || !prim_params.multi_tokens_mode;
ScalarDescriptor num_of_partitions_scalar;
num_of_partitions_scalar.t = ScalarDescriptor::Types::UINT32;
num_of_partitions_scalar.v.u32 = static_cast(num_of_partitions);
kd.kernels[KernelsTypes::FINALIZATION].params.scalars.resize(1);
kd.kernels[KernelsTypes::FINALIZATION].params.scalars[0] = num_of_partitions_scalar;
+ kd.kernels[KernelsTypes::FINALIZATION_MULTI_TOKENS].params.scalars.resize(1);
+ kd.kernels[KernelsTypes::FINALIZATION_MULTI_TOKENS].params.scalars[0] = num_of_partitions_scalar;
auto buf_dt_size = BytesPerElement(softmax_acc_dt);
auto buf_elements_count = sequences_number * prim_params.conf.heads_num * num_of_partitions;
diff --git a/src/plugins/intel_gpu/src/plugin/ops/constant.cpp b/src/plugins/intel_gpu/src/plugin/ops/constant.cpp
index f87c2b39848d09..a947bdf585125b 100644
--- a/src/plugins/intel_gpu/src/plugin/ops/constant.cpp
+++ b/src/plugins/intel_gpu/src/plugin/ops/constant.cpp
@@ -22,6 +22,7 @@
#include "openvino/op/util/op_types.hpp"
#include "openvino/op/loop.hpp"
#include "openvino/op/tensor_iterator.hpp"
+#include "openvino/op/bucketize.hpp"
#include "openvino/op/util/binary_elementwise_bitwise.hpp"
#include "intel_gpu/primitives/data.hpp"
@@ -80,11 +81,6 @@ static void create_data(ProgramBuilder& p, const ov::Shape& const_shape, const s
constTensor.feature[0] = 1;
}
- // If const_shape has a dimension = 0, then create tensor with single value
- // TODO: check if dim=0 is a valid case
- if (std::accumulate(const_shape.begin(), const_shape.end(), size_t(1), std::multiplies()) == 0)
- constTensor = cldnn::tensor{1};
-
cldnn::data_types out_dtype = cldnn::element_type_to_data_type(op->get_output_element_type(0));
cldnn::layout constLayout = p.use_new_shape_infer() ? cldnn::layout(const_shape, out_dtype, constFormat) :
cldnn::layout(out_dtype, constFormat, constTensor);
@@ -134,7 +130,6 @@ static bool is_btiwise(Node* node) {
static void CreateConstantOp(ProgramBuilder& p, const std::shared_ptr& op) {
ov::Shape constDims = op->get_shape();
auto constUsers = op->get_output_target_inputs(0);
-
std::unordered_map, ConstProperties> consts = {
{op, {false}}
};
diff --git a/src/plugins/intel_gpu/src/plugin/transformations/bcast_and_pad_zp_buffers.cpp b/src/plugins/intel_gpu/src/plugin/transformations/bcast_and_pad_zp_buffers.cpp
index c35816b7d3febc..9e85fbbb535946 100644
--- a/src/plugins/intel_gpu/src/plugin/transformations/bcast_and_pad_zp_buffers.cpp
+++ b/src/plugins/intel_gpu/src/plugin/transformations/bcast_and_pad_zp_buffers.cpp
@@ -75,34 +75,39 @@ bool all_same_value(const T* qp_ptr, size_t size) {
});
}
-std::shared_ptr scalar_parameter(std::shared_ptr qp) {
+template
+std::shared_ptr
+create_scalar_constant(const std::shared_ptr& qp) {
auto type = qp->get_element_type();
- size_t size = ov::shape_size(qp->get_shape());
- bool has_same_value = false;
- switch (type) {
- case ov::element::u8:
- has_same_value = all_same_value(static_cast(qp->get_data_ptr()), size);
- break;
- case ov::element::i8:
- has_same_value = all_same_value(static_cast(qp->get_data_ptr()), size);
- break;
- case ov::element::f16:
- has_same_value = all_same_value(static_cast(qp->get_data_ptr()), size);
- break;
- case ov::element::f32:
- has_same_value = all_same_value(static_cast(qp->get_data_ptr()), size);
- break;
- default: OPENVINO_THROW("[GPU] Can't pad quantization parameter for ", type, " element type");
+ auto shape = qp->get_shape();
+ if (all_same_value(static_cast(qp->get_data_ptr()), ov::shape_size(shape))) {
+ ov::Shape new_shape(shape.size(), 1);
+ ov::Tensor new_tensor(type, new_shape);
+ auto new_qp = std::make_shared(new_tensor);
+ auto val = qp->get_vector()[0];
+ new_qp->fill_data(type, val);
+ return new_qp;
}
+ return nullptr;
+}
- if (has_same_value) {
- auto new_shape = qp->get_shape();
- std::fill(new_shape.begin(), new_shape.end(), 1);
- ov::Tensor new_qp(type, new_shape);
- return std::make_shared(new_qp);
+std::shared_ptr scalar_parameter(std::shared_ptr qp) {
+ auto type = qp->get_element_type();
+ std::shared_ptr new_qp = nullptr;
+
+ if (type == ov::element::u8) {
+ new_qp = create_scalar_constant(qp);
+ } else if (type == ov::element::i8) {
+ new_qp = create_scalar_constant(qp);
+ } else if (type == ov::element::f16) {
+ new_qp = create_scalar_constant(qp);
+ } else if (type == ov::element::f32) {
+ new_qp = create_scalar_constant(qp);
+ } else {
+ OPENVINO_THROW("[GPU] Can't pad quantization parameter for ", type, " element type");
}
- return nullptr;
+ return new_qp;
}
} // namespace
diff --git a/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/bucketize.cpp b/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/bucketize.cpp
index 89da385392745f..15f39f9f635546 100644
--- a/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/bucketize.cpp
+++ b/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/bucketize.cpp
@@ -106,4 +106,44 @@ INSTANTIATE_TEST_SUITE_P(smoke_Bucketize_input_u8,
testing::Values(ov::test::utils::DEVICE_GPU)),
BucketizeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Bucketize_empty_boundary_f16,
+ BucketizeLayerTest,
+ testing::Combine(testing::Values(ov::test::static_shapes_to_test_representation({{6, 7, 3, 2, 8, 5}, {0}})),
+ testing::ValuesIn(with_right_bound),
+ testing::Values(ov::element::f16),
+ testing::Values(ov::element::f16),
+ testing::ValuesIn(out_precision),
+ testing::Values(ov::test::utils::DEVICE_GPU)),
+ BucketizeLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Bucketize_empty_boundary_f32,
+ BucketizeLayerTest,
+ testing::Combine(testing::Values(ov::test::static_shapes_to_test_representation({{6, 7, 3, 2, 8, 5}, {0}})),
+ testing::ValuesIn(with_right_bound),
+ testing::Values(ov::element::f32),
+ testing::Values(ov::element::f32),
+ testing::ValuesIn(out_precision),
+ testing::Values(ov::test::utils::DEVICE_GPU)),
+ BucketizeLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Bucketize_empty_boundary_i8,
+ BucketizeLayerTest,
+ testing::Combine(testing::Values(ov::test::static_shapes_to_test_representation({{6, 7, 3, 2, 8, 5}, {0}})),
+ testing::ValuesIn(with_right_bound),
+ testing::Values(ov::element::i8),
+ testing::Values(ov::element::i8),
+ testing::ValuesIn(out_precision),
+ testing::Values(ov::test::utils::DEVICE_GPU)),
+ BucketizeLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Bucketize_empty_boundary_u8,
+ BucketizeLayerTest,
+ testing::Combine(testing::Values(ov::test::static_shapes_to_test_representation({{6, 7, 3, 2, 8, 5}, {0}})),
+ testing::ValuesIn(with_right_bound),
+ testing::Values(ov::element::u8),
+ testing::Values(ov::element::u8),
+ testing::ValuesIn(out_precision),
+ testing::Values(ov::test::utils::DEVICE_GPU)),
+ BucketizeLayerTest::getTestCaseName);
+
} // namespace
diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/bucketize.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/bucketize.cpp
new file mode 100644
index 00000000000000..d65f4ea51c9f1d
--- /dev/null
+++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/bucketize.cpp
@@ -0,0 +1,154 @@
+// Copyright (C) 2018-2022 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+#include
+
+#include "common_test_utils/ov_tensor_utils.hpp"
+#include "shared_test_classes/base/ov_subgraph.hpp"
+
+#include "openvino/op/parameter.hpp"
+#include "openvino/op/result.hpp"
+#include "openvino/op/bucketize.hpp"
+
+namespace {
+using ov::test::InputShape;
+
+typedef std::tuple BucketizeLayerParamsSet;
+
+class BucketizeLayerDynamicTest : public testing::WithParamInterface,
+ virtual public ov::test::SubgraphBaseTest {
+public:
+ static std::string getTestCaseName(testing::TestParamInfo obj) {
+ InputShape shapes;
+ InputShape boundary;
+ bool with_right_boundary;
+ ov::element::Type input_type;
+ ov::element::Type boundary_type;
+ ov::element::Type output_type;
+ std::string deviceName;
+ std::tie(shapes, boundary, with_right_boundary, input_type, boundary_type, output_type, deviceName) = obj.param;
+
+ std::ostringstream results;
+ results << "IS=" << ov::test::utils::partialShape2str({shapes.first}) << "_";
+ results << "TS=";
+ for (const auto& item : shapes.second) {
+ results << ov::test::utils::vec2str(item) << "_";
+ }
+ for (const auto& item : boundary.second) {
+ results << ov::test::utils::vec2str(item) << "_";
+ }
+ results << "withRightBoundary=" << with_right_boundary << "_";
+ results << "netPRC=" << input_type << "_";
+ results << "boundPRC=" << boundary_type << "_";
+ results << "outPRC=" << output_type << "_";
+
+ return results.str();
+ }
+
+ void generate_inputs(const std::vector& targetInputStaticShapes) override {
+ inputs.clear();
+ const auto& func_inputs = function->inputs();
+ ov::Tensor tensor;
+ for (size_t i = 0; i < func_inputs.size(); ++i) {
+ const auto& func_input = func_inputs[i];
+ tensor = ov::test::utils::create_and_fill_tensor(func_input.get_element_type(), targetInputStaticShapes[i]);
+ inputs.insert({func_input.get_node_shared_ptr(), tensor});
+ }
+ inferRequestNum++;
+ }
+
+protected:
+ size_t inferRequestNum = 0;
+
+ void SetUp() override {
+ InputShape shapes;
+ InputShape boundary;
+ bool with_right_boundary;
+ ov::element::Type input_type;
+ ov::element::Type boundary_type;
+ ov::element::Type output_type;
+ std::string deviceName;
+ std::tie(shapes, boundary, with_right_boundary, input_type, boundary_type, output_type, deviceName) = this->GetParam();
+
+ targetDevice = ov::test::utils::DEVICE_GPU;
+
+ std::vector input_shapes;
+ input_shapes.push_back(shapes);
+ input_shapes.push_back(boundary);
+
+ init_input_shapes(input_shapes);
+
+ ov::ParameterVector params{std::make_shared(input_type, inputDynamicShapes.front()),
+ std::make_shared(boundary_type, inputDynamicShapes.back())};
+
+ auto bucketize = std::make_shared(params[0], params[1], output_type, with_right_boundary);
+
+ ov::ResultVector results;
+ for (size_t i = 0; i < bucketize->get_output_size(); i++) {
+ results.push_back(std::make_shared(bucketize->output(i)));
+ }
+
+ function = std::make_shared(results, params, "BucketizeFuncTest");
+ }
+};
+
+TEST_P(BucketizeLayerDynamicTest, inference) {
+ run();
+}
+
+const std::vector input_shapes = {
+ {{-1, -1}, {{2, 3}, {3, 4}}}
+};
+
+const std::vector boundary_shapes = {
+ {{-1}, {{1}, {0}}}
+};
+
+const std::vector with_right_boundary = {
+ true,
+ false
+};
+
+const std::vector input_precisions = {
+ ov::element::f16,
+ ov::element::f32,
+ ov::element::i64,
+ ov::element::i32,
+ ov::element::i8,
+ ov::element::u8
+};
+
+const std::vector boundary_precisions = {
+ ov::element::f16,
+ ov::element::f32,
+ ov::element::i64,
+ ov::element::i32,
+ ov::element::i8,
+ ov::element::u8
+};
+
+const std::vector output_precisions = {
+ ov::element::i64,
+ ov::element::i32
+};
+
+INSTANTIATE_TEST_SUITE_P(smoke_bucketize_dynamic,
+ BucketizeLayerDynamicTest,
+ ::testing::Combine(
+ ::testing::ValuesIn(input_shapes),
+ ::testing::ValuesIn(boundary_shapes),
+ ::testing::ValuesIn(with_right_boundary),
+ ::testing::ValuesIn(input_precisions),
+ ::testing::ValuesIn(boundary_precisions),
+ ::testing::ValuesIn(output_precisions),
+ ::testing::Values(ov::test::utils::DEVICE_GPU)),
+ BucketizeLayerDynamicTest::getTestCaseName);
+
+} // namespace
\ No newline at end of file
diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/eltwise_gpu_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/eltwise_gpu_test.cpp
index fa529293b923b6..5f2f5a6bbfe7d2 100644
--- a/src/plugins/intel_gpu/tests/unit/test_cases/eltwise_gpu_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/test_cases/eltwise_gpu_test.cpp
@@ -347,7 +347,7 @@ void run_eltwise_int_shift_generic_test(cldnn::eltwise_mode mode) {
0, \
0, \
0, \
- static_cast(std::numeric_limits::max()) / 2, \
+ static_cast(std::numeric_limits::max()) /16, \
0, \
((sizeof(type) * 8) - 1) / 2);
diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/loop_gpu_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/loop_gpu_test.cpp
index df403b4001e2c2..e9d55960cf568f 100644
--- a/src/plugins/intel_gpu/tests/unit/test_cases/loop_gpu_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/test_cases/loop_gpu_test.cpp
@@ -182,14 +182,14 @@ void test_loop_gpu_basic_concat(bool is_caching_test)
std::vector eltwise_operand {
1.f, -2.f, 3.f, -4.f
};
- size_t trip_count = input_data.size()/eltwise_operand.size();
+ int64_t trip_count = input_data.size()/eltwise_operand.size();
int initial_condition = 1;
// initialize input buffers
set_values(input_mem, input_data);
set_values(operand_mem, eltwise_operand);
- set_values(trip_count_mem, {trip_count});
- set_values(initial_condition_mem, {initial_condition});
+ set_values(trip_count_mem, {trip_count});
+ set_values(initial_condition_mem, {initial_condition});
topology body(
input_layout("input", operand_mem->get_layout()),
@@ -1220,7 +1220,7 @@ void test_loop_gpu_zero_bytes_layout(bool is_caching_test)
auto& engine = get_test_engine();
// shape for zero bytes layout
- auto trip_count_mem = ov::intel_gpu::allocate_memory_evenif_zero_bytes(engine, { cldnn::layout{ ov::PartialShape({0}), data_types::i32, format::bfyx } });
+ auto trip_count_mem = engine.allocate_memory({data_types::i32, format::bfyx, {1, 1, 1, 1}});
auto input_mem = engine.allocate_memory({ data_types::f32, format::bfyx, { 1, 1, 4, 5 } });
auto operand_mem = engine.allocate_memory({ data_types::f32, format::bfyx, { 1, 1, 4, 5 } });
diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/memory_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/memory_test.cpp
index 52af896e4a0611..987483620ab3a9 100644
--- a/src/plugins/intel_gpu/tests/unit/test_cases/memory_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/test_cases/memory_test.cpp
@@ -555,9 +555,9 @@ class memory_pool: public ::testing::Test {
auto input_data2 = engine.allocate_memory(input_actual_layout2);
auto fc_weights_data = engine.allocate_memory({ ov::PartialShape{ weight_b, input_f }, data_types::f32,format::bfyx});
- set_values(input_data1, { -0.5f, 2.0f, 0.5f });
- set_values(input_data2, { 0.5f, -2.0f, -0.5f,
- -0.5f, 2.0f, 0.5f });
+ set_values(input_data1, { -0.5f, 2.0f, 0.5f,
+ 0.5f, -2.0f, -0.5f});
+ set_values(input_data2, { 0.5f, -2.0f, -0.5f });
set_values(fc_weights_data, { 1.5f, 1.0f, 0.5f,
-1.0f, 0.0f, 0.5f,
0.5f, -0.5f, -2.0f,
diff --git a/src/plugins/intel_gpu/tests/unit/transformations/bcast_and_pad_zp_buffers_test.cpp b/src/plugins/intel_gpu/tests/unit/transformations/bcast_and_pad_zp_buffers_test.cpp
index 5bea993237855d..218519f5bedbb1 100644
--- a/src/plugins/intel_gpu/tests/unit/transformations/bcast_and_pad_zp_buffers_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/transformations/bcast_and_pad_zp_buffers_test.cpp
@@ -184,6 +184,61 @@ TEST_F(TransformationTestsF, BroadcastAndPadZeroPointBuffers_3) {
}
}
+TEST_F(TransformationTestsF, BroadcastAndPadZeroPointBuffers_scalar_wzp) {
+ ov::Strides strides{1, 1};
+ ov::Strides dilations{1, 1};
+ ov::CoordinateDiff pads_begin{0, 0};
+ ov::CoordinateDiff pads_end{0, 0};
+ {
+ auto input = std::make_shared(ov::element::u8, ov::PartialShape{ 1, 8, 11, 12 });
+ auto weights_const = ov::op::v0::Constant::create(ov::element::u8, ov::Shape{ 8, 8, 3, 3 }, { 1 });
+ auto no_bias = std::make_shared();
+ auto azp_const = ov::op::v0::Constant::create(ov::element::u8, ov::Shape{ 1, 1, 1, 1 }, { 1 });
+ auto wzp_const = ov::op::v0::Constant::create(ov::element::u8, ov::Shape{ 1, 8, 1, 1 }, { 12 });
+ auto compensation = ov::op::v0::Constant::create(ov::element::f32, ov::Shape{ 1, 8, 1, 1 }, { 1 });
+ auto conv = std::make_shared(input,
+ weights_const,
+ no_bias,
+ azp_const,
+ wzp_const,
+ compensation,
+ strides,
+ pads_begin,
+ pads_end,
+ dilations,
+ -1,
+ ov::op::PadType::EXPLICIT,
+ ov::element::f32);
+
+ model = std::make_shared(ov::NodeVector{ conv }, ov::ParameterVector{ input });
+ manager.register_pass(8, true);
+ }
+ {
+ auto input = std::make_shared(ov::element::u8, ov::PartialShape{ 1, 8, 11, 12 });
+ auto weights_const = ov::op::v0::Constant::create(ov::element::u8, ov::Shape{ 8, 8, 3, 3 }, { 1 });
+ auto no_bias = std::make_shared();
+ auto azp_const = ov::op::v0::Constant::create(ov::element::u8, ov::Shape{ 1, 8, 1, 1 }, { 1 });
+ auto wzp_const = ov::op::v0::Constant::create(ov::element::u8, ov::Shape{ 1, 1, 1, 1 }, { 12 });
+ auto compensation = ov::op::v0::Constant::create(ov::element::f32, ov::Shape{ 1, 8, 1, 1 }, { 1 });
+ auto conv = std::make_shared(input,
+ weights_const,
+ no_bias,
+ azp_const,
+ wzp_const,
+ compensation,
+ strides,
+ pads_begin,
+ pads_end,
+ dilations,
+ -1,
+ ov::op::PadType::EXPLICIT,
+ ov::element::f32);
+
+ model_ref = std::make_shared(ov::NodeVector{ conv }, ov::ParameterVector{ input });
+ }
+ comparator.enable(FunctionsComparator::CmpValues::CONST_VALUES);
+}
+
} // namespace intel_gpu
} // namespace test
} // namespace ov
diff --git a/src/plugins/intel_npu/src/al/include/intel_npu/al/config/npuw.hpp b/src/plugins/intel_npu/src/al/include/intel_npu/al/config/npuw.hpp
index 2ce67a71a5da57..c5e91369ce80e2 100644
--- a/src/plugins/intel_npu/src/al/include/intel_npu/al/config/npuw.hpp
+++ b/src/plugins/intel_npu/src/al/include/intel_npu/al/config/npuw.hpp
@@ -41,6 +41,7 @@ DEFINE_OPT(NPUW_ONLINE_DUMP_PLAN, std::string, "", npuw::partitioning::online::d
DEFINE_OPT(NPUW_PLAN, std::string, "", npuw::partitioning::plan, CompileTime);
DEFINE_OPT(NPUW_FOLD, bool, false, npuw::partitioning::fold, CompileTime);
DEFINE_OPT(NPUW_CWAI, bool, false, npuw::partitioning::cwai, CompileTime);
+DEFINE_OPT(NPUW_DQ, bool, false, npuw::partitioning::dyn_quant, CompileTime);
DEFINE_OPT(NPUW_DCOFF_TYPE, std::string, "", npuw::partitioning::dcoff_type, CompileTime);
DEFINE_OPT(NPUW_DCOFF_SCALE, bool, false, npuw::partitioning::dcoff_with_scale, CompileTime);
DEFINE_OPT(NPUW_FUNCALL_FOR_ALL, bool, false, npuw::partitioning::funcall_for_all, CompileTime);
diff --git a/src/plugins/intel_npu/src/al/include/npuw_private_properties.hpp b/src/plugins/intel_npu/src/al/include/npuw_private_properties.hpp
index 627b6b957ebfb3..b0cf6f4a608f66 100644
--- a/src/plugins/intel_npu/src/al/include/npuw_private_properties.hpp
+++ b/src/plugins/intel_npu/src/al/include/npuw_private_properties.hpp
@@ -159,6 +159,14 @@ static constexpr ov::Property fold{"NPUW_FOLD"};
*/
static constexpr ov::Property cwai{"NPUW_CWAI"};
+/**
+ * @brief
+ * Type: bool.
+ * Apply dynamic quantization transformations at the plugin side.
+ * Default value: false.
+ */
+static constexpr ov::Property dyn_quant{"NPUW_DQ"};
+
/**
* @brief
* Type: std::string.
diff --git a/src/plugins/intel_npu/src/al/src/config/npuw.cpp b/src/plugins/intel_npu/src/al/src/config/npuw.cpp
index a43794e883368c..406fb9e6288fff 100644
--- a/src/plugins/intel_npu/src/al/src/config/npuw.cpp
+++ b/src/plugins/intel_npu/src/al/src/config/npuw.cpp
@@ -26,6 +26,7 @@ void intel_npu::registerNPUWOptions(OptionsDesc& desc) {
desc.add();
desc.add();
desc.add();
+ desc.add();
desc.add();
desc.add();
desc.add();
diff --git a/src/plugins/intel_npu/src/plugin/npuw/compiled_model.cpp b/src/plugins/intel_npu/src/plugin/npuw/compiled_model.cpp
index 6cfb7fd7ce1dc7..bfb1b474ee0f34 100644
--- a/src/plugins/intel_npu/src/plugin/npuw/compiled_model.cpp
+++ b/src/plugins/intel_npu/src/plugin/npuw/compiled_model.cpp
@@ -797,6 +797,7 @@ void ov::npuw::CompiledModel::implement_properties() {
BIND(npuw::partitioning::plan, NPUW_PLAN),
BIND(npuw::partitioning::fold, NPUW_FOLD),
BIND(npuw::partitioning::cwai, NPUW_CWAI),
+ BIND(npuw::partitioning::dyn_quant, NPUW_DQ),
BIND(npuw::partitioning::funcall_for_all, NPUW_FUNCALL_FOR_ALL),
BIND(npuw::partitioning::dcoff_type, NPUW_DCOFF_TYPE),
BIND(npuw::partitioning::dcoff_with_scale, NPUW_DCOFF_SCALE),
diff --git a/src/plugins/intel_npu/src/plugin/npuw/just_sync_infer_request.cpp b/src/plugins/intel_npu/src/plugin/npuw/just_sync_infer_request.cpp
index 6bd1b296c3a9a9..ba1f56b060e0c4 100644
--- a/src/plugins/intel_npu/src/plugin/npuw/just_sync_infer_request.cpp
+++ b/src/plugins/intel_npu/src/plugin/npuw/just_sync_infer_request.cpp
@@ -478,6 +478,8 @@ void ov::npuw::JustInferRequest::unpack_closure(std::size_t idx, RqPtr request)
// Bind extra parameters from the function's closure
// First, do easy things & delay heavy stuff
std::vector closure_unpack_required;
+ std::vector closure_copy_required;
+
for (std::size_t cidx = 0u; cidx < comp_model_desc.closure.size(); cidx++) {
auto& closure = comp_model_desc.closure[cidx];
@@ -488,14 +490,27 @@ void ov::npuw::JustInferRequest::unpack_closure(std::size_t idx, RqPtr request)
// Remember where the unpack is required
closure_unpack_required.push_back(cidx);
} else if (comp_model_desc.update_required[cidx]) {
- // Easy case, just set one to another. Copy_to is also possible
- // and even may be preferrable for some devices, like this:
- // ```ov::get_tensor_impl(closure)->copy_to(clparam._ptr);'''
- request->set_tensor(iport, ov::get_tensor_impl(closure));
+ if (needs_copy(idx)) {
+ // Remember where copy is requried
+ closure_copy_required.push_back(cidx);
+ } else {
+ // Easy case, just set one to another
+ request->set_tensor(iport, ov::get_tensor_impl(closure));
+ }
}
} // for(closure)
- // m_ms_unpack += ov::npuw::perf::ms_to_run([&](){
- // ov::parallel_for(closure_unpack_required.size(), [&](std::size_t j) {
+
+ // m_ms_unpack += ov::npuw::perf::ms_to_run([&](){
+ ov::parallel_for(closure_copy_required.size(), [&](std::size_t j) {
+ auto cidx = closure_copy_required[j];
+ auto& closure = comp_model_desc.closure[cidx];
+ const auto closure_param_id = comp_model_desc.param_base + cidx;
+ auto& iport = func_desc.compiled_model->inputs()[closure_param_id];
+ auto clparam = request->get_tensor(iport);
+ ov::get_tensor_impl(closure)->copy_to(clparam._ptr);
+ });
+ // }); // ms_to_run
+
for (std::size_t j = 0; j != closure_unpack_required.size(); j++) {
// NB: No need to protect anything here as containers are all
// preallocated and we only access elements under particular (thread
@@ -525,8 +540,6 @@ void ov::npuw::JustInferRequest::unpack_closure(std::size_t idx, RqPtr request)
ov::npuw::util::unpack(ov::get_tensor_impl(closure), clparam);
}
}
- //}); // ov_parallel_for
- // }); // ms_to_run
}
void ov::npuw::JustInferRequest::recreate_subrequests(std::size_t idx) {
diff --git a/src/plugins/intel_npu/src/plugin/npuw/partitioning/online/snapshot.cpp b/src/plugins/intel_npu/src/plugin/npuw/partitioning/online/snapshot.cpp
index 4e373dda5a24eb..2ee36fcb09361a 100644
--- a/src/plugins/intel_npu/src/plugin/npuw/partitioning/online/snapshot.cpp
+++ b/src/plugins/intel_npu/src/plugin/npuw/partitioning/online/snapshot.cpp
@@ -5,6 +5,7 @@
#include "snapshot.hpp"
#include "../../logging.hpp"
+#include "../../util.hpp"
#include "../patterns/avoid.hpp"
#include "../patterns/compute.hpp"
#include "group.hpp"
@@ -72,6 +73,8 @@ void Snapshot::buildGraph() {
++gid;
}
+ using namespace ov::npuw::util::at;
+
for (const auto& nh : m_graph->sorted()) {
auto gptr = m_graph->meta(nh).get();
auto ov_node = gptr->getInitialNode();
@@ -83,7 +86,7 @@ void Snapshot::buildGraph() {
auto ov_node_child = target_output.get_node()->shared_from_this();
// Insert readers from other layers
- m_node_to_prod_cons->at(ov_node).second.insert(ov_node_child);
+ _(m_node_to_prod_cons).at(ov_node).second.insert(ov_node_child);
// Save ports for repeated blocks pipeline
m_ports_map.insert({{ov_node, ov_node_child}, {i, target_output.get_index()}});
@@ -91,9 +94,9 @@ void Snapshot::buildGraph() {
if (!isOp(ov_node_child)) {
continue;
}
-
- if (!m_graph->linked(nh, m_node_to_gr->at(ov_node_child)->getHandle())) {
- m_graph->link(nh, m_node_to_gr->at(ov_node_child)->getHandle());
+ Group::GPtr gr_child = _(m_node_to_gr).at(ov_node_child);
+ if (!m_graph->linked(nh, gr_child->getHandle())) {
+ m_graph->link(nh, gr_child->getHandle());
}
}
} // for(outputs)
@@ -103,7 +106,7 @@ void Snapshot::buildGraph() {
auto ov_node_parent = target_input.get_node()->shared_from_this();
// Insert writers from other layers
- m_node_to_prod_cons->at(ov_node).first.insert(ov_node_parent);
+ _(m_node_to_prod_cons).at(ov_node).first.insert(ov_node_parent);
// Save ports for repeated blocks pipeline
m_ports_map.insert({{ov_node_parent, ov_node}, {target_input.get_index(), i}});
@@ -112,8 +115,9 @@ void Snapshot::buildGraph() {
continue;
}
- if (!m_graph->linked(m_node_to_gr->at(ov_node_parent)->getHandle(), nh)) {
- m_graph->link(m_node_to_gr->at(ov_node_parent)->getHandle(), nh);
+ Group::GPtr gr_parent = _(m_node_to_gr).at(ov_node_parent);
+ if (!m_graph->linked(gr_parent->getHandle(), nh)) {
+ m_graph->link(gr_parent->getHandle(), nh);
}
} // for(inputs)
} // for(get_ordered_ops)
@@ -1028,11 +1032,11 @@ GPtrSet Snapshot::getRepGroups(const Group::GPtr& group) const {
}
const OVNodeSet& Snapshot::getNodeProducers(const OVNodePtr& node) const {
- return m_node_to_prod_cons->at(node).first;
+ return ov::npuw::util::at::_(m_node_to_prod_cons).at(node).first;
}
const OVNodeSet& Snapshot::getNodeConsumers(const OVNodePtr& node) const {
- return m_node_to_prod_cons->at(node).second;
+ return ov::npuw::util::at::_(m_node_to_prod_cons).at(node).second;
}
// Updated within a group during fusion
diff --git a/src/plugins/intel_npu/src/plugin/npuw/partitioning/partitioning.cpp b/src/plugins/intel_npu/src/plugin/npuw/partitioning/partitioning.cpp
index 6fef5d8b6fdf94..fed5126f62a221 100644
--- a/src/plugins/intel_npu/src/plugin/npuw/partitioning/partitioning.cpp
+++ b/src/plugins/intel_npu/src/plugin/npuw/partitioning/partitioning.cpp
@@ -9,6 +9,7 @@
#include "intel_npu/al/config/npuw.hpp"
#include "online/compiler.hpp"
#include "online/utils/utils.hpp" // getMetaDesc
+#include "openvino/core/parallel.hpp"
#include "openvino/op/convert.hpp"
#include "openvino/op/slice.hpp"
#include "openvino/op/util/op_types.hpp"
@@ -16,6 +17,7 @@
#include "openvino/util/common_util.hpp"
#include "openvino/util/xml_parse_utils.hpp"
#include "patterns/dcoff.hpp"
+#include "patterns/opt.hpp"
namespace {
@@ -238,7 +240,8 @@ class Partitioner {
if (!ov::is_type(node_ptr)) {
OPENVINO_THROW("NPUW: trying to get a unique name of a non-Constant node");
}
- return node_ptr->get_friendly_name() + " with meta " + ov::npuw::online::util::getMetaDesc(node_ptr);
+ return node_ptr->get_friendly_name() + " with meta " + ov::npuw::online::util::getMetaDesc(node_ptr) +
+ " with output " + (*node_ptr->output(0).get_target_inputs().begin()).get_node()->description();
}
public:
@@ -277,6 +280,7 @@ class Partitioner {
void matchResults(const std::string& func_name);
void createFunction(const std::string& func_name);
void matchRepeatedSubgraphs(const std::string& func_name);
+ void optimize(const std::string& func_name);
void decompressionCutOff(const std::string& func_name);
// Final steps
@@ -1557,6 +1561,50 @@ void Partitioner::matchRepeatedSubgraphs(const std::string& func_name) {
LOG_VERB("Done");
}
+void Partitioner::optimize(const std::string& func_name) {
+ if (!cfg.get<::intel_npu::NPUW_DQ>()) {
+ LOG_VERB("No optimizations will be done to " << func_name << " in model " << model->get_friendly_name()
+ << "...");
+ return;
+ }
+
+ LOG_VERB("Optimize function " << func_name << " in model " << model->get_friendly_name() << "...");
+ LOG_BLOCK();
+
+ ov::npuw::Function& f = P.functions.at(func_name);
+
+ ov::npuw::patterns::opt::Context ctx;
+ ov::pass::GraphRewrite rewr;
+ rewr.add_matcher();
+ rewr.add_matcher(std::ref(ctx));
+ rewr.add_matcher(std::ref(ctx));
+ rewr.run_on_model(f._model);
+ ov::pass::Validate().run_on_model(f._model);
+
+ // Permute tensors where required
+ auto& func_group = all_functions.at(func_name);
+ for (auto&& p : ctx.closures_to_permute) {
+ auto param_idx = f._model->get_parameter_index(p.first);
+ auto closure_idx = param_idx - f._param_offset;
+ ov::parallel_for(func_group.refs.size(), [&](std::size_t f_idx) {
+ auto& funcall = func_group.refs[f_idx].get();
+ ov::npuw::util::permute(funcall._closure[closure_idx], p.second);
+ });
+ }
+
+ // Convert tensors where required
+ for (auto&& p : ctx.closures_to_f16) {
+ auto param_idx = f._model->get_parameter_index(p);
+ auto closure_idx = param_idx - f._param_offset;
+ ov::parallel_for(func_group.refs.size(), [&](std::size_t f_idx) {
+ auto& funcall = func_group.refs[f_idx].get();
+ ov::npuw::util::to_f16(funcall._closure[closure_idx]);
+ });
+ }
+
+ LOG_VERB("Done");
+}
+
void Partitioner::decompressionCutOff(const std::string& func_name) {
LOG_VERB("Decompression cut-off for function " << func_name << " in model " << model->get_friendly_name() << "...");
LOG_BLOCK();
@@ -1826,6 +1874,7 @@ ov::npuw::Partitioning ov::npuw::getPartitioning(const std::shared_ptr()) {
@@ -1841,6 +1890,7 @@ ov::npuw::Partitioning ov::npuw::getPartitioning(const std::shared_ptr
+// Param(W) -> to(f16) -> Multiply -> to(f32) -> MatMul
+// Param(S) ------------>
+//
+// TO:
+// ???(Act) -> to(f16) ->
+// Param(W) -> to(f16) -> MatMul -> Multiply -> to(f32)
+// Param(S) -> Reshape ----------->
+//
+
+DQMatMulCWi::DQMatMulCWi() {
+ auto qweight = opp::wrap_type();
+ auto qcoeff = opp::wrap_type();
+ auto qcvtw = opp::wrap_type({qweight});
+ auto qmuls = opp::wrap_type({qcvtw, qcoeff});
+ auto qcvtm = opp::wrap_type({qmuls});
+ auto qmmi = opp::any_input();
+ auto qmm = opp::wrap_type({qmmi, qcvtm});
+
+ // Note: Use [=] to make sure the above objects stay alive in the callback
+ auto callback = [=](ov::pass::pattern::Matcher& m) {
+ auto& node_to_output = m.get_pattern_value_map();
+
+ auto matched_node_qweight = node_to_output.at(qweight).get_node_shared_ptr();
+ auto matched_node_qcoeff = node_to_output.at(qcoeff).get_node_shared_ptr();
+ auto matched_node_matmul = node_to_output.at(qmm).get_node_shared_ptr();
+
+ auto matched_qweight = std::static_pointer_cast(matched_node_qweight);
+ auto matched_qcoeff = std::static_pointer_cast(matched_node_qcoeff);
+ auto matched_matmul = std::static_pointer_cast(matched_node_matmul);
+
+ auto qcoeff_shape = matched_qcoeff->output(0).get_shape();
+
+ if (ov::element::i4 == matched_qweight->get_element_type() && qcoeff_shape[1] == 1 &&
+ !matched_matmul->get_transpose_a() && matched_matmul->get_transpose_b()) {
+ auto matched_node_cvtw = node_to_output.at(qcvtw).get_node_shared_ptr();
+ auto matched_node_cvtm = node_to_output.at(qcvtm).get_node_shared_ptr();
+ auto matched_node_muls = node_to_output.at(qmuls).get_node_shared_ptr();
+ auto matched_node_mmi = node_to_output.at(qmmi).get_node_shared_ptr();
+
+ // Reconnect MatMul to read from Convert(W) directly.
+ // Note: ACT is f32 so has to be converted too.
+ auto new_cvt_act = std::make_shared(matched_node_mmi, ov::element::f16);
+ matched_matmul->input(0).replace_source_output(new_cvt_act);
+ matched_matmul->input(1).replace_source_output(matched_node_cvtw);
+
+ // Store MatMul's readers
+ auto mm_readers = matched_matmul->output(0).get_target_inputs();
+
+ // Introduce a Reshape to alter Scale factor's shape
+ auto new_dims = std::vector{qcoeff_shape[1], qcoeff_shape[0]};
+ auto new_const = std::make_shared(ov::element::i32, ov::Shape{2}, new_dims);
+ auto new_reshape = std::make_shared(matched_node_qcoeff, new_const, false);
+
+ // Reconnect Multiply's both inputs. Drop all outputs
+ matched_node_muls->input(0).replace_source_output(matched_matmul);
+ matched_node_muls->input(1).replace_source_output(new_reshape);
+ for (auto&& r : matched_node_muls->output(0).get_target_inputs()) {
+ matched_node_muls->output(0).remove_target_input(r);
+ }
+
+ // Reconnect Convert(M) to convert the Multiply's result
+ matched_node_cvtm->input(0).replace_source_output(matched_node_muls);
+
+ // Reconnect MatMul's old readers to Convert(Multiply)
+ for (auto&& r : mm_readers) {
+ r.replace_source_output(matched_node_cvtm);
+ }
+ }
+
+ return true; // root has changed
+ };
+ register_matcher(std::make_shared(qmm, "OptDQMatMulCWi"), std::move(callback));
+}
+
+// FROM:
+// ???(Act) -------------------------------------------->
+// Param(W) -> Convert(f16|f32) -> Multiply -> Reshape -> MatMul
+// Param(S) --------------------->
+//
+// WHERE (example):
+// Act: [ 1, 1, 4096]
+// W: [32,128,11008]
+// S: [32, 1,11008]
+// [1, 1 ,128] x
+// TO: [1,11K,128]T =
+// [32,1,128] [1, 1 ,11K] [32,1,11K]
+// ???(Act) -> Reshape > Split(/32) ->[to(f16) -> ]}
+// Param(W*) -----------> Split(/32) ->[to(f16) -> MatMul]} Concat v
+// Param(S) ---------------------------------------------> Multiply
+// Reshape(1,a,b,c)
+// ReduceSum(1)
+// Reshape(a,b,c)
+// to(f32)
+// WHERE:
+// W* : [32,11008,128]
+
+DQMatMulGQi::DQMatMulGQi(Context::Ref ctx) {
+ auto qweight = opp::wrap_type();
+ auto qcoeff = opp::wrap_type();
+ auto qcvtw = opp::wrap_type({qweight});
+ auto qmuls = opp::wrap_type({qcvtw, qcoeff});
+ auto qreshp = opp::wrap_type({qmuls, opp::any_input()});
+ auto qmmi = opp::any_input();
+ auto qmm = opp::wrap_type({qmmi, qreshp});
+
+ // Note: Use [=] to make sure the above objects stay alive in the callback
+ auto callback = [=](ov::pass::pattern::Matcher& m) {
+ auto& node_to_output = m.get_pattern_value_map();
+
+ auto matched_node_qweight = node_to_output.at(qweight).get_node_shared_ptr();
+ auto matched_node_qcoeff = node_to_output.at(qcoeff).get_node_shared_ptr();
+ auto matched_node_matmul = node_to_output.at(qmm).get_node_shared_ptr();
+ auto matched_out_mmi = node_to_output.at(qmmi);
+
+ auto matched_qweight = std::static_pointer_cast(matched_node_qweight);
+ auto matched_qcoeff = std::static_pointer_cast(matched_node_qcoeff);
+ auto matched_matmul = std::static_pointer_cast(matched_node_matmul);
+
+ auto qweight_shape = matched_qweight->output(0).get_shape();
+ auto qcoeff_shape = matched_qcoeff->output(0).get_shape();
+ auto act_shape = matched_out_mmi.get_shape();
+ auto out_shape = matched_node_matmul->output(0).get_shape();
+
+ if (ov::element::i4 == matched_qweight->get_element_type() &&
+ ov::element::f32 == matched_qcoeff->get_element_type() && qcoeff_shape.size() == 3 &&
+ qweight_shape.size() == 3 && act_shape.size() == 3 && qcoeff_shape[0] == qweight_shape[0] &&
+ qcoeff_shape[1] == 1 && qcoeff_shape[2] == qweight_shape[2] && !matched_matmul->get_transpose_a() &&
+ !matched_matmul->get_transpose_b()) {
+ // Mark W closure to transpose, and transpose the respective parameter
+ ctx.get().permute(matched_qweight, {0, 2, 1});
+
+ // Mark S closure to be lowered fo f16
+ ctx.get().to_f16(matched_qcoeff);
+
+ ov::Shape tw_shape = {qweight_shape[0], qweight_shape[2], qweight_shape[1]};
+ matched_qweight->set_partial_shape(tw_shape);
+ matched_qweight->validate_and_infer_types();
+
+ matched_qcoeff->set_element_type(ov::element::f16);
+ matched_qcoeff->validate_and_infer_types();
+
+ // Reshape the Act to group format
+ const auto NSPLIT = qweight_shape[0];
+ std::vector rshp_act_v = {NSPLIT, act_shape[1], act_shape[2] / NSPLIT};
+ auto rshp_act_c = std::make_shared(ov::element::i32, ov::Shape{3}, rshp_act_v);
+ auto rshp_act = std::make_shared(matched_out_mmi, rshp_act_c, false);
+
+ // Split Act and W, and S tensors by NSPLIT
+ auto split_axis = std::make_shared(ov::element::i32, ov::Shape{}, 0);
+ auto split_a = std::make_shared(rshp_act, split_axis, NSPLIT);
+ auto split_w = std::make_shared(matched_qweight, split_axis, NSPLIT);
+
+ // Do the CW MM for every split
+ std::vector> to_concat;
+ for (std::size_t i = 0; i < NSPLIT; i++) {
+ auto a_f16 = std::make_shared(split_a->output(i), ov::element::f16);
+ auto w_f16 = std::make_shared(split_w->output(i), ov::element::f16);
+ auto m_f16 = std::make_shared(a_f16, w_f16, false, true);
+ to_concat.push_back(m_f16);
+ }
+
+ // Now concat and scale the result
+ auto concat = std::make_shared(to_concat, 0);
+ auto s_f16 = std::make_shared(concat, matched_qcoeff);
+
+ // Now reshape to a better shape, ReduceSum, and reshape to the right size again
+ std::vector rshp_ccat_v = {1, NSPLIT, 1, qweight_shape[2]};
+ auto rshp_ccat_c = std::make_shared(ov::element::i32, ov::Shape{4}, rshp_ccat_v);
+ auto rshp_ccat = std::make_shared(s_f16, rshp_ccat_c, false);
+
+ auto reduce_axis = std::make_shared(ov::element::i32, ov::Shape{}, 1);
+ auto reduce = std::make_shared(rshp_ccat, reduce_axis, true);
+
+ auto rshp_out_c = std::make_shared(ov::element::i32, ov::Shape{3}, out_shape);
+ auto rshp_out = std::make_shared(reduce, rshp_out_c, false);
+
+ // Convert the result to f32 to maintain the graph contracts. FIXME should be avoided
+ auto out = std::make_shared(rshp_out, ov::element::f32);
+
+ // Now.. Reconnect the matmul readers to the new output (reducesum)
+ for (auto&& r : matched_matmul->output(0).get_target_inputs()) {
+ r.replace_source_output(out);
+ }
+ return true; // root has changed
+ }
+ return false; // did nothing here
+ };
+ register_matcher(std::make_shared(qmm, "OptDQMatMulGQi"), std::move(callback));
+}
+
+// FROM:
+// ???(Act) -------------------------------------------------------->
+// Param(W) -> Convert(f16) -> Multiply -> Reshape -> Convert(f32) -> MatMul
+// Param(S) ----------------->
+//
+// WHERE (example):
+// Act: [ 1, 1,2048]
+// W: [512,16, 128]
+// S: [512,16, 1]
+// [1, 1,128] x
+// TO: [1,512,128]T =
+// [16,1,128] [1, 1,512] [16,1,512]
+// ???(Act) -> Reshape > Split(/16) ->[to(f16) -> ]}
+// Param(W*) -----------> Split(/16) ->[to(f16) -> MatMul v ]} Concat
+// Param(S) -----------> Split(/16) ->[---------> Multiply ]} v
+// Reshape(1,16,1,512)
+// ReduceSum(1)
+// Reshape( 1,1,512)
+// to(f32)
+// WHERE:
+// W* : [16,512,128]
+
+DQMatMulGQ2i::DQMatMulGQ2i(Context::Ref ctx) {
+ auto qweight = opp::wrap_type();
+ auto qcoeff = opp::wrap_type();
+ auto qcvtw = opp::wrap_type({qweight});
+ auto qmuls = opp::wrap_type({qcvtw, qcoeff});
+ auto qreshp = opp::wrap_type({qmuls, opp::any_input()});
+ auto qcvtr = opp::wrap_type({qreshp});
+ auto qmmi = opp::any_input();
+ auto qmm = opp::wrap_type({qmmi, qcvtr});
+
+ // Note: Use [=] to make sure the above objects stay alive in the callback
+ auto callback = [=](ov::pass::pattern::Matcher& m) {
+ auto& node_to_output = m.get_pattern_value_map();
+
+ auto matched_node_qweight = node_to_output.at(qweight).get_node_shared_ptr();
+ auto matched_node_qcoeff = node_to_output.at(qcoeff).get_node_shared_ptr();
+ auto matched_node_matmul = node_to_output.at(qmm).get_node_shared_ptr();
+ auto matched_out_mmi = node_to_output.at(qmmi);
+
+ auto matched_qweight = std::static_pointer_cast(matched_node_qweight);
+ auto matched_qcoeff = std::static_pointer_cast(matched_node_qcoeff);
+ auto matched_matmul = std::static_pointer_cast(matched_node_matmul);
+
+ auto qweight_shape = matched_qweight->output(0).get_shape();
+ auto qcoeff_shape = matched_qcoeff->output(0).get_shape();
+ auto act_shape = matched_out_mmi.get_shape();
+ auto out_shape = matched_node_matmul->output(0).get_shape();
+
+ if (ov::element::i4 == matched_qweight->get_element_type() && qweight_shape.size() == 3 &&
+ ov::element::f16 == matched_qcoeff->get_element_type() && qcoeff_shape.size() == 3 &&
+ act_shape.size() == 3 && qcoeff_shape[0] == qweight_shape[0] && qcoeff_shape[2] == 1 &&
+ qcoeff_shape[1] == qweight_shape[1] && !matched_matmul->get_transpose_a() &&
+ matched_matmul->get_transpose_b()) {
+ // Mark W closure to transpose, and transpose the respective parameter
+ ctx.get().permute(matched_qweight, {1, 0, 2});
+
+ ov::Shape tw_shape = {qweight_shape[1], qweight_shape[0], qweight_shape[2]};
+ matched_qweight->set_partial_shape(tw_shape);
+ matched_qweight->validate_and_infer_types();
+
+ // Reshape the Act to group format
+ const auto NSPLIT = qweight_shape[1];
+ std::vector rshp_act_v = {NSPLIT, 1, act_shape[2] / NSPLIT};
+ auto rshp_act_c = std::make_shared(ov::element::i32, ov::Shape{3}, rshp_act_v);
+ auto rshp_act = std::make_shared(matched_out_mmi, rshp_act_c, false);
+
+ // Split Act and W, and S tensors by NSPLIT
+ auto split_axis = std::make_shared(ov::element::i32, ov::Shape{}, 0);
+ auto split_a = std::make_shared(rshp_act, split_axis, NSPLIT);
+ auto split_w = std::make_shared(matched_qweight, split_axis, NSPLIT);
+
+ auto split_axis_s = std::make_shared(ov::element::i32, ov::Shape{}, 1);
+ auto split_s = std::make_shared(matched_qcoeff, split_axis_s, NSPLIT);
+
+ std::vector rshp_scale_v = {1, 1, qcoeff_shape[0]};
+ auto rshp_scale_c = std::make_shared(ov::element::i32, ov::Shape{3}, rshp_scale_v);
+
+ // Do the CW MM for every split
+ std::vector> to_concat;
+ for (std::size_t i = 0; i < NSPLIT; i++) {
+ auto a_f16 = std::make_shared(split_a->output(i), ov::element::f16);
+ auto w_f16 = std::make_shared(split_w->output(i), ov::element::f16);
+ auto m_f16 = std::make_shared(a_f16, w_f16, false, true);
+
+ auto r_f16 = std::make_shared(split_s->output(i), rshp_scale_c, false);
+ auto s_f16 = std::make_shared(m_f16, r_f16);
+ to_concat.push_back(s_f16);
+ }
+
+ // Now concat and scale the result
+ auto concat = std::make_shared(to_concat, 0);
+
+ // Now reshape to a better shape, ReduceSum, and reshape to the right size again
+ std::vector rshp_ccat_v = {1, NSPLIT, 1, qweight_shape[0]};
+ auto rshp_ccat_c = std::make_shared(ov::element::i32, ov::Shape{4}, rshp_ccat_v);
+ auto rshp_ccat = std::make_shared(concat, rshp_ccat_c, false);
+
+ auto reduce_axis = std::make_shared(ov::element::i32, ov::Shape{}, 1);
+ auto reduce = std::make_shared(rshp_ccat, reduce_axis, true);
+
+ auto rshp_out_c = std::make_shared(ov::element::i32, ov::Shape{3}, out_shape);
+ auto rshp_out = std::make_shared(reduce, rshp_out_c, false);
+
+ // Convert the result to f32 to maintain the graph contracts. FIXME should be avoided
+ auto out = std::make_shared