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add poetry support for tensorflow maskrcnn; update tensorflow resnet5… (#2679)
* add poetry support for tensorflow maskrcnn; update tensorflow resnet50v1_5 inference * fix: correct database file path in IP leak detection workflow * fix: update database entries for IP leak detection workflow * add smoke tests for Mask R-CNN and ResNet50 models * remove unused smoke.yaml files for Mask R-CNN and ResNet50 models * fix: update Dockerfiles to set up poetry environment and add to PATH * refactor: streamline Python dependency installation in Dockerfiles and setup.sh * refactor: consolidate Python dependency installation scripts across Dockerfiles and setup.sh files * docker tf flex maskrcnn (#2682) * update tf maskrcnn gpu * modify poetry files * update poetry * remove maskrcnn flex gpu workloads * remove compose references * refactor: remove unnecessary activation of poetry environment in dependency installation script * tf rn50 training gpu update (#2685) * update dockerfile * Update tf-max-series-resnet50v1-5-training.Dockerfile * TF RN50 Inference (#2686) * update dockerfile * update tf rn50 inference * update tests and doc * Update smoke.yaml * Update tests.yaml * Update tf-max-series-resnet50v1-5-training.Dockerfile * Update smoke.yaml * Update tests.yaml * Update docker-compose.yml * update smoke and tests * Revert "update smoke and tests" This reverts commit a06b59f24eb42a2c7455e067025aab59a2832420. * refine dockerfile maskrcnn training (#2684) * refine dockerfile * Update pyproject.toml * update poetry files and add smoke test * add pythonpath * update tests * add pybind * fix service name * remove rn50 inference * remove rn50 tf inf smoke file * update bert_large build --------- Co-authored-by: Srikanth Ramakrishna <[email protected]>
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‎README.md‎

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@@ -139,6 +139,7 @@ For best performance on Intel® Data Center GPU Max Series, please check the [li
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| [DLRM v2](https://arxiv.org/abs/1906.00091) | PyTorch | Training | Max Series | [FP32 TF32 BF16](/models_v2/pytorch/torchrec_dlrm/training/gpu/README.md)
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| [3D-Unet](https://arxiv.org/pdf/1606.06650.pdf) | PyTorch | Inference | Max Series | [FP16 INT8 FP32](/models_v2/pytorch/3d_unet/inference/gpu/README.md) |
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| [3D-Unet](https://arxiv.org/pdf/1606.06650.pdf) | TensorFlow | Training | Max Series | [BFloat16 FP32](/models_v2/tensorflow/3d_unet/training/gpu/README.md) |
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| [Stable Diffusion](https://arxiv.org/pdf/2112.10752.pdf) | PyTorch | Inference | Max Series, Arc Series | [FP16 FP32](/models_v2/pytorch/stable_diffusion/inference/gpu/README.md) |
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| [Mask R-CNN](https://arxiv.org/pdf/1703.06870.pdf) | TensorFlow | Training | Max Series | [FP32 BFloat16](/models_v2/tensorflow/maskrcnn/training/gpu/README.md) |
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| [RNN-T](https://arxiv.org/abs/1211.3711) | PyTorch | Inference | Max Series | [FP16 BF16 FP32](/models_v2/pytorch/rnnt/inference/gpu/README.md) |
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| [RNN-T](https://arxiv.org/abs/1211.3711) | PyTorch | Training | Max Series | [FP32 BF16 TF32](/models_v2/pytorch/rnnt/training/gpu/README.md) |

‎docker/tensorflow/bert_large/training/gpu/tf-max-series-bert-large-training.Dockerfile‎

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@@ -36,10 +36,8 @@ WORKDIR /workspace/tf-max-series-bert-large-training/models
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COPY models_v2/tensorflow/bert_large/training/gpu .
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RUN git clone https://github.com/titipata/pubmed_parser && \
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pip install ./pubmed_parser
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RUN python -m pip install --no-cache-dir -r requirements.txt
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COPY models_v2/common/install-python-dependencies.sh .
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RUN ./install-python-dependencies.sh
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RUN git clone https://github.com/NVIDIA/DeepLearningExamples.git && \
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cd DeepLearningExamples/TensorFlow2/LanguageModeling/BERT && \

‎docker/tensorflow/docker-compose.yml‎

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image: ${REGISTRY}/aiops/mlops-ci:b-${GITHUB_RUN_NUMBER:-0}-image-recognition-tf-max-gpu-resnet50v1-5-training
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cap_drop:
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- NET_RAW
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bert-large-training-gpu:
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bert_large-training-gpu:
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build:
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dockerfile: docker/tensorflow/bert_large/training/gpu/tf-max-series-bert-large-training.Dockerfile
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extends: resnet50v1_5-training-gpu

‎docker/tensorflow/maskrcnn/training/gpu/smoke.yaml‎

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single-tile-bf16-training:
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img: ${REGISTRY}/aiops/mlops-ci:b-${GITHUB_RUN_NUMBER:-0}-image-segmentation-tf-max-gpu-maskrcnn-training
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ipc: host
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cmd: mpirun -np 1 -prepend-rank -ppn 1 bash run_model.sh
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device: ["/dev/dri"]
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env:
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PRECISION: bfloat16
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EPOCHS: '1'
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STEPS_PER_EPOCH: '20'
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BATCH_SIZE: '4'
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MULTI_TILE: 'False'
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OUTPUT_DIR: /tmp
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DATASET_DIR: /tf_dataset/dataset/coco_dataset/COCO2017_training_data/
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volumes:
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- src: /tf_dataset/dataset/coco_dataset/COCO2017_training_data/
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dst: /tf_dataset/dataset/coco_dataset/COCO2017_training_data/
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- src: /dev/dri/by-path
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dst: /dev/dri/by-path
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- src: /tmp
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dst: /tmp

‎docker/tensorflow/maskrcnn/training/gpu/tests.yaml‎

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img: ${REGISTRY}/aiops/mlops-ci:b-${GITHUB_RUN_NUMBER:-0}-image-segmentation-tf-max-gpu-maskrcnn-training
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ipc: host
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cmd: mpirun -np 1 -prepend-rank -ppn 1 bash run_model.sh
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device: /dev/dri
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device: ["/dev/dri"]
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env:
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PRECISION: bfloat16
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EPOCHS: '1'
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multi-tile-bf16-training:
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img: ${REGISTRY}/aiops/mlops-ci:b-${GITHUB_RUN_NUMBER:-0}-image-segmentation-tf-max-gpu-maskrcnn-training
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cmd: bash run_model.sh
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device: /dev/dri
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device: ["/dev/dri"]
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env:
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PRECISION: bfloat16
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EPOCHS: '1'
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img: ${REGISTRY}/aiops/mlops-ci:b-${GITHUB_RUN_NUMBER:-0}-image-segmentation-tf-max-gpu-maskrcnn-training
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ipc: host
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cmd: mpirun -np 1 -prepend-rank -ppn 1 bash run_model.sh
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device: /dev/dri
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device: ["/dev/dri"]
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env:
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PRECISION: fp32
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EPOCHS: '1'
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multi-tile-fp32-training:
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img: ${REGISTRY}/aiops/mlops-ci:b-${GITHUB_RUN_NUMBER:-0}-image-segmentation-tf-max-gpu-maskrcnn-training
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cmd: bash run_model.sh
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device: /dev/dri
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device: ["/dev/dri"]
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env:
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PRECISION: fp32
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EPOCHS: '1'

‎docker/tensorflow/maskrcnn/training/gpu/tf-max-series-maskrcnn-training.Dockerfile‎

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COPY models_v2/tensorflow/maskrcnn/training/gpu .
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RUN python -m pip install opencv-python-headless \
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pybind11 \
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pycocotools \
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-e "git+https://github.com/NVIDIA/dllogger#egg=dllogger"
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COPY models_v2/common/install-python-dependencies.sh .
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RUN ./install-python-dependencies.sh
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RUN git clone https://github.com/NVIDIA/DeepLearningExamples.git && \
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cd DeepLearningExamples/TensorFlow2/Segmentation/MaskRCNN && \
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ENV CCL_ROOT=/opt/intel/oneapi/ccl/2021.13
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ENV I_MPI_ROOT=/opt/intel/oneapi/mpi/2021.13
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ENV FI_PROVIDER_PATH=/opt/intel/oneapi/mpi/2021.13/opt/mpi/libfabric/lib/prov:/usr/lib/x86_64-linux-gnu/libfabric
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ENV PYTHONPATH=/root/.cache/pypoetry/virtualenvs/tf-maskrcnn-trn-gpu-3khfSOyS-py3.10/lib/python3.10/site-packages:$PYTHONPATH
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COPY LICENSE licenses/LICENSE
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COPY third_party licenses/third_party

‎docker/tensorflow/resnet50v1_5/training/gpu/tf-max-series-resnet50v1-5-training.Dockerfile‎

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intel-oneapi-ccl=${CCL_VER} && \
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rm -rf /var/lib/apt/lists/*
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RUN curl -sSL https://install.python-poetry.org | python3 -
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WORKDIR /workspace/tf-max-series-resnet50v1-5-training/models
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COPY models_v2/tensorflow/resnet50v1_5/training/gpu .
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RUN /root/.local/bin/poetry install
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RUN /root/.local/bin/poetry add intel-optimization-for-horovod
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COPY models_v2/common/install-python-dependencies.sh .
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RUN ./install-python-dependencies.sh
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RUN mkdir -p resnet50 && \
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cd resnet50 && \
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ENV CCL_ROOT=/opt/intel/oneapi/ccl/2021.13
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ENV I_MPI_ROOT=/opt/intel/oneapi/mpi/2021.13
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ENV FI_PROVIDER_PATH=/opt/intel/oneapi/mpi/2021.13/opt/mpi/libfabric/lib/prov:/usr/lib/x86_64-linux-gnu/libfabric
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ENV PYTHONPATH=/root/.cache/pypoetry/virtualenvs/models-v2-tensorflow-resnet50v1-5-training-WKRPeTfh-py3.10/lib/python3.10/site-packages:$PYTHONPATH
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COPY LICENSE licenses/LICENSE
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COPY third_party licenses/third_party

‎models_v2/common/install-python-dependencies.sh‎

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#!/bin/bash
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if [ -f "./pyproject.toml" ]; then
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# Download and run the Poetry installation script
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curl -sSL https://install.python-poetry.org | python3 -
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export PATH="~/.local/bin:$PATH"
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# Install the pypi dependencies using poetry
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poetry install
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else
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echo "No pypi dependencies defined with poetry."
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fi

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