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TransNetV2 Inference

Description

This document has instructions for running TransNetV2 Inference.

Quick Start Scripts

DataType Throughput Latency
FP32 bash inference_throughput.sh fp32 bash inference_realtime.sh fp32
BF16 bash inference_throughput.sh bf16 bash inference_realtime.sh bf16

Follow the instructions to setup your bare metal environment on either Linux or Windows systems. Once all the setup is done, the Model Zoo can be used to run a quickstart script. Ensure that you have a clone of the Model Zoo Github repository.

git clone https://github.com/IntelAI/models.git

Run the model on Linux

Follow link to install Miniconda and build Pytorch, IPEX, TorchVison and Jemalloc.

  • Install dependencies

    pip install ffmpeg-python matplotlib Pillow pycocotools pandas

  • Set Jemalloc Preload for better performance

    After Jemalloc setup, set the following environment variables.

    export LD_PRELOAD="<path to the jemalloc directory>/lib/libjemalloc.so":$LD_PRELOAD
export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000"

  • Set IOMP preload for better performance

    IOMP should be installed in your conda env. Set the following environment variables.

    export LD_PRELOAD=<path to the intel-openmp directory>/lib/libiomp5.so:$LD_PRELOAD

  • Set ENV to use AMX if you are using SPR

    export DNNL_MAX_CPU_ISA=AVX512_CORE_AMX

  • Run the model:

    cd models

# Set environment variables
export OUTPUT_DIR=<path to an output directory>

# Run a quickstart script (for example, FP32 batch inference)
bash quickstart/shot_boundary_detection/pytorch/transnetv2/inference/cpu/inference_throughput.sh fp32

Run the model on Windows

If not already setup, please follow instructions for environment setup on Windows.

  • Install dependencies 
    pip install ffmpeg-python matplotlib Pillow pycocotools pandas
  • Using Windows CMD.exe, run: 
    cd models

# Set environment variables
set OUTPUT_DIR=<path to an output directory>

# Run a quickstart script (FP32 realtime inference or batch inference)
bash quickstart\shot_boundary_detection\pytorch\transnetv2\inference\cpu\inference_realtime.sh fp32

License

LICENSE