Skip to content

Latest commit

 

History

History
70 lines (51 loc) · 2.13 KB

README.md

File metadata and controls

70 lines (51 loc) · 2.13 KB
Raw

TransNetV2 Inference

Description

This document has instructions for running TransNetV2 Inference using Intel-optimized PyTorch.

Bare Metal

General setup

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

Model Specific Setup

  • Install dependencies

    pip install ffmpeg-python matplotlib Pillow pycocotools pandas

  • Set Jemalloc Preload for better performance

    The jemalloc should be built from the General setup section.

    export LD_PRELOAD="path/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 from the General setup section.

    export LD_PRELOAD=path/lib/libiomp5.so:$LD_PRELOAD

  • Set ENV to use AMX if you are using SPR

    export DNNL_MAX_CPU_ISA=AVX512_CORE_AMX

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

Run the model

Follow the instructions above to setup your bare metal environment, download and preprocess the dataset, and do the model specific setup. Once all the setup is done, the Model Zoo can be used to run a quickstart script. Ensure that you have an enviornment variables set to point to the dataset directory, the downloaded pretrained model, and an output directory.

# Clone the model zoo repo and set the MODEL_DIR
git clone https://github.com/IntelAI/models.git
cd models
export MODEL_DIR=$(pwd)

# Env vars
export OUTPUT_DIR=<path to an output directory>

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

License

LICENSE