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#!/bin/bash
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
function print_help {
echo "Usage: `basename $0` [--build-container] <python_file>"
echo ""
echo "Option --build-container will build the Docker container based on"
echo "docker/Dockerfile and tag the image with gltorch:latest."
echo ""
echo "Example: `basename $0` samples/torch/envphong.py"
}
build_container=0
sample=""
while [[ "$#" -gt 0 ]]; do
case $1 in
--build-container) build_container=1;;
-h|--help) print_help; exit 0 ;;
--*) echo "Unknown parameter passed: $1"; exit 1 ;;
*) sample="$1"; shift; break;
esac
shift
done
rest=$@
# Build the docker container
if [ "$build_container" = "1" ]; then
docker build --tag gltorch:latest -f docker/Dockerfile .
docker build --tag gltensorflow:latest --build-arg BASE_IMAGE=tensorflow/tensorflow:1.15.0-gpu-py3 -f docker/Dockerfile .
fi
if [ ! -f "$sample" ]; then
echo
echo "No python sample given or file '$sample' not found. Exiting."
exit 1
fi
image="gltorch:latest"
TENSORFLOW_CUDA_CACHE=""
# Magically choose the tensorflow container if running a sample from the samples/tensorflow/ directory
if [[ $sample == *"/tensorflow/"* ]]; then
image="gltensorflow:latest"
TENSORFLOW_CUDA_CACHE="-e NVDIFFRAST_CACHE_DIR=/app/tmp"
fi
echo "Using container image: $image"
echo "Running command: $sample $rest"
# Run a sample with docker
docker run --rm -it --gpus all --user $(id -u):$(id -g) \
-v `pwd`:/app --workdir /app -e TORCH_EXTENSIONS_DIR=/app/tmp $TENSORFLOW_CUDA_CACHE $image python3 $sample $rest
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