用于在SageMaker上运行TensorFlow训练脚本的工具包。用于构建SageMakerTensorFlow.zip

# TensorFlow benchmarking scripts This folder contains the TF training scripts https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks. ## Basic usage **execute_tensorflow_training.py train** uses SageMaker python sdk to start a training job. ```bash ./execute_tensorflow_training.py train --help Usage: execute_tensorflow_training.py train [OPTIONS] [SCRIPT_ARGS]... Options: --framework-version [1.11.0|1.12.0] [required] --device [cpu|gpu] [required] --py-versions TEXT --training-input-mode [File|Pipe] --networking-isolation / --no-networking-isolation --wait / --no-wait --security-groups TEXT --subnets TEXT --role TEXT --instance-counts INTEGER --batch-sizes INTEGER --instance-types TEXT --help Show this message and exit. ``` **execute_tensorflow_training.py generate_reports** generate benchmark reports. ## Examples: ```bash #!/usr/bin/env bash ./execute_tensorflow_training.py train \ --framework-version 1.11.0 \ --device gpu \ \ --instance-types ml.p3.2xlarge \ --instance-types ml.p3.8xlarge \ --instance-types ml.p3.16xlarge \ --instance-types ml.p2.xlarge \ --instance-types ml.p2.8xlarge \ --instance-types ml.p2.16xlarge \ \ --instance-counts 1 \ \ --py-versions py3 \ --py-versions py2 \ \ --subnets subnet-125fb674 \ \ --security-groups sg-ce5dd1b4 \ \ --batch-sizes 32 \ --batch-sizes 64 \ --batch-sizes 128 \ --batch-sizes 256 \ --batch-sizes 512 \ \ -- --model resnet32 --num_epochs 10 --data_format NHWC --summary_verbosity 1 --save_summaries_steps 10 --data_name cifar10 ``` ## Using other models, datasets and benchmarks configurations ```python tf_cnn_benchmarks/tf_cnn_benchmarks.py --help``` shows all the options that the script has.