TensorFlow Cloud is a library to connect your local environment to Google Cloud.
import tensorflow_cloud as tfc
TF_GPU_IMAGE = "tensorflow/tensorflow:latest-gpu"
run_parameters = {
distribution_strategy='auto',
requirements_txt='requirements.txt',
docker_config=tfc.DockerConfig(
parent_image=TF_GPU_IMAGE,
image_build_bucket=GCS_BUCKET
),
chief_config=tfc.COMMON_MACHINE_CONFIGS['K80_1X'],
worker_config=tfc.COMMON_MACHINE_CONFIGS['K80_1X'],
worker_count=3,
job_labels={'job': "my_job"}
}
tfc.run(**run_parameters) # Runs your training on Google Cloud!
Run in a Notebook
The TensorFlow Cloud repository provides APIs that ease the transition from local model building and debugging to distributed training and hyperparameter tuning on Google Cloud. From inside a Colab or Kaggle Notebook or a local script file, you can send your model for tuning or training on Cloud directly, without needing to use the Cloud Console.
