TF Serving blog post: Docker image

TF_servingPost_docker_image.sh

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# Pseudocode for creating Docker image

# Get the Docker TF Serving image we'll use as a foundation to build our custom image
docker pull tensorflow/serving

# Start up this TF Docker image as a container named `serving_base`
docker run -d --name serving_base tensorflow/serving

# Copy the Estimator from our local folder to the Docker container
# You can rename `my_model` to best reflect your model's name. It's what will be used in the REST API call
docker cp /path/to/my_exported_models serving_base:/models/<my_model>

# Commit the new Docker container and kill the serving base
docker commit --change "ENV MODEL_NAME <my_model>" serving_base <org_name>/<image_name>:<version_tag>
docker kill serving_base

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# Same example with filled in data:

docker pull tensorflow/serving
docker run -d --name serving_base tensorflow/serving
docker cp models_hvgrid_export serving_base:/models/hv_grid
docker commit --change "ENV MODEL_NAME hv_grid" serving_base developmentseed/hv_grid:v1
docker kill serving_base
docker run -p 8501:8501 -t developmentseed/hv_grid:v1