Metadata-Version: 2.1
Name: tensorio-bundler
Version: 0.2.0
Summary: Bundle models for use with TensorIO
Home-page: https://github.com/doc-ai/tensorio-bundler
Author: Doc.ai
Author-email: neeraj@doc.ai
License: Apache License 2.0
Description: # tensorio-bundler
        Create TensorIO model bundles
        
        
        ## Running the bundler from the command line
        
        NOTE: Working on making a PyPI package. Once that is done, these instructions will change
        to use whatever binary the corresponding `pip install` produces.
        
        ### Requirements
        + Python 3
        
        ### Instructions
        The `tensorio_bundler` module comes with a `bundler` utility that you can use to create TensorIO
        zipped tiobundle files directly from your command line.
        
        For more information on how to run the `bundler`, run:
        ```
        python -m tensorio_bundler.bundler -h
        ```
        
        A sample invocation (using test data, assumed to be run from project root -- same directory as this
        README):
        ```
        python -m tensorio_bundler.bundler \
            --tflite-model ./tensorio_bundler/fixtures/test.tflite \
            --model-json ./tensorio_bundler/fixtures/test.tiobundle/model.json \
            --assets-dir ./tensorio_bundler/fixtures/test.tiobundle/assets \
            --bundle-name sample.tiobundle \
            --outfile sample.tiobundle.zip
        ```
        
        
        ## Calling the bundler locally through the REST API
        
        To run the REST API locally from project root (same directory as this README):
        ```
        gunicorn tensorio_bundler.rest:api
        ```
        
        In a separate terminal window, you can invoke the bundler as follows:
        ```
        TFLITE_PATH="\"$(mktemp -d)/model.tflite\""
        
        read -r -d '' REQUEST_BODY <<-EOF
            {
                "saved_model_dir": "./tensorio_bundler/fixtures/test-model",
                "build": true,
                "tflite_path": $TFLITE_PATH,
                "model_json_path": "./tensorio_bundler/fixtures/test.tiobundle/model.json",
                "assets_path": "./tensorio_bundler/fixtures/test.tiobundle/assets",
                "bundle_name": "curl-test.tiobundle",
                "bundle_output_path": "curl-test.tiobundle.zip"
            }
        EOF
        
        curl -v -X POST \
            -H "Content-Type: application/json" \
            -d "$REQUEST_BODY" \
            http://localhost:8000/bundle
        ```
        
        
        ## Running the bundler via docker
        
        ### Requirements
        + Docker
        
        If you don't have it, [get it](https://docs.docker.com/install/linux/docker-ce/ubuntu/)
        
        ### Instructions
        You can either bind mount the paths to the inputs into your docker container when you run the
        bundler or you can bind mount in a service account credentials file and set the
        `GOOGLE_APPLICATION_CREDENTIALS` environment variable to point at the mount path in the container.
        
        NOTE: These instructions are extremely sparse at the moment. They will not be so forever.
        
        
        ## Running tests if you want to contribute to this project
        
        ### Requirements
        + Docker
        
        If you don't have it, [get it](https://docs.docker.com/install/linux/docker-ce/ubuntu/)
        
        ### Instructions
        Simply run:
        ```
        ./test.sh
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries
Description-Content-Type: text/markdown
