Metadata-Version: 2.1
Name: tfjs-graph-converter
Version: 1.0.1
Summary: A tensorflowjs Graph Model Converter
Home-page: https://github.com/patlevin/tfjs-to-tf/
Author: Patrick Levin
Author-email: vertical-pink@protonmail.com
License: UNKNOWN
Description: # TensorFlow.js Graph Model Converter
        
        ![TFJS Graph Converter Logo](/docs/logo.png)
        
        The purpose of this library is to import TFJS graph models into Tensorflow.
        This allows you to use TensorFlow.js models with Python in case you don't
        have access to the original formats or the models have been created in TFJS.
        
        ## Disclaimer
        
        I'm neither a Python developer, nor do I know TensorFlow or TensorFlow.js.
        I created this package solely because I ran into an issue when trying to convert
        a pretrained TensorFlow.js model into a different format. I didn't have access to
        the pretrained original TF model and didn't have the resources to train it myself.
        I soon learned that I'm not alone with this [issue](https://github.com/tensorflow/tfjs/issues/1575)
        so I sat down and wrote this little library.
        
        If you find any part of the code to be non-idiomatic or know of a simpler way to
        achieve certain things, feel free to let me know, since I'm a beginner in both
        Python and especially TensorFlow (used it for the very first time in this
        very project).
        
        ## Prerequisites
        
        * tensorflow 2.1+
        * tensorflowjs 1.5.2+
        
        ## Compatibility
        
        The converter has been tested with tensorflowjs v1.7.2 and tensorflow v2.1.
        The Python version used was Python 3.7.7.
        
        ## Installation
        
        ```sh
        pip install tfjs-graph-converter
        ```
        
        ## Usage
        
        After the installation, you can run the packaged `tfjs_graph_converter` binary
        for quick and easy model conversion.
        
        ### Positional Arguments
        
         | Positional Argument | Description |
         | :--- | :--- |
         | `input_path` | Path to the TFJS Graph Model directory containing the model.json |
         | `output_path` | For output format "tf_saved_model", a SavedModel target directory. For output format "tf_frozen_model", a frozen model file. |
        
        ### Options
        
        | Option | Description |
        | :--- | :--- |
        | `-h`, `--help` | Show help message and exit |
        | `--output_format` | Use `tf_frozen_model` (the default) to save a Tensorflow frozen model. `tf_saved_model` exports to a Tensorflow _SavedModel_ instead. |
         | `--saved_model_tags` | Specifies the tags of the MetaGraphDef to save, in comma separated string format. Defaults to "serve". Applicable only if `--output format` is `tf_saved_model` |
         | `-v`, `--version` | Shows the version of the converter and its dependencies. |
         | `-s`, `--silent` | Suppresses any output besides error messages. |
        
        Alternatively, you can create your own converter programs using the module's API.
        The API is required to accomplish more complicated tasks, like packaging multiple
        TensorFlow.js models into a single SavedModel.
        
        ## Example
        
        To convert a TensorFlow.js graph model to a TensorFlow frozen model (i.e. the
        most common use case?), just specify the directory containing the `model.json`,
        followed by the path and file name of the frozen model like so:
        
        ```sh
        tfjs_graph_converter path/to/js/model path/to/frozen/model.pb
        ```
        
        ## Usage from within Python
        
        The package installs the module `tfjs_graph_converter`, which contains all the
        functionality used by the converter script.
        You can leverage the API to either load TensorFlow.js graph models directly for
        use with your TensorFlow program (e.g. for inference, fine-tuning, or extending),
        or use the advanced functionality to combine several TFJS models into a single
        `SavedModel`.
        The latter is only supported using the API (it's just a single function call,
        though, so don't panic ðŸ˜‰)
        
        [API Documentation](./docs/modules.rst)
        
Keywords: tensorflow tensorflowjs converter
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6
Description-Content-Type: text/markdown
