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    "info": {
        "author": "Ezekiel Victor",
        "author_email": "zekevictor@gmail.com",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
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        "description": "# alt-model-checkpoint\n\nAn adapter callback for Keras [ModelCheckpoint](https://keras.io/callbacks/#modelcheckpoint) that allows checkpointing\nan alternate model (often submodel of a multi-GPU model).\n\n## Installation\n\n```bash\npip install alt-model-checkpoint\n```\n\n## Usage\n\n*You must provide your own Keras or Tensorflow installation.* See `Pipfile` for preferred versions.\n\n\nIf using the Keras bundled in Tensorflow:\n\n```python\nfrom alt_model_checkpoint.tensorflow import AltModelCheckpoint\n```\n\nIf using Keras standalone:\n\n```python\nfrom alt_model_checkpoint.keras import AltModelCheckpoint\n```\n\nCommon usage involving multi-GPU models built with Keras `multi_gpu_model()`:\n\n```python\nfrom alt_model_checkpoint.keras import AltModelCheckpoint\nfrom keras.models import Model\nfrom keras.utils import multi_gpu_model\n\nbase_model = Model(...)\ngpu_model = multi_gpu_model(base_model)\ngpu_model.compile(...)\n\ngpu_model.fit(..., callbacks=[\n    AltModelCheckpoint('save/path/for/model.hdf5', base_model)\n])\n```\n\n## Constructor args\n\n### filepath\n\nModel save file path; see [underlying ModelCheckpoint docs](https://keras.io/callbacks/#modelcheckpoint) for details.\n\n### alternate_model\n\nKeras model to save instead of the default. This is used especially when training multi-gpu models built with Keras\nmulti_gpu_model(). In that case, you would pass the original \"template model\" to be saved each checkpoint.\n\n### inherit_optimizer\n\nIf TRUE (default), saves the optimizer of the base model (e.g. a multi-gpu model) with the alternate model. This is\nnecessary if you want to be able to resume training on a saved alternate model. If FALSE, the alternate model's\noptimizer will be saved as-is.\n\n### *args, **kwargs\n\nThese are passed as-is to the underlying [ModelCheckpoint](https://keras.io/callbacks/#modelcheckpoint) constructor.\n\n## Dev environment setup\n\n1. Install [pipenv](https://docs.pipenv.org/install/).\n2. Run `make test` (runs `make test-build` automatically to ensure deps)\n\n\n",
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