Metadata-Version: 2.1
Name: alt-model-checkpoint
Version: 2.0.1
Summary: An adapter callback for Keras ModelCheckpoint that allows checkpointing an alternate model (often submodel of a multi-GPU model).
Home-page: https://github.com/TextpertAi/alt-model-checkpoint
Author: Ezekiel Victor
Author-email: zekevictor@gmail.com
License: UNKNOWN
Description: # alt-model-checkpoint
        
        An adapter callback for Keras [ModelCheckpoint](https://keras.io/callbacks/#modelcheckpoint) that allows checkpointing
        an alternate model (often submodel of a multi-GPU model).
        
        ## Installation
        
        ```bash
        pip install alt-model-checkpoint
        ```
        
        ## Usage
        
        *You must provide your own Keras or Tensorflow installation.* See `Pipfile` for preferred versions.
        
        
        If using the Keras bundled in Tensorflow:
        
        ```python
        from alt_model_checkpoint.tensorflow import AltModelCheckpoint
        ```
        
        If using Keras standalone:
        
        ```python
        from alt_model_checkpoint.keras import AltModelCheckpoint
        ```
        
        Common usage involving multi-GPU models built with Keras `multi_gpu_model()`:
        
        ```python
        from alt_model_checkpoint.keras import AltModelCheckpoint
        from keras.models import Model
        from keras.utils import multi_gpu_model
        
        base_model = Model(...)
        gpu_model = multi_gpu_model(base_model)
        gpu_model.compile(...)
        
        gpu_model.fit(..., callbacks=[
            AltModelCheckpoint('save/path/for/model.hdf5', base_model)
        ])
        ```
        
        ## Constructor args
        
        ### filepath
        
        Model save file path; see [underlying ModelCheckpoint docs](https://keras.io/callbacks/#modelcheckpoint) for details.
        
        ### alternate_model
        
        Keras model to save instead of the default. This is used especially when training multi-gpu models built with Keras
        multi_gpu_model(). In that case, you would pass the original "template model" to be saved each checkpoint.
        
        ### inherit_optimizer
        
        If TRUE (default), saves the optimizer of the base model (e.g. a multi-gpu model) with the alternate model. This is
        necessary if you want to be able to resume training on a saved alternate model. If FALSE, the alternate model's
        optimizer will be saved as-is.
        
        ### *args, **kwargs
        
        These are passed as-is to the underlying [ModelCheckpoint](https://keras.io/callbacks/#modelcheckpoint) constructor.
        
        ## Dev environment setup
        
        1. Install [pipenv](https://docs.pipenv.org/install/).
        2. Run `make test` (runs `make test-build` automatically to ensure deps)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
