tensorflow_probability/python/layers/distribution_layer.py
def get_config(self):
    """Returns the config of this layer.

    NOTE: At the moment, this configuration can only be serialized if the
    Layer's `convert_to_tensor_fn` is a serializable Keras object (i.e.,
    implements `get_config`) or one of the standard values:
     - `Distribution.sample` (or `"sample"`)
     - `Distribution.mean` (or `"mean"`)
     - `Distribution.mode` (or `"mode"`)
     - `Distribution.stddev` (or `"stddev"`)
     - `Distribution.variance` (or `"variance"`)
    """
    config = {
        'event_shape': self._event_shape,
        'convert_to_tensor_fn': _serialize(self._convert_to_tensor_fn),
        'sample_dtype': self._sample_dtype,
        'validate_args': self._validate_args
    }
    base_config = super(IndependentBernoulli, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))
def get_config(self):
    """Returns the config of this layer.

    NOTE: At the moment, this configuration can only be serialized if the
    Layer's `convert_to_tensor_fn` is a serializable Keras object (i.e.,
    implements `get_config`) or one of the standard values:
     - `Distribution.sample` (or `"sample"`)
     - `Distribution.mean` (or `"mean"`)
     - `Distribution.mode` (or `"mode"`)
     - `Distribution.stddev` (or `"stddev"`)
     - `Distribution.variance` (or `"variance"`)
    """
    config = {
        'event_shape': self._event_shape,
        'convert_to_tensor_fn': _serialize(self._convert_to_tensor_fn),
        'sample_dtype': self._sample_dtype,
        'validate_args': self._validate_args
    }
    base_config = super(IndependentBernoulli, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))
def get_config ( self ) : config = { 'event_shape' : self . _event_shape , 'convert_to_tensor_fn' : _serialize ( self . _convert_to_tensor_fn ) , 'sample_dtype' : self . _sample_dtype , 'validate_args' : self . _validate_args } base_config = super ( IndependentBernoulli , self ) . get_config ( ) return dict ( list ( base_config . items ( ) ) + list ( config . items ( ) ) )
Returns the config of this layer.

    NOTE: At the moment, this configuration can only be serialized if the
    Layer's `convert_to_tensor_fn` is a serializable Keras object (i.e.,
    implements `get_config`) or one of the standard values:
     - `Distribution.sample` (or `"sample"`)
     - `Distribution.mean` (or `"mean"`)
     - `Distribution.mode` (or `"mode"`)
     - `Distribution.stddev` (or `"stddev"`)
     - `Distribution.variance` (or `"variance"`)
Returns the config of this layer .