tensorflow_probability/python/layers/distribution_layer.py
def params_size(num_components, component_params_size, name=None):
    """Number of `params` needed to create a `MixtureSameFamily` distribution.

    Arguments:
      num_components: Number of component distributions in the mixture
        distribution.
      component_params_size: Number of parameters needed to create a single
        component distribution.
      name: The name to use for the op to compute the number of parameters
        (if such an op needs to be created).

    Returns:
     params_size: The number of parameters needed to create the mixture
       distribution.
    """
    with tf.compat.v1.name_scope(name, 'MixtureSameFamily_params_size',
                                 [num_components, component_params_size]):
      num_components = tf.convert_to_tensor(
          value=num_components, name='num_components', dtype_hint=tf.int32)
      component_params_size = tf.convert_to_tensor(
          value=component_params_size, name='component_params_size')

      num_components = dist_util.prefer_static_value(num_components)
      component_params_size = dist_util.prefer_static_value(
          component_params_size)

      return num_components + num_components * component_params_size
def params_size(num_components, component_params_size, name=None):
    """Number of `params` needed to create a `MixtureSameFamily` distribution.

    Arguments:
      num_components: Number of component distributions in the mixture
        distribution.
      component_params_size: Number of parameters needed to create a single
        component distribution.
      name: The name to use for the op to compute the number of parameters
        (if such an op needs to be created).

    Returns:
     params_size: The number of parameters needed to create the mixture
       distribution.
    """
    with tf.compat.v1.name_scope(name, 'MixtureSameFamily_params_size',
                                 [num_components, component_params_size]):
      num_components = tf.convert_to_tensor(
          value=num_components, name='num_components', dtype_hint=tf.int32)
      component_params_size = tf.convert_to_tensor(
          value=component_params_size, name='component_params_size')

      num_components = dist_util.prefer_static_value(num_components)
      component_params_size = dist_util.prefer_static_value(
          component_params_size)

      return num_components + num_components * component_params_size
def params_size ( num_components , component_params_size , name = None ) : with tf . compat . v1 . name_scope ( name , 'MixtureSameFamily_params_size' , [ num_components , component_params_size ] ) : num_components = tf . convert_to_tensor ( value = num_components , name = 'num_components' , dtype_hint = tf . int32 ) component_params_size = tf . convert_to_tensor ( value = component_params_size , name = 'component_params_size' ) num_components = dist_util . prefer_static_value ( num_components ) component_params_size = dist_util . prefer_static_value ( component_params_size ) return num_components + num_components * component_params_size
Number of `params` needed to create a `MixtureSameFamily` distribution.

    Arguments:
      num_components: Number of component distributions in the mixture
        distribution.
      component_params_size: Number of parameters needed to create a single
        component distribution.
      name: The name to use for the op to compute the number of parameters
        (if such an op needs to be created).

    Returns:
     params_size: The number of parameters needed to create the mixture
       distribution.
Number of params needed to create a MixtureSameFamily distribution .