(minval=0, maxval=None, seed=None,
                           dtype=dtypes.float32)
return _initializer
Returns an initializer that generates tensors with an exponential distribution.

    Args:
      minval: A python scalar or a scalar tensor. Lower bound of the range
        of random values to generate.
      maxval: A python scalar or a scalar tensor. Upper bound of the range
        of random values to generate.  Defaults to 1 for float types.
      seed: A Python integer. Used to create random seeds. See
        [`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
        for behavior.
      dtype: The data type.

    Returns:
      An initializer that generates tensors with an exponential distribution.
Returns an initializer that generates tensors with an exponential distribution.
Returns an initializer that generates tensors with an exponential distribution .
def random_exp_initializer(minval=0, maxval=None, seed=None,
                           dtype=dtypes.float32):
    """Returns an initializer that generates tensors with an exponential distribution.

    Args:
      minval: A python scalar or a scalar tensor. Lower bound of the range
        of random values to generate.
      maxval: A python scalar or a scalar tensor. Upper bound of the range
        of random values to generate.  Defaults to 1 for float types.
      seed: A Python integer. Used to create random seeds. See
        [`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
        for behavior.
      dtype: The data type.

    Returns:
      An initializer that generates tensors with an exponential distribution.
    """
    
    def _initializer(shape, dtype=dtype, partition_info=None):
        return tf.exp(random_ops.random_uniform(shape, minval, maxval, dtype, seed=seed))
    
    return _initializer
def random_exp_initializer ( minval = 0 , maxval = None , seed = None , dtype = dtypes . float32 ) : def _initializer ( shape , dtype = dtype , partition_info = None ) : return tf . exp ( random_ops . random_uniform ( shape , minval , maxval , dtype , seed = seed ) ) return _initializer