phased_lstm.py 文件源码

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


# Register the gradient for the mod operation. tf.mod() does not have a gradient implemented.