(shape, distribution_fn=tf.random.uniform,
                minval=-1.0, maxval=1.0, stddev=1.0, name=None)
return utils.call_with_accepted_args(
      distribution_fn, shape=shape, minval=minval, maxval=maxval,
      stddev=stddev, name=name)
Random noise distributions as TF op.

  Args:
    shape: A 1-D integer Tensor or Python array.
    distribution_fn: Function that create a Tensor. If the function has any
      of the arguments 'minval', 'maxval' or 'stddev' these are passed to it.
    minval: The lower bound on the range of random values to generate.
    maxval: The upper bound on the range of random values to generate.
    stddev: The standard deviation of a normal distribution.
    name: A name for the operation.

  Returns:
    Tensor with the given shape and dtype tf.float32.
Random noise distributions as TF op.
Random noise distributions as TF op .
def z_generator(shape, distribution_fn=tf.random.uniform,
                minval=-1.0, maxval=1.0, stddev=1.0, name=None):
  """Random noise distributions as TF op.

  Args:
    shape: A 1-D integer Tensor or Python array.
    distribution_fn: Function that create a Tensor. If the function has any
      of the arguments 'minval', 'maxval' or 'stddev' these are passed to it.
    minval: The lower bound on the range of random values to generate.
    maxval: The upper bound on the range of random values to generate.
    stddev: The standard deviation of a normal distribution.
    name: A name for the operation.

  Returns:
    Tensor with the given shape and dtype tf.float32.
  """
  return utils.call_with_accepted_args(
      distribution_fn, shape=shape, minval=minval, maxval=maxval,
      stddev=stddev, name=name)
def z_generator ( shape , distribution_fn = tf . random . uniform , minval = - 1.0 , maxval = 1.0 , stddev = 1.0 , name = None ) : return utils . call_with_accepted_args ( distribution_fn , shape = shape , minval = minval , maxval = maxval , stddev = stddev , name = name )