parameters: (num_elements, seed, dtype=tf.float32)
return_statement: return tf.cast(_cmwc_random_sequence(num_elements, seed), dtype)
docstring: Returns a Tensor of `num_elements` random values in [0, 1) as `dtype`.
docstring_summary: Returns a Tensor of `num_elements` random values in [0, 1) as `dtype`.
docstring_tokens: Returns a Tensor of num_elements random values in [ 0 1 ) as dtype .
function: def random_floats_cmwc(num_elements, seed, dtype=tf.float32):
    """Returns a Tensor of `num_elements` random values in [0, 1) as `dtype`."""
    if dtype not in [tf.float32, tf.float64]:
      raise TypeError(
          'Unsupported type: %s. Supported types are tf.float32 and '
          'tf.float64 values' % dtype)
    return tf.cast(_cmwc_random_sequence(num_elements, seed), dtype)
function_tokens: def random_floats_cmwc ( num_elements , seed , dtype = tf . float32 ) : if dtype not in [ tf . float32 , tf . float64 ] : raise TypeError ( 'Unsupported type: %s. Supported types are tf.float32 and ' 'tf.float64 values' % dtype ) return tf . cast ( _cmwc_random_sequence ( num_elements , seed ) , dtype )