module_cell.py 文件源码

def _concat(prefix, suffix, static=False):
  """Concat that enables int, Tensor, or TensorShape values.
  This function takes a size specification, which can be an integer, a
  TensorShape, or a Tensor, and converts it into a concatenated Tensor
  (if static = False) or a list of integers (if static = True).
  Args:
    prefix: The prefix; usually the batch size (and/or time step size).
      (TensorShape, int, or Tensor.)
    suffix: TensorShape, int, or Tensor.
    static: If `True`, return a python list with possibly unknown dimensions.
      Otherwise return a `Tensor`.
  Returns:
    shape: the concatenation of prefix and suffix.
  Raises:
    ValueError: if `suffix` is not a scalar or vector (or TensorShape).
    ValueError: if prefix or suffix was `None` and asked for dynamic
      Tensors out.
  """
  if isinstance(prefix, ops.Tensor):
    p = prefix
    p_static = tensor_util.constant_value(prefix)
    if p.shape.ndims == 0:
      p = array_ops.expand_dims(p, 0)
    elif p.shape.ndims != 1:
      raise ValueError("prefix tensor must be either a scalar or vector, "
                       "but saw tensor: %s" % p)
  else:
    p = tensor_shape.as_shape(prefix)
    p_static = p.as_list() if p.ndims is not None else None
    p = (constant_op.constant(p.as_list(), dtype=dtypes.int32)
         if p.is_fully_defined() else None)
  if isinstance(suffix, ops.Tensor):
    s = suffix
    s_static = tensor_util.constant_value(suffix)
    if s.shape.ndims == 0:
      s = array_ops.expand_dims(s, 0)
    elif s.shape.ndims != 1:
      raise ValueError("suffix tensor must be either a scalar or vector, "
                       "but saw tensor: %s" % s)
  else:
    s = tensor_shape.as_shape(suffix)
    s_static = s.as_list() if s.ndims is not None else None
    s = (constant_op.constant(s.as_list(), dtype=dtypes.int32)
         if s.is_fully_defined() else None)

  if static:
    shape = tensor_shape.as_shape(p_static).concatenate(s_static)
    shape = shape.as_list() if shape.ndims is not None else None
  else:
    if p is None or s is None:
      raise ValueError("Provided a prefix or suffix of None: %s and %s"
                       % (prefix, suffix))
    shape = array_ops.concat((p, s), 0)
  return shape