parameters: (self, value, name=None)
docstring: Pack the values of a `Tensor` in the TensorArray.
  
      Args:
        value: (N+1)-D.  Tensor of type `dtype`.  The Tensor to unpack.
        name: A name for the operation (optional).
  
      Returns:
        A new TensorArray object with flow that ensures the unpack occurs.
        Use this object all for subsequent operations.
  
      Raises:
        ValueError: if the shape inference fails.
docstring_summary: Pack the values of a `Tensor` in the TensorArray.
docstring_tokens: Pack the values of a Tensor in the TensorArray .
function: def unpack(self, value, name=None):
      """Pack the values of a `Tensor` in the TensorArray.
  
      Args:
        value: (N+1)-D.  Tensor of type `dtype`.  The Tensor to unpack.
        name: A name for the operation (optional).
  
      Returns:
        A new TensorArray object with flow that ensures the unpack occurs.
        Use this object all for subsequent operations.
  
      Raises:
        ValueError: if the shape inference fails.
      """
      with ops.colocate_with(self._handle):
        flow_out = gen_data_flow_ops._tensor_array_unpack(
            handle=self._handle, value=value, flow_in=self._flow,
            name=name)
        ta = TensorArray(dtype=self._dtype, handle=self._handle)
        ta._flow = flow_out
        ta._infer_shape = self._infer_shape
        ta._elem_shape = self._elem_shape
        if ta._infer_shape:
          val_shape = flow_out.op.inputs[1].get_shape()
          elem_shape = tensor_shape.unknown_shape()
          if val_shape.dims is not None:
            elem_shape = tensor_shape.TensorShape(val_shape.dims[1:])
          if ta._elem_shape:
            if not elem_shape == ta._elem_shape[0]:
              raise ValueError(
                  "Inconsistent shapes: saw %s but expected %s "
                  "(and infer_shape=True)" % (elem_shape, ta._elem_shape[0]))
          else:
            ta._elem_shape.append(elem_shape)
        return ta
function_tokens: def unpack ( self , value , name = None ) : with ops . colocate_with ( self . _handle ) : flow_out = gen_data_flow_ops . _tensor_array_unpack ( handle = self . _handle , value = value , flow_in = self . _flow , name = name ) ta = TensorArray ( dtype = self . _dtype , handle = self . _handle ) ta . _flow = flow_out ta . _infer_shape = self . _infer_shape ta . _elem_shape = self . _elem_shape if ta . _infer_shape : val_shape = flow_out . op . inputs [ 1 ] . get_shape ( ) elem_shape = tensor_shape . unknown_shape ( ) if val_shape . dims is not None : elem_shape = tensor_shape . TensorShape ( val_shape . dims [ 1 : ] ) if ta . _elem_shape : if not elem_shape == ta . _elem_shape [ 0 ] : raise ValueError ( "Inconsistent shapes: saw %s but expected %s " "(and infer_shape=True)" % ( elem_shape , ta . _elem_shape [ 0 ] ) ) else : ta . _elem_shape . append ( elem_shape ) return ta