Flow | Let your code flow

def build_graph(device, n, m, k, transpose_a, transpose_b, dtype):
  """Build a graph containing a sequence of matmul operations.

  Args:
    device: String, the device to run on.
    n: tensor A's first dimension size.
    m: tensor A's second dime  

def build_ta_with_new_flow(old_ta, flow):
  """Builds a TensorArray with a new `flow` tensor."""
  # Sometimes we get old_ta as the implementation, sometimes it's the
  # TensorArray wrapper object.
  impl = (old_ta._implementation if isinstance(old_  

def _preserve_control_flow_context(tensor):
  """Preserve the control flow context for the given tensor.

  Sets the graph context to the tensor's context so that side effect ops are
  added under the same context.

  This is needed when subscribing