message: Add missing args in description for LSTM and GRU
  Added time_major description for LSTM and GRU.
diff: @@ -1851,6 +1851,14 @@ class GRU(RNN):
  Unrolling can speed-up a RNN,
  although it tends to be more memory-intensive.
  Unrolling is only suitable for short sequences.
  + time_major: The shape format of the `inputs` and `outputs` tensors.
  + If True, the inputs and outputs will be in shape
  + `(timesteps, batch, ...)`, whereas in the False case, it will be
  + `(batch, timesteps, ...)`. Using `time_major = True` is a bit more
  + efficient because it avoids transposes at the beginning and end of the
  + RNN calculation. However, most TensorFlow data is batch-major, so by
  + default this function accepts input and emits output in batch-major
  + form.
  reset_after: GRU convention (whether to apply reset gate after or
  before matrix multiplication). False = "before" (default),
  True = "after" (CuDNN compatible).
  @@ -2466,6 +2474,14 @@ class LSTM(RNN):
  Unrolling can speed-up a RNN,
  although it tends to be more memory-intensive.
  Unrolling is only suitable for short sequences.
  + time_major: The shape format of the `inputs` and `outputs` tensors.
  + If True, the inputs and outputs will be in shape
  + `(timesteps, batch, ...)`, whereas in the False case, it will be
  + `(batch, timesteps, ...)`. Using `time_major = True` is a bit more
  + efficient because it avoids transposes at the beginning and end of the
  + RNN calculation. However, most TensorFlow data is batch-major, so by
  + default this function accepts input and emits output in batch-major
  + form.
  Call arguments:
  inputs: A 3D tensor.
  