message: Tweaks for tf.random.uniform documentation
  tf.compat.v1.set_random_seed -> tf.random.set_seed
  Added some doctested examples
  Clarified the "seed" argument behavior
diff: @@ -205,18 +205,45 @@ def random_uniform(shape,
  `maxval - minval` significantly smaller than the range of the output (either
  `2**32` or `2**64`).
  + Examples:
  +
  + >>> tf.random.uniform(shape=[2])
  + <tf.Tensor: id=..., shape=(2,), dtype=float32, numpy=array([..., ...],
  + dtype=float32)>
  + >>> tf.random.uniform(shape=[], minval=-1., maxval=0.)
  + <tf.Tensor: id=..., shape=(), dtype=float32, numpy=-...>
  + >>> tf.random.uniform(shape=[], minval=5, maxval=10, dtype=tf.int64)
  + <tf.Tensor: id=..., shape=(), dtype=int64, numpy=...>
  +
  + The `seed` argument produces a deterministic sequence of tensors across
  + multiple calls. To repeat that sequence, use `tf.random.set_seed`:
  +
  + >>> tf.random.set_seed(5)
  + >>> tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)
  + <tf.Tensor: id=..., shape=(), dtype=int32, numpy=2>
  + >>> tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)
  + <tf.Tensor: id=..., shape=(), dtype=int32, numpy=0>
  + >>> tf.random.set_seed(5)
  + >>> tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)
  + <tf.Tensor: id=..., shape=(), dtype=int32, numpy=2>
  + >>> tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)
  + <tf.Tensor: id=..., shape=(), dtype=int32, numpy=0>
  +
  + Without `tf.random.set_seed` but with a `seed` argument is specified, small
  + changes to function graphs or previously executed operations will change the
  + returned value. See `tf.random.set_seed` for details.
  +
  Args:
  shape: A 1-D integer Tensor or Python array. The shape of the output tensor.
  minval: A 0-D Tensor or Python value of type `dtype`. The lower bound on the
  - range of random values to generate. Defaults to 0.
  - maxval: A 0-D Tensor or Python value of type `dtype`. The upper bound on
  - the range of random values to generate. Defaults to 1 if `dtype` is
  - floating point.
  + range of random values to generate (inclusive). Defaults to 0.
  + maxval: A 0-D Tensor or Python value of type `dtype`. The upper bound on the
  + range of random values to generate (exclusive). Defaults to 1 if `dtype`
  + is floating point.
  dtype: The type of the output: `float16`, `float32`, `float64`, `int32`,
  or `int64`.
  - seed: A Python integer. Used to create a random seed for the distribution.
  - See `tf.compat.v1.set_random_seed`
  - for behavior.
  + seed: A Python integer. Used in combination with `tf.random.set_seed` to
  + create a reproducible sequence of tensors across multiple calls.
  name: A name for the operation (optional).
  Returns:
  