message: remove the expired forward_compatible check on random_op
diff: @@ -20,7 +20,6 @@ from __future__ import print_function
  import numpy as np
  -from tensorflow.python.compat import compat
  from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  @@ -281,8 +280,6 @@ def random_uniform(shape,
  maxval = 1
  with ops.name_scope(name, "random_uniform", [shape, minval, maxval]) as name:
  shape = tensor_util.shape_tensor(shape)
  - # TODO(b/143079601): Remove this once the compatible window is passed.
  - if compat.forward_compatible(2019, 12, 3):
  # In case of [0,1) floating results, minval and maxval is unused. We do an
  # `is` comparison here since this is cheaper than isinstance or __eq__.
  minval_is_zero = minval is 0 # pylint: disable=literal-comparison
  @@ -299,20 +296,9 @@ def random_uniform(shape,
  shape, dtype, seed=seed1, seed2=seed2)
  if minval_is_zero:
  if not maxval_is_one:
  - result = result * maxval
  + result = math_ops.multiply(result, maxval)
  else:
  result = math_ops.add(result * (maxval - minval), minval, name=name)
  - else:
  - minval = ops.convert_to_tensor(minval, dtype=dtype, name="min")
  - maxval = ops.convert_to_tensor(maxval, dtype=dtype, name="max")
  - seed1, seed2 = random_seed.get_seed(seed)
  - if dtype.is_integer:
  - result = gen_random_ops.random_uniform_int(
  - shape, minval, maxval, seed=seed1, seed2=seed2, name=name)
  - else:
  - rnd = gen_random_ops.random_uniform(
  - shape, dtype, seed=seed1, seed2=seed2)
  - result = math_ops.add(rnd * (maxval - minval), minval, name=name)
  # TODO(b/132092188): C++ shape inference inside functional ops does not
  # cross FuncGraph boundaries since that information is only available in
  # python. So we manually get the static shape using
  