message: Add normalizer_fn support for sequence_numeric_column
  This fix tries to address the issue raised in 19628
  where there were no normalizer_fn support for sequence_numeric_column
  (unlike numeric_column). This fix adds the normalizer_fn support.
  This fix fixes 19628.
diff: @@ -346,7 +346,8 @@ def sequence_numeric_column(
  key,
  shape=(1,),
  default_value=0.,
  - dtype=dtypes.float32):
  + dtype=dtypes.float32,
  + normalizer_fn=None):
  """Returns a feature column that represents sequences of numeric data.
  Example:
  @@ -383,12 +384,15 @@ def sequence_numeric_column(
  if not (dtype.is_integer or dtype.is_floating):
  raise ValueError('dtype must be convertible to float. '
  'dtype: {}, key: {}'.format(dtype, key))
  + if normalizer_fn is not None and not callable(normalizer_fn):
  + raise TypeError('normalizer_fn must be a callable. Given: {}'.format(normalizer_fn))
  return _SequenceNumericColumn(
  key,
  shape=shape,
  default_value=default_value,
  - dtype=dtype)
  + dtype=dtype,
  + normalizer_fn=normalizer_fn)
  def _assert_all_equal_and_return(tensors, name=None):
  @@ -407,7 +411,7 @@ class _SequenceNumericColumn(
  fc._SequenceDenseColumn,
  collections.namedtuple(
  '_SequenceNumericColumn',
  - ['key', 'shape', 'default_value', 'dtype'])):
  + ['key', 'shape', 'default_value', 'dtype', 'normalizer_fn'])):
  """Represents sequences of numeric data."""
  @property
  @@ -419,7 +423,10 @@ class _SequenceNumericColumn(
  return {self.key: parsing_ops.VarLenFeature(self.dtype)}
  def _transform_feature(self, inputs):
  - return inputs.get(self.key)
  + input_tensor = inputs.get(self.key)
  + if self.normalizer_fn is not None:
  + input_tensor = self.normalizer_fn(input_tensor)
  + return input_tensor
  @property
  def _variable_shape(self):
  