easy_rec/python/compat/feature_column/feature_column_v2.py [3238:3302]:
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        ('categorical_column', 'weight_feature_key', 'dtype'))):
  """See `weighted_categorical_column`."""

  @property
  def _is_v2_column(self):
    return (isinstance(self.categorical_column, FeatureColumn) and
            self.categorical_column._is_v2_column)  # pylint: disable=protected-access

  @property
  def name(self):
    """See `FeatureColumn` base class."""
    return '{}_weighted_by_{}'.format(self.categorical_column.name,
                                      self.weight_feature_key)

  @property
  def raw_name(self):
    """See `FeatureColumn` base class."""
    return self.categorical_column.raw_name

  @property
  def parse_example_spec(self):
    """See `FeatureColumn` base class."""
    config = self.categorical_column.parse_example_spec
    if self.weight_feature_key in config:
      raise ValueError('Parse config {} already exists for {}.'.format(
          config[self.weight_feature_key], self.weight_feature_key))
    config[self.weight_feature_key] = parsing_ops.VarLenFeature(self.dtype)
    return config

  @property
  @deprecation.deprecated(_FEATURE_COLUMN_DEPRECATION_DATE,
                          _FEATURE_COLUMN_DEPRECATION)
  def _parse_example_spec(self):
    config = self.categorical_column._parse_example_spec  # pylint: disable=protected-access
    if self.weight_feature_key in config:
      raise ValueError('Parse config {} already exists for {}.'.format(
          config[self.weight_feature_key], self.weight_feature_key))
    config[self.weight_feature_key] = parsing_ops.VarLenFeature(self.dtype)
    return config

  @property
  def num_buckets(self):
    """See `DenseColumn` base class."""
    return self.categorical_column.num_buckets

  @property
  @deprecation.deprecated(_FEATURE_COLUMN_DEPRECATION_DATE,
                          _FEATURE_COLUMN_DEPRECATION)
  def _num_buckets(self):
    return self.categorical_column._num_buckets  # pylint: disable=protected-access

  def _transform_weight_tensor(self, weight_tensor):
    if weight_tensor is None:
      raise ValueError('Missing weights {}.'.format(self.weight_feature_key))
    weight_tensor = sparse_tensor_lib.convert_to_tensor_or_sparse_tensor(
        weight_tensor)
    if self.dtype != weight_tensor.dtype.base_dtype:
      raise ValueError('Bad dtype, expected {}, but got {}.'.format(
          self.dtype, weight_tensor.dtype))
    if not isinstance(weight_tensor, sparse_tensor_lib.SparseTensor):
      # The weight tensor can be a regular Tensor. In this case, sparsify it.
      weight_tensor = _to_sparse_input_and_drop_ignore_values(
          weight_tensor, ignore_value=0.0)
    if not weight_tensor.dtype.is_floating:
      weight_tensor = math_ops.cast(weight_tensor, dtypes.float32)
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easy_rec/python/compat/feature_column/feature_column_v2.py [4358:4422]:
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        ('categorical_column', 'weight_feature_key', 'dtype'))):
  """See `weighted_categorical_column`."""

  @property
  def _is_v2_column(self):
    return (isinstance(self.categorical_column, FeatureColumn) and
            self.categorical_column._is_v2_column)  # pylint: disable=protected-access

  @property
  def name(self):
    """See `FeatureColumn` base class."""
    return '{}_weighted_by_{}'.format(self.categorical_column.name,
                                      self.weight_feature_key)

  @property
  def raw_name(self):
    """See `FeatureColumn` base class."""
    return self.categorical_column.raw_name

  @property
  def parse_example_spec(self):
    """See `FeatureColumn` base class."""
    config = self.categorical_column.parse_example_spec
    if self.weight_feature_key in config:
      raise ValueError('Parse config {} already exists for {}.'.format(
          config[self.weight_feature_key], self.weight_feature_key))
    config[self.weight_feature_key] = parsing_ops.VarLenFeature(self.dtype)
    return config

  @property
  @deprecation.deprecated(_FEATURE_COLUMN_DEPRECATION_DATE,
                          _FEATURE_COLUMN_DEPRECATION)
  def _parse_example_spec(self):
    config = self.categorical_column._parse_example_spec  # pylint: disable=protected-access
    if self.weight_feature_key in config:
      raise ValueError('Parse config {} already exists for {}.'.format(
          config[self.weight_feature_key], self.weight_feature_key))
    config[self.weight_feature_key] = parsing_ops.VarLenFeature(self.dtype)
    return config

  @property
  def num_buckets(self):
    """See `DenseColumn` base class."""
    return self.categorical_column.num_buckets

  @property
  @deprecation.deprecated(_FEATURE_COLUMN_DEPRECATION_DATE,
                          _FEATURE_COLUMN_DEPRECATION)
  def _num_buckets(self):
    return self.categorical_column._num_buckets  # pylint: disable=protected-access

  def _transform_weight_tensor(self, weight_tensor):
    if weight_tensor is None:
      raise ValueError('Missing weights {}.'.format(self.weight_feature_key))
    weight_tensor = sparse_tensor_lib.convert_to_tensor_or_sparse_tensor(
        weight_tensor)
    if self.dtype != weight_tensor.dtype.base_dtype:
      raise ValueError('Bad dtype, expected {}, but got {}.'.format(
          self.dtype, weight_tensor.dtype))
    if not isinstance(weight_tensor, sparse_tensor_lib.SparseTensor):
      # The weight tensor can be a regular Tensor. In this case, sparsify it.
      weight_tensor = _to_sparse_input_and_drop_ignore_values(
          weight_tensor, ignore_value=0.0)
    if not weight_tensor.dtype.is_floating:
      weight_tensor = math_ops.cast(weight_tensor, dtypes.float32)
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