feature_column.py 文件源码

def insert_transformed_feature(self, columns_to_tensors):
    """Apply transformation and inserts it into columns_to_tensors.

    Args:
      columns_to_tensors: A mapping from feature columns to tensors. 'string'
        key means a base feature (not-transformed). It can have _FeatureColumn
        as a key too. That means that _FeatureColumn is already transformed.
    """
    # Transform the input tensor according to the normalizer function + reshape.
    input_tensor = self._normalized_input_tensor(columns_to_tensors[self.name])
    batch_size = input_tensor.get_shape().as_list()[0]
    batch_size = int(batch_size) if batch_size else -1
    flattened_shape = [batch_size, self.dimension]
    columns_to_tensors[self] = array_ops.reshape(
        math_ops.to_float(input_tensor), flattened_shape, name="reshape")

  # pylint: disable=unused-argument