dataset_schema.py 文件源码

def infer_column_schema_from_tensor(tensor):
  """Infer a ColumnSchema from a tensor."""
  if isinstance(tensor, tf.SparseTensor):
    # For SparseTensor, there's insufficient information to distinguish between
    # ListColumnRepresentation and SparseColumnRepresentation. So we just guess
    # the former, and callers are expected to handle the latter case on their
    # own (e.g. by requiring the user to provide the schema). This is a policy
    # motivated by the prevalence of VarLenFeature in current tf.Learn code.
    axes = [Axis(None)]
    representation = ListColumnRepresentation()
  else:
    axes = _shape_to_axes(tensor.get_shape(),
                          remove_batch_dimension=True)
    representation = FixedColumnRepresentation()
  return ColumnSchema(tensor.dtype, axes, representation)