old_contents: import functools
  import tensorflow as tf
  
  from .util import func_scope
  
  
  @func_scope()
  def unpack_to_array(tensor):
      return tf.TensorArray(tensor.dtype, tf.shape(tensor)[0]).unpack(tensor)
  
  
  @func_scope()
  def with_dependencies(dependencies, tensor):
      """
      This function is documented partially in tensorflow.org.
      But, it cannot be found in a library.
      """
      with tf.control_dependencies(dependencies):
          if isinstance(tensor, tf.Tensor):
              return tf.identity(tensor)
          elif isinstance(tensor, tf.Operation):
              return tf.group(tensor)
          raise ValueError(
              "{} must be tf.Tensor or tf.Operation.".format(tensor))
  
  
  @func_scope()
  def sequential(*ops):
      return functools.reduce(lambda x, y: with_dependencies([x], y), ops)
  
new_contents: import functools
  import tensorflow as tf
  
  from .util import func_scope
  
  
  @func_scope()
  def unpack_to_array(tensor):
      return tf.TensorArray(tensor.dtype, tf.shape(tensor)[0]).unpack(tensor)
  
  
  @func_scope()
  def with_dependencies(dependencies, tensor):
      """
      This function is documented partially in tensorflow.org.
      But, it cannot be found in a library.
      """
      with tf.control_dependencies(dependencies):
          if isinstance(tensor, tf.Tensor):
              return tf.identity(tensor)
          elif isinstance(tensor, tf.Operation):
              return tf.group(tensor)
  
          raise ValueError("{} must be tf.Tensor or tf.Operation."
                           .format(tensor))
  
  
  @func_scope()
  def sequential(*ops):
      return functools.reduce(lambda x, y: with_dependencies([x], y), ops)
  
subject: Format control module