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):
      return 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: Fix implementation of with_dependencies()