parameters: (self, sequence: Any)
docstring: Appends sequence of data to the internal buffer.
  
      Each element in `sequence` must have the same leading dimension [T].
  
      A call to `append_sequence` is equivalent to splitting `sequence` along its
      first dimension and calling `append` once for each slice.
  
      For example:
  
      ```python
  
        with client.writer(max_sequence_length=2) as writer:
          sequence = np.array([[1, 2, 3],
                               [4, 5, 6]])
  
          # Insert two timesteps.
          writer.append_sequence([sequence])
  
          # Create an item that references the step [4, 5, 6].
          writer.create_item('my_table', num_timesteps=1, priority=1.0)
  
          # Create an item that references the steps [1, 2, 3] and [4, 5, 6].
          writer.create_item('my_table', num_timesteps=2, priority=1.0)
  
      ```
  
      Is equivalent to:
  
      ```python
  
        with client.writer(max_sequence_length=2) as writer:
          # Insert two timesteps.
          writer.append([np.array([1, 2, 3])])
          writer.append([np.array([4, 5, 6])])
  
          # Create an item that references the step [4, 5, 6].
          writer.create_item('my_table', num_timesteps=1, priority=1.0)
  
          # Create an item that references the steps [1, 2, 3] and [4, 5, 6].
          writer.create_item('my_table', num_timesteps=2, priority=1.0)
  
      ```
  
      Args:
        sequence: Batched (possibly nested) structure to make available for items
          to reference.
docstring_summary: Appends sequence of data to the internal buffer.
docstring_tokens: Appends sequence of data to the internal buffer .
function: def append_sequence(self, sequence: Any):
      """Appends sequence of data to the internal buffer.
  
      Each element in `sequence` must have the same leading dimension [T].
  
      A call to `append_sequence` is equivalent to splitting `sequence` along its
      first dimension and calling `append` once for each slice.
  
      For example:
  
      ```python
  
        with client.writer(max_sequence_length=2) as writer:
          sequence = np.array([[1, 2, 3],
                               [4, 5, 6]])
  
          # Insert two timesteps.
          writer.append_sequence([sequence])
  
          # Create an item that references the step [4, 5, 6].
          writer.create_item('my_table', num_timesteps=1, priority=1.0)
  
          # Create an item that references the steps [1, 2, 3] and [4, 5, 6].
          writer.create_item('my_table', num_timesteps=2, priority=1.0)
  
      ```
  
      Is equivalent to:
  
      ```python
  
        with client.writer(max_sequence_length=2) as writer:
          # Insert two timesteps.
          writer.append([np.array([1, 2, 3])])
          writer.append([np.array([4, 5, 6])])
  
          # Create an item that references the step [4, 5, 6].
          writer.create_item('my_table', num_timesteps=1, priority=1.0)
  
          # Create an item that references the steps [1, 2, 3] and [4, 5, 6].
          writer.create_item('my_table', num_timesteps=2, priority=1.0)
  
      ```
  
      Args:
        sequence: Batched (possibly nested) structure to make available for items
          to reference.
      """
      self._writer.AppendSequence(tree.flatten(sequence))
function_tokens: def append_sequence ( self , sequence : Any ) : self . _writer . AppendSequence ( tree . flatten ( sequence ) )