parameters: (path)
docstring: An iterator for reading `Event` protocol buffers from an event file.
  
    You can use this function to read events written to an event file. It returns
    a Python iterator that yields `Event` protocol buffers.
  
    Example: Print the contents of an events file.
  
    ```python
    for e in tf.compat.v1.train.summary_iterator(path to events file):
        print(e)
    ```
  
    Example: Print selected summary values.
  
    ```python
    # This example supposes that the events file contains summaries with a
    # summary value tag 'loss'.  These could have been added by calling
    # `add_summary()`, passing the output of a scalar summary op created with
    # with: `tf.compat.v1.summary.scalar('loss', loss_tensor)`.
    for e in tf.compat.v1.train.summary_iterator(path to events file):
        for v in e.summary.value:
            if v.tag == 'loss':
                print(v.simple_value)
    ```
  
    See the protocol buffer definitions of
    [Event](https://www.tensorflow.org/code/tensorflow/core/util/event.proto)
    and
    [Summary](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
    for more information about their attributes.
  
    Args:
      path: The path to an event file created by a `SummaryWriter`.
  
    Yields:
      `Event` protocol buffers.
docstring_summary: An iterator for reading `Event` protocol buffers from an event file.
docstring_tokens: An iterator for reading Event protocol buffers from an event file .
function: def summary_iterator(path):
    # pylint: disable=line-too-long
    """An iterator for reading `Event` protocol buffers from an event file.
  
    You can use this function to read events written to an event file. It returns
    a Python iterator that yields `Event` protocol buffers.
  
    Example: Print the contents of an events file.
  
    ```python
    for e in tf.compat.v1.train.summary_iterator(path to events file):
        print(e)
    ```
  
    Example: Print selected summary values.
  
    ```python
    # This example supposes that the events file contains summaries with a
    # summary value tag 'loss'.  These could have been added by calling
    # `add_summary()`, passing the output of a scalar summary op created with
    # with: `tf.compat.v1.summary.scalar('loss', loss_tensor)`.
    for e in tf.compat.v1.train.summary_iterator(path to events file):
        for v in e.summary.value:
            if v.tag == 'loss':
                print(v.simple_value)
    ```
  
    See the protocol buffer definitions of
    [Event](https://www.tensorflow.org/code/tensorflow/core/util/event.proto)
    and
    [Summary](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
    for more information about their attributes.
  
    Args:
      path: The path to an event file created by a `SummaryWriter`.
  
    Yields:
      `Event` protocol buffers.
    """
    # pylint: enable=line-too-long
    for r in tf_record.tf_record_iterator(path):
      yield event_pb2.Event.FromString(r)
function_tokens: def summary_iterator ( path ) : # pylint: disable=line-too-long # pylint: enable=line-too-long for r in tf_record . tf_record_iterator ( path ) : yield event_pb2 . Event . FromString ( r )