Python tensorflow.python.summary.writer.event_file_writer.EventFileWriter() Examples

def __init__(self, log_dir, enable=True):
    """Create a new SummaryWriter.

    Args:
      log_dir: path to record tfevents files in.
      enable: bool: if False don't actually write or flush data.  Used in
        multihost training.
    """
    # If needed, create log_dir directory as well as missing parent directories.
    if not tf.io.gfile.isdir(log_dir):
      tf.io.gfile.makedirs(log_dir)

    self._event_writer = EventFileWriter(log_dir, 10, 120, None)
    self._step = 0
    self._closed = False
    self._enabled = enable 

def reopen(self):
    """Reopens the EventFileWriter.

    Can be called after `close()` to add more events in the same directory.
    The events will go into a new events file.

    Does nothing if the EventFileWriter was not closed.
    """
    self.event_writer.reopen() 

def reopen(self):
    """Reopens the EventFileWriter.

    Can be called after `close()` to add more events in the same directory.
    The events will go into a new events file.

    Does nothing if the EventFileWriter was not closed.
    """
    self.event_writer.reopen() 

def __init__(self, log_dir):
    """Create a new SummaryWriter.

    Args:
      log_dir: path to record tfevents files in.
    """
    # If needed, create log_dir directory as well as missing parent directories.
    if not gfile.isdir(log_dir):
      gfile.makedirs(log_dir)

    self._event_writer = EventFileWriter(log_dir, 10, 120, None)
    self._step = 0
    self._closed = False 

def reopen(self):
    """Reopens the EventFileWriter.

    Can be called after `close()` to add more events in the same directory.
    The events will go into a new events file.

    Does nothing if the EventFileWriter was not closed.
    """
    self.event_writer.reopen() 

def reopen(self):
    """Reopens the EventFileWriter.

    Can be called after `close()` to add more events in the same directory.
    The events will go into a new events file.

    Does nothing if the EventFileWriter was not closed.
    """
    self.event_writer.reopen() 

def reopen(self):
    """Reopens the EventFileWriter.

    Can be called after `close()` to add more events in the same directory.
    The events will go into a new events file.

    Does nothing if the EventFileWriter was not closed.
    """
    self.event_writer.reopen() 

def __init__(self,
               logdir,
               graph=None,
               max_queue=10,
               flush_secs=120,
               graph_def=None,
               filename_suffix=None):
    """Creates a `FileWriter` and an event file.

    On construction the summary writer creates a new event file in `logdir`.
    This event file will contain `Event` protocol buffers constructed when you
    call one of the following functions: `add_summary()`, `add_session_log()`,
    `add_event()`, or `add_graph()`.

    If you pass a `Graph` to the constructor it is added to
    the event file. (This is equivalent to calling `add_graph()` later).

    TensorBoard will pick the graph from the file and display it graphically so
    you can interactively explore the graph you built. You will usually pass
    the graph from the session in which you launched it:

    ```python
    ...create a graph...
    # Launch the graph in a session.
    sess = tf.Session()
    # Create a summary writer, add the 'graph' to the event file.
    writer = tf.summary.FileWriter(<some-directory>, sess.graph)
    ```

    The other arguments to the constructor control the asynchronous writes to
    the event file:

    *  `flush_secs`: How often, in seconds, to flush the added summaries
       and events to disk.
    *  `max_queue`: Maximum number of summaries or events pending to be
       written to disk before one of the 'add' calls block.

    Args:
      logdir: A string. Directory where event file will be written.
      graph: A `Graph` object, such as `sess.graph`.
      max_queue: Integer. Size of the queue for pending events and summaries.
      flush_secs: Number. How often, in seconds, to flush the
        pending events and summaries to disk.
      graph_def: DEPRECATED: Use the `graph` argument instead.
      filename_suffix: A string. Every event file's name is suffixed with
        `suffix`.
    """
    event_writer = EventFileWriter(logdir, max_queue, flush_secs,
                                   filename_suffix)
    super(FileWriter, self).__init__(event_writer, graph, graph_def) 

def __init__(self,
               logdir,
               graph=None,
               max_queue=10,
               flush_secs=120,
               graph_def=None):
    """Creates a `FileWriter` and an event file.

    On construction the summary writer creates a new event file in `logdir`.
    This event file will contain `Event` protocol buffers constructed when you
    call one of the following functions: `add_summary()`, `add_session_log()`,
    `add_event()`, or `add_graph()`.

    If you pass a `Graph` to the constructor it is added to
    the event file. (This is equivalent to calling `add_graph()` later).

    TensorBoard will pick the graph from the file and display it graphically so
    you can interactively explore the graph you built. You will usually pass
    the graph from the session in which you launched it:

    ```python
    ...create a graph...
    # Launch the graph in a session.
    sess = tf.Session()
    # Create a summary writer, add the 'graph' to the event file.
    writer = tf.summary.FileWriter(<some-directory>, sess.graph)
    ```

    The other arguments to the constructor control the asynchronous writes to
    the event file:

    *  `flush_secs`: How often, in seconds, to flush the added summaries
       and events to disk.
    *  `max_queue`: Maximum number of summaries or events pending to be
       written to disk before one of the 'add' calls block.

    Args:
      logdir: A string. Directory where event file will be written.
      graph: A `Graph` object, such as `sess.graph`.
      max_queue: Integer. Size of the queue for pending events and summaries.
      flush_secs: Number. How often, in seconds, to flush the
        pending events and summaries to disk.
      graph_def: DEPRECATED: Use the `graph` argument instead.
    """
    event_writer = EventFileWriter(logdir, max_queue, flush_secs)
    super(FileWriter, self).__init__(event_writer, graph, graph_def) 

def __init__(self,
               logdir,
               graph=None,
               max_queue=10,
               flush_secs=120,
               graph_def=None):
    """Creates a `FileWriter` and an event file.

    On construction the summary writer creates a new event file in `logdir`.
    This event file will contain `Event` protocol buffers constructed when you
    call one of the following functions: `add_summary()`, `add_session_log()`,
    `add_event()`, or `add_graph()`.

    If you pass a `Graph` to the constructor it is added to
    the event file. (This is equivalent to calling `add_graph()` later).

    TensorBoard will pick the graph from the file and display it graphically so
    you can interactively explore the graph you built. You will usually pass
    the graph from the session in which you launched it:

    ```python
    ...create a graph...
    # Launch the graph in a session.
    sess = tf.Session()
    # Create a summary writer, add the 'graph' to the event file.
    writer = tf.train.SummaryWriter(<some-directory>, sess.graph)
    ```

    The other arguments to the constructor control the asynchronous writes to
    the event file:

    *  `flush_secs`: How often, in seconds, to flush the added summaries
       and events to disk.
    *  `max_queue`: Maximum number of summaries or events pending to be
       written to disk before one of the 'add' calls block.

    Args:
      logdir: A string. Directory where event file will be written.
      graph: A `Graph` object, such as `sess.graph`.
      max_queue: Integer. Size of the queue for pending events and summaries.
      flush_secs: Number. How often, in seconds, to flush the
        pending events and summaries to disk.
      graph_def: DEPRECATED: Use the `graph` argument instead.
    """
    event_writer = EventFileWriter(logdir, max_queue, flush_secs)
    super(FileWriter, self).__init__(event_writer, graph, graph_def) 

def __init__(self,
               logdir,
               graph=None,
               max_queue=10,
               flush_secs=120,
               graph_def=None,
               filename_suffix=None):
    """Creates a `FileWriter` and an event file.

    On construction the summary writer creates a new event file in `logdir`.
    This event file will contain `Event` protocol buffers constructed when you
    call one of the following functions: `add_summary()`, `add_session_log()`,
    `add_event()`, or `add_graph()`.

    If you pass a `Graph` to the constructor it is added to
    the event file. (This is equivalent to calling `add_graph()` later).

    TensorBoard will pick the graph from the file and display it graphically so
    you can interactively explore the graph you built. You will usually pass
    the graph from the session in which you launched it:

    ```python
    ...create a graph...
    # Launch the graph in a session.
    sess = tf.Session()
    # Create a summary writer, add the 'graph' to the event file.
    writer = tf.summary.FileWriter(<some-directory>, sess.graph)
    ```

    The other arguments to the constructor control the asynchronous writes to
    the event file:

    *  `flush_secs`: How often, in seconds, to flush the added summaries
       and events to disk.
    *  `max_queue`: Maximum number of summaries or events pending to be
       written to disk before one of the 'add' calls block.

    Args:
      logdir: A string. Directory where event file will be written.
      graph: A `Graph` object, such as `sess.graph`.
      max_queue: Integer. Size of the queue for pending events and summaries.
      flush_secs: Number. How often, in seconds, to flush the
        pending events and summaries to disk.
      graph_def: DEPRECATED: Use the `graph` argument instead.
      filename_suffix: A string. Every event file's name is suffixed with
        `suffix`.
    """
    event_writer = EventFileWriter(logdir, max_queue, flush_secs,
                                   filename_suffix)
    super(FileWriter, self).__init__(event_writer, graph, graph_def) 

def __init__(self,
               logdir,
               graph=None,
               max_queue=10,
               flush_secs=120,
               graph_def=None):
    """Creates a `FileWriter` and an event file.

    On construction the summary writer creates a new event file in `logdir`.
    This event file will contain `Event` protocol buffers constructed when you
    call one of the following functions: `add_summary()`, `add_session_log()`,
    `add_event()`, or `add_graph()`.

    If you pass a `Graph` to the constructor it is added to
    the event file. (This is equivalent to calling `add_graph()` later).

    TensorBoard will pick the graph from the file and display it graphically so
    you can interactively explore the graph you built. You will usually pass
    the graph from the session in which you launched it:

    ```python
    ...create a graph...
    # Launch the graph in a session.
    sess = tf.Session()
    # Create a summary writer, add the 'graph' to the event file.
    writer = tf.summary.FileWriter(<some-directory>, sess.graph)
    ```

    The other arguments to the constructor control the asynchronous writes to
    the event file:

    *  `flush_secs`: How often, in seconds, to flush the added summaries
       and events to disk.
    *  `max_queue`: Maximum number of summaries or events pending to be
       written to disk before one of the 'add' calls block.

    Args:
      logdir: A string. Directory where event file will be written.
      graph: A `Graph` object, such as `sess.graph`.
      max_queue: Integer. Size of the queue for pending events and summaries.
      flush_secs: Number. How often, in seconds, to flush the
        pending events and summaries to disk.
      graph_def: DEPRECATED: Use the `graph` argument instead.
    """
    event_writer = EventFileWriter(logdir, max_queue, flush_secs)
    super(FileWriter, self).__init__(event_writer, graph, graph_def)