Python summary_ops_v2.always_record_summaries函数代码示例

  def _write_custom_summaries(self, step, logs=None):
    """Writes metrics out as custom scalar summaries.

    Arguments:
        step: the global step to use for TensorBoard.
        logs: dict. Keys are scalar summary names, values are
            NumPy scalars.

    """
    logs = logs or {}
    if context.executing_eagerly():
      # use v2 summary ops
      with self.writer.as_default(), summary_ops_v2.always_record_summaries():
        for name, value in logs.items():
          if isinstance(value, np.ndarray):
            value = value.item()
          summary_ops_v2.scalar(name, value, step=step)
    else:
      # use FileWriter from v1 summary
      for name, value in logs.items():
        if isinstance(value, np.ndarray):
          value = value.item()
        summary = tf_summary.Summary()
        summary_value = summary.value.add()
        summary_value.simple_value = value
        summary_value.tag = name
        self.writer.add_summary(summary, step)
    self.writer.flush()

 def testWriterInitAndClose(self):
   logdir = self.get_temp_dir()
   get_total = lambda: len(summary_test_util.events_from_logdir(logdir))
   with summary_ops.always_record_summaries():
     writer = summary_ops.create_file_writer(
         logdir, max_queue=100, flush_millis=1000000)
     self.assertEqual(1, get_total())  # file_version Event
     # Calling init() again while writer is open has no effect
     writer.init()
     self.assertEqual(1, get_total())
     try:
       # Not using .as_default() to avoid implicit flush when exiting
       writer.set_as_default()
       summary_ops.scalar('one', 1.0, step=1)
       self.assertEqual(1, get_total())
       # Calling .close() should do an implicit flush
       writer.close()
       self.assertEqual(2, get_total())
       # Calling init() on a closed writer should start a new file
       time.sleep(1.1)  # Ensure filename has a different timestamp
       writer.init()
       files = sorted(gfile.Glob(os.path.join(logdir, '*tfevents*')))
       self.assertEqual(2, len(files))
       get_total = lambda: len(summary_test_util.events_from_file(files[1]))
       self.assertEqual(1, get_total())  # file_version Event
       summary_ops.scalar('two', 2.0, step=2)
       writer.close()
       self.assertEqual(2, get_total())
     finally:
       # Clean up by resetting default writer
       summary_ops.create_file_writer(None).set_as_default()

  def _test_summary_for_replica_zero_only(self, d):
    logdir = tempfile.mkdtemp()

    def run_fn():
      """Function executed for each replica."""
      with summary_writer.as_default():
        replica_id = ds_context.get_replica_context().replica_id_in_sync_group
        return summary_ops.write("a", replica_id)

    with self.cached_session() as sess, d.scope(), \
        summary_ops.always_record_summaries():
      # We need global_step because summary writing op *always* has global_step
      # as input, even when we always record summary or never record summary.
      global_step = training_util.get_or_create_global_step()
      if not context.executing_eagerly():
        # When executing eagerly, variables are initialized immediately after
        # creation, and its initializer will be None.
        global_step.initializer.run()
      summary_ops.set_step(0)
      summary_writer = summary_ops.create_file_writer(logdir)
      output = d.extended.call_for_each_replica(run_fn)
      unwrapped = d.unwrap(output)
      if not context.executing_eagerly():
        sess.run(summary_writer.init())
        sess.run(unwrapped)
        sess.run(summary_writer.close())

      events = _events_from_logdir(self, logdir)
      # There will be 2 entries: 1 summary file header entry, and 1 entry
      # written by replica 0.
      self.assertLen(events, 2)
      self.assertEqual(events[1].summary.value[0].tag, "a")
      self.assertEqual(events[1].summary.value[0].simple_value, 0.0)

 def testWriterInitAndClose(self):
   logdir = self.get_temp_dir()
   with summary_ops.always_record_summaries():
     writer = summary_ops.create_file_writer(
         logdir, max_queue=100, flush_millis=1000000)
     with writer.as_default():
       summary_ops.scalar('one', 1.0, step=1)
   with self.cached_session() as sess:
     sess.run(summary_ops.summary_writer_initializer_op())
     get_total = lambda: len(summary_test_util.events_from_logdir(logdir))
     self.assertEqual(1, get_total())  # file_version Event
     # Running init() again while writer is open has no effect
     sess.run(writer.init())
     self.assertEqual(1, get_total())
     sess.run(summary_ops.all_summary_ops())
     self.assertEqual(1, get_total())
     # Running close() should do an implicit flush
     sess.run(writer.close())
     self.assertEqual(2, get_total())
     # Running init() on a closed writer should start a new file
     time.sleep(1.1)  # Ensure filename has a different timestamp
     sess.run(writer.init())
     sess.run(summary_ops.all_summary_ops())
     sess.run(writer.close())
     files = sorted(gfile.Glob(os.path.join(logdir, '*tfevents*')))
     self.assertEqual(2, len(files))
     self.assertEqual(2, len(summary_test_util.events_from_file(files[1])))

  def testIntegerSummaries(self):
    step = training_util.create_global_step()
    writer = self.create_db_writer()

    def adder(x, y):
      state_ops.assign_add(step, 1)
      summary_ops.generic('x', x)
      summary_ops.generic('y', y)
      sum_ = x + y
      summary_ops.generic('sum', sum_)
      return sum_

    with summary_ops.always_record_summaries():
      with writer.as_default():
        self.assertEqual(5, adder(int64(2), int64(3)).numpy())

    six.assertCountEqual(
        self, [1, 1, 1],
        get_all(self.db, 'SELECT step FROM Tensors WHERE dtype IS NOT NULL'))
    six.assertCountEqual(self, ['x', 'y', 'sum'],
                         get_all(self.db, 'SELECT tag_name FROM Tags'))
    x_id = get_one(self.db, 'SELECT tag_id FROM Tags WHERE tag_name = "x"')
    y_id = get_one(self.db, 'SELECT tag_id FROM Tags WHERE tag_name = "y"')
    sum_id = get_one(self.db, 'SELECT tag_id FROM Tags WHERE tag_name = "sum"')

    with summary_ops.always_record_summaries():
      with writer.as_default():
        self.assertEqual(9, adder(int64(4), int64(5)).numpy())

    six.assertCountEqual(
        self, [1, 1, 1, 2, 2, 2],
        get_all(self.db, 'SELECT step FROM Tensors WHERE dtype IS NOT NULL'))
    six.assertCountEqual(self, [x_id, y_id, sum_id],
                         get_all(self.db, 'SELECT tag_id FROM Tags'))
    self.assertEqual(2, get_tensor(self.db, x_id, 1))
    self.assertEqual(3, get_tensor(self.db, y_id, 1))
    self.assertEqual(5, get_tensor(self.db, sum_id, 1))
    self.assertEqual(4, get_tensor(self.db, x_id, 2))
    self.assertEqual(5, get_tensor(self.db, y_id, 2))
    self.assertEqual(9, get_tensor(self.db, sum_id, 2))
    six.assertCountEqual(
        self, ['experiment'],
        get_all(self.db, 'SELECT experiment_name FROM Experiments'))
    six.assertCountEqual(self, ['run'],
                         get_all(self.db, 'SELECT run_name FROM Runs'))
    six.assertCountEqual(self, ['user'],
                         get_all(self.db, 'SELECT user_name FROM Users'))

 def testGraphSummary(self):
   training_util.get_or_create_global_step()
   name = 'hi'
   graph = graph_pb2.GraphDef(node=(node_def_pb2.NodeDef(name=name),))
   with summary_ops.always_record_summaries():
     with self.create_db_writer().as_default():
       summary_ops.graph(graph)
   six.assertCountEqual(self, [name],
                        get_all(self.db, 'SELECT node_name FROM Nodes'))

  def __init__(self, session, logdir, max_queue=10, flush_secs=120,
               filename_suffix=''):
    """Creates an `EventFileWriterV2` and an event file to write to.

    On construction, this calls `tf.contrib.summary.create_file_writer` within
    the graph from `session.graph` to look up a shared summary writer resource
    for `logdir` if one exists, and create one if not. Creating the summary
    writer resource in turn creates a new event file in `logdir` to be filled
    with `Event` protocol buffers passed to `add_event`. Graph ops to control
    this writer resource are added to `session.graph` during this init call;
    stateful methods on this class will call `session.run()` on these ops.

    Note that because the underlying resource is shared, it is possible that
    other parts of the code using the same session may interact independently
    with the resource, e.g. by flushing or even closing it. It is the caller's
    responsibility to avoid any undesirable sharing in this regard.

    The remaining arguments to the constructor (`flush_secs`, `max_queue`, and
    `filename_suffix`) control the construction of the shared writer resource
    if one is created. If an existing resource is reused, these arguments have
    no effect.  See `tf.contrib.summary.create_file_writer` for details.

    Args:
      session: A `tf.compat.v1.Session`. Session that will hold shared writer
        resource. The writer ops will be added to session.graph during this
        init call.
      logdir: A string. Directory where event file will be written.
      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.
      filename_suffix: A string. Every event file's name is suffixed with
        `filename_suffix`.
    """
    self._session = session
    self._logdir = logdir
    self._closed = False
    if not gfile.IsDirectory(self._logdir):
      gfile.MakeDirs(self._logdir)

    with self._session.graph.as_default():
      with ops.name_scope('filewriter'):
        file_writer = summary_ops_v2.create_file_writer(
            logdir=self._logdir,
            max_queue=max_queue,
            flush_millis=flush_secs * 1000,
            filename_suffix=filename_suffix)
        with summary_ops_v2.always_record_summaries(), file_writer.as_default():
          self._event_placeholder = array_ops.placeholder_with_default(
              constant_op.constant('unused', dtypes.string),
              shape=[])
          self._add_event_op = summary_ops_v2.import_event(
              self._event_placeholder)
        self._init_op = file_writer.init()
        self._flush_op = file_writer.flush()
        self._close_op = file_writer.close()
      self._session.run(self._init_op)

 def testEagerMemory(self):
   training_util.get_or_create_global_step()
   logdir = self.get_temp_dir()
   with summary_ops.create_file_writer(
       logdir, max_queue=0,
       name='t0').as_default(), summary_ops.always_record_summaries():
     summary_ops.generic('tensor', 1, '')
     summary_ops.scalar('scalar', 2.0)
     summary_ops.histogram('histogram', [1.0])
     summary_ops.image('image', [[[[1.0]]]])
     summary_ops.audio('audio', [[1.0]], 1.0, 1)

 def testSummaryName(self):
   logdir = self.get_temp_dir()
   writer = summary_ops.create_file_writer(logdir, max_queue=0)
   with writer.as_default(), summary_ops.always_record_summaries():
     summary_ops.scalar('scalar', 2.0, step=1)
   with self.cached_session() as sess:
     sess.run(summary_ops.summary_writer_initializer_op())
     sess.run(summary_ops.all_summary_ops())
   events = summary_test_util.events_from_logdir(logdir)
   self.assertEqual(2, len(events))
   self.assertEqual('scalar', events[1].summary.value[0].tag)

  def testSummaryGlobalStep(self):
    step = training_util.get_or_create_global_step()
    logdir = tempfile.mkdtemp()
    with summary_ops.create_file_writer(
        logdir, max_queue=0,
        name='t2').as_default(), summary_ops.always_record_summaries():

      summary_ops.scalar('scalar', 2.0, step=step)

      events = summary_test_util.events_from_logdir(logdir)
      self.assertEqual(len(events), 2)
      self.assertEqual(events[1].summary.value[0].tag, 'scalar')

 def testMaxQueue(self):
   logs = tempfile.mkdtemp()
   with summary_ops.create_file_writer(
       logs, max_queue=1, flush_millis=999999,
       name='lol').as_default(), summary_ops.always_record_summaries():
     get_total = lambda: len(summary_test_util.events_from_logdir(logs))
     # Note: First tf.Event is always file_version.
     self.assertEqual(1, get_total())
     summary_ops.scalar('scalar', 2.0, step=1)
     self.assertEqual(1, get_total())
     # Should flush after second summary since max_queue = 1
     summary_ops.scalar('scalar', 2.0, step=2)
     self.assertEqual(3, get_total())

  def testWriteSummaries(self):
    m = metrics.Mean()
    m([1, 10, 100])
    training_util.get_or_create_global_step()
    logdir = tempfile.mkdtemp()
    with summary_ops.create_file_writer(
        logdir, max_queue=0,
        name="t0").as_default(), summary_ops.always_record_summaries():
      m.result()  # As a side-effect will write summaries.

    events = summary_test_util.events_from_logdir(logdir)
    self.assertEqual(len(events), 2)
    self.assertEqual(events[1].summary.value[0].simple_value, 37.0)

 def testSummaryGlobalStep(self):
   training_util.get_or_create_global_step()
   logdir = self.get_temp_dir()
   writer = summary_ops.create_file_writer(logdir, max_queue=0)
   with writer.as_default(), summary_ops.always_record_summaries():
     summary_ops.scalar('scalar', 2.0)
   with self.cached_session() as sess:
     sess.run(variables.global_variables_initializer())
     sess.run(summary_ops.summary_writer_initializer_op())
     step, _ = sess.run(
         [training_util.get_global_step(), summary_ops.all_summary_ops()])
   events = summary_test_util.events_from_logdir(logdir)
   self.assertEqual(2, len(events))
   self.assertEqual(step, events[1].step)

 def testSummaryOps(self):
   training_util.get_or_create_global_step()
   logdir = tempfile.mkdtemp()
   with summary_ops.create_file_writer(
       logdir, max_queue=0,
       name='t0').as_default(), summary_ops.always_record_summaries():
     summary_ops.generic('tensor', 1, '')
     summary_ops.scalar('scalar', 2.0)
     summary_ops.histogram('histogram', [1.0])
     summary_ops.image('image', [[[[1.0]]]])
     summary_ops.audio('audio', [[1.0]], 1.0, 1)
     # The working condition of the ops is tested in the C++ test so we just
     # test here that we're calling them correctly.
     self.assertTrue(gfile.Exists(logdir))

 def testDbURIOpen(self):
   tmpdb_path = os.path.join(self.get_temp_dir(), 'tmpDbURITest.sqlite')
   tmpdb_uri = six.moves.urllib_parse.urljoin("file:", tmpdb_path)
   tmpdb_writer = summary_ops.create_db_writer(
       tmpdb_uri,
       "experimentA",
       "run1",
       "user1")
   with summary_ops.always_record_summaries():
     with tmpdb_writer.as_default():
       summary_ops.scalar('t1', 2.0)
   tmpdb = sqlite3.connect(tmpdb_path)
   num = get_one(tmpdb, 'SELECT count(*) FROM Tags WHERE tag_name = "t1"')
   self.assertEqual(num, 1)
   tmpdb.close()