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Python tensorflow.Event方法代码示例

本文整理汇总了Python中tensorflow.Event方法的典型用法代码示例。如果您正苦于以下问题:Python tensorflow.Event方法的具体用法?Python tensorflow.Event怎么用?Python tensorflow.Event使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在tensorflow的用法示例。


在下文中一共展示了tensorflow.Event方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: _setup_graph

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def _setup_graph(self):
        # special heuristics for Horovod
        from ..train import HorovodTrainer
        if isinstance(self.trainer, HorovodTrainer):
            if self.trainer.mpi_enabled():
                logger.warn("GPUUtilizationTracker is disabled under MPI.")
                self._enabled = False
                return
            else:
                self._devices = [self.trainer.hvd.local_rank()]

        if self._devices is None:
            self._devices = self._guess_devices()
        assert len(self._devices), "[GPUUtilizationTracker] No GPU device given!"

        self._evt = mp.Event()
        self._stop_evt = mp.Event()
        self._queue = mp.Queue()
        self._proc = mp.Process(target=self.worker, args=(
            self._evt, self._queue, self._stop_evt, self._devices))
        ensure_proc_terminate(self._proc)
        start_proc_mask_signal(self._proc) 
开发者ID:junsukchoe,项目名称:ADL,代码行数:24,代码来源:prof.py

示例2: on_graph_def

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def on_graph_def(self, graph_def, device_name, wall_time):
        """Implementation of the GraphDef-carrying Event proto callback.

        Args:
          graph_def: A GraphDef proto. N.B.: The GraphDef is from
            the core runtime of a debugged Session::Run() call, after graph
            partition. Therefore it may differ from the GraphDef available to
            the general TensorBoard. For example, the GraphDef in general
            TensorBoard may get partitioned for multiple devices (CPUs and GPUs),
            each of which will generate a GraphDef event proto sent to this
            method.
          device_name: Name of the device on which the graph was created.
          wall_time: An epoch timestamp (in microseconds) for the graph.
        """
        # For now, we do nothing with the graph def. However, we must define this
        # method to satisfy the handler's interface. Furthermore, we may use the
        # graph in the future (for instance to provide a graph if there is no graph
        # provided otherwise).
        del wall_time
        self._graph_defs[device_name] = graph_def

        if not self._graph_defs_arrive_first:
            self._add_graph_def(device_name, graph_def)
            self._incoming_channel.get() 
开发者ID:tensorflow,项目名称:tensorboard,代码行数:26,代码来源:interactive_debugger_server_lib.py

示例3: tb_add_histogram

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def tb_add_histogram(experiment, name, wall_time, step, histo):
  # Tensorflow does not support key being unicode
  histo_string = {}
  for k,v in histo.items():
    histo_string[str(k)] = v
  histo = histo_string

  writer = tb_get_xp_writer(experiment)
  summary = tf.Summary(value=[
      tf.Summary.Value(tag=name, histo=histo),
  ])
  event = tf.Event(wall_time=wall_time, step=step, summary=summary)
  writer.add_event(event)
  writer.flush()
  tb_modified_xp(experiment, modified_type="histograms", wall_time=wall_time)

# Perform requests to tensorboard http api 
开发者ID:torrvision,项目名称:crayon,代码行数:19,代码来源:server.py

示例4: Load

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def Load(self):
    """Loads all new values from disk.

    Calling Load multiple times in a row will not 'drop' events as long as the
    return value is not iterated over.

    Yields:
      All values that were written to disk that have not been yielded yet.
    """
    tf.logging.debug('Loading events from %s', self._file_path)
    while True:
      try:
        with tf.errors.raise_exception_on_not_ok_status() as status:
          self._reader.GetNext(status)
      except (tf.errors.DataLossError, tf.errors.OutOfRangeError):
        # We ignore partial read exceptions, because a record may be truncated.
        # PyRecordReader holds the offset prior to the failed read, so retrying
        # will succeed.
        break
      event = tf.Event()
      event.ParseFromString(self._reader.record())
      yield event
    tf.logging.debug('No more events in %s', self._file_path) 
开发者ID:PacktPublishing,项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda,代码行数:25,代码来源:event_file_loader.py

示例5: on_graph_def

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def on_graph_def(self, graph_def, device_name, wall_time):
    """Implementation of the GraphDef-carrying Event proto callback.

    Args:
      graph_def: A GraphDef proto. N.B.: The GraphDef is from
        the core runtime of a debugged Session::Run() call, after graph
        partition. Therefore it may differ from the GraphDef available to
        the general TensorBoard. For example, the GraphDef in general
        TensorBoard may get partitioned for multiple devices (CPUs and GPUs),
        each of which will generate a GraphDef event proto sent to this
        method.
      device_name: Name of the device on which the graph was created.
      wall_time: An epoch timestamp (in microseconds) for the graph.
    """
    # For now, we do nothing with the graph def. However, we must define this
    # method to satisfy the handler's interface. Furthermore, we may use the
    # graph in the future (for instance to provide a graph if there is no graph
    # provided otherwise).
    del device_name
    del wall_time
    del graph_def 
开发者ID:PacktPublishing,项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda,代码行数:23,代码来源:debugger_server_lib.py

示例6: WriteScalarSeries

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def WriteScalarSeries(writer, tag, f, n=5):
  """Write a series of scalar events to writer, using f to create values."""
  step = 0
  wall_time = _start_time
  for i in xrange(n):
    v = f(i)
    value = tf.Summary.Value(tag=tag, simple_value=v)
    summary = tf.Summary(value=[value])
    event = tf.Event(wall_time=wall_time, step=step, summary=summary)
    writer.add_event(event)
    step += 1
    wall_time += 10 
开发者ID:tobegit3hub,项目名称:deep_image_model,代码行数:14,代码来源:generate_testdata.py

示例7: WriteHistogramSeries

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def WriteHistogramSeries(writer, tag, mu_sigma_tuples, n=20):
  """Write a sequence of normally distributed histograms to writer."""
  step = 0
  wall_time = _start_time
  for [mean, stddev] in mu_sigma_tuples:
    data = [random.normalvariate(mean, stddev) for _ in xrange(n)]
    histo = _MakeHistogram(data)
    summary = tf.Summary(value=[tf.Summary.Value(tag=tag, histo=histo)])
    event = tf.Event(wall_time=wall_time, step=step, summary=summary)
    writer.add_event(event)
    step += 10
    wall_time += 100 
开发者ID:tobegit3hub,项目名称:deep_image_model,代码行数:14,代码来源:generate_testdata.py

示例8: _before_train

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def _before_train(self):
        assert gpu_available_in_session(), "[GPUUtilizationTracker] needs GPU!"
        self._evt = mp.Event()
        self._stop_evt = mp.Event()
        self._queue = mp.Queue()
        self._proc = mp.Process(target=self.worker, args=(
            self._evt, self._queue, self._stop_evt))
        ensure_proc_terminate(self._proc)
        start_proc_mask_signal(self._proc) 
开发者ID:microsoft,项目名称:petridishnn,代码行数:11,代码来源:prof.py

示例9: _write_event

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def _write_event(self, metadata):
        evt = tf.Event()
        evt.tagged_run_metadata.tag = 'trace-{}'.format(self.global_step)
        evt.tagged_run_metadata.run_metadata = metadata.SerializeToString()
        self.trainer.monitors.put_event(evt) 
开发者ID:microsoft,项目名称:petridishnn,代码行数:7,代码来源:prof.py

示例10: WriteScalarSeries

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def WriteScalarSeries(writer, tag, f, n=5):
    """Write a series of scalar events to writer, using f to create values."""
    step = 0
    wall_time = _start_time
    for i in xrange(n):
        v = f(i)
        value = tf.Summary.Value(tag=tag, simple_value=v)
        summary = tf.Summary(value=[value])
        event = tf.Event(wall_time=wall_time, step=step, summary=summary)
        writer.add_event(event)
        step += 1
        wall_time += 10 
开发者ID:tensorflow,项目名称:tensorboard,代码行数:14,代码来源:generate_testdata.py

示例11: WriteHistogramSeries

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def WriteHistogramSeries(writer, tag, mu_sigma_tuples, n=20):
    """Write a sequence of normally distributed histograms to writer."""
    step = 0
    wall_time = _start_time
    for [mean, stddev] in mu_sigma_tuples:
        data = [random.normalvariate(mean, stddev) for _ in xrange(n)]
        histo = _MakeHistogram(data)
        summary = tf.Summary(value=[tf.Summary.Value(tag=tag, histo=histo)])
        event = tf.Event(wall_time=wall_time, step=step, summary=summary)
        writer.add_event(event)
        step += 10
        wall_time += 100 
开发者ID:tensorflow,项目名称:tensorboard,代码行数:14,代码来源:generate_testdata.py

示例12: _extract_device_name_from_event

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def _extract_device_name_from_event(event):
    """Extract device name from a tf.Event proto carrying tensor value."""
    plugin_data_content = json.loads(
        tf.compat.as_str(event.summary.value[0].metadata.plugin_data.content)
    )
    return plugin_data_content["device"] 
开发者ID:tensorflow,项目名称:tensorboard,代码行数:8,代码来源:interactive_debugger_server_lib.py

示例13: on_core_metadata_event

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def on_core_metadata_event(self, event):
        """Implementation of the core metadata-carrying Event proto callback.

        Args:
          event: An Event proto that contains core metadata about the debugged
            Session::Run() in its log_message.message field, as a JSON string.
            See the doc string of debug_data.DebugDumpDir.core_metadata for details.
        """
        core_metadata = json.loads(event.log_message.message)
        input_names = ",".join(core_metadata["input_names"])
        output_names = ",".join(core_metadata["output_names"])
        target_nodes = ",".join(core_metadata["target_nodes"])

        self._run_key = RunKey(input_names, output_names, target_nodes)
        if not self._graph_defs:
            self._graph_defs_arrive_first = False
        else:
            for device_name in self._graph_defs:
                self._add_graph_def(device_name, self._graph_defs[device_name])

        self._outgoing_channel.put(
            _comm_metadata(self._run_key, event.wall_time)
        )

        # Wait for acknowledgement from client. Blocks until an item is got.
        logger.info("on_core_metadata_event() waiting for client ack (meta)...")
        self._incoming_channel.get()
        logger.info("on_core_metadata_event() client ack received (meta).")

        # TODO(cais): If eager mode, this should return something to yield. 
开发者ID:tensorflow,项目名称:tensorboard,代码行数:32,代码来源:interactive_debugger_server_lib.py

示例14: _CreateEventWithDebugNumericSummary

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def _CreateEventWithDebugNumericSummary(
        self, device_name, op_name, output_slot, wall_time, step, list_of_values
    ):
        """Creates event with a health pill summary.

        Note the debugger plugin only works with TensorFlow and, thus, uses TF
        protos and TF EventsWriter.

        Args:
          device_name: The name of the op's device.
          op_name: The name of the op to which a DebugNumericSummary was attached.
          output_slot: The numeric output slot for the tensor.
          wall_time: The numeric wall time of the event.
          step: The step of the event.
          list_of_values: A python list of values within the tensor.

        Returns:
          A `tf.Event` with a health pill summary.
        """
        event = tf.compat.v1.Event(step=step, wall_time=wall_time)
        tensor = tf.compat.v1.make_tensor_proto(
            list_of_values, dtype=tf.float64, shape=[len(list_of_values)]
        )
        value = event.summary.value.add(
            tag=op_name,
            node_name="%s:%d:DebugNumericSummary" % (op_name, output_slot),
            tensor=tensor,
        )
        content_proto = debugger_event_metadata_pb2.DebuggerEventMetadata(
            device=device_name, output_slot=output_slot
        )
        value.metadata.plugin_data.plugin_name = constants.DEBUGGER_PLUGIN_NAME
        value.metadata.plugin_data.content = tf.compat.as_bytes(
            json_format.MessageToJson(
                content_proto, including_default_value_fields=True
            )
        )
        return event 
开发者ID:tensorflow,项目名称:tensorboard,代码行数:40,代码来源:debugger_plugin_testlib.py

示例15: tb_add_scalar

# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import Event [as 别名]
def tb_add_scalar(experiment, name, wall_time, step, value):
  writer = tb_get_xp_writer(experiment)
  summary = tf.Summary(value=[
      tf.Summary.Value(tag=name, simple_value=value),
  ])
  event = tf.Event(wall_time=wall_time, step=step, summary=summary)
  writer.add_event(event)
  writer.flush()
  tb_modified_xp(experiment, modified_type="scalars", wall_time=wall_time) 
开发者ID:torrvision,项目名称:crayon,代码行数:11,代码来源:server.py


注:本文中的tensorflow.Event方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。