本文整理汇总了Python中tensorflow.python.platform.tf_logging.ERROR属性的典型用法代码示例。如果您正苦于以下问题：Python tf_logging.ERROR属性的具体用法？Python tf_logging.ERROR怎么用？Python tf_logging.ERROR使用的例子？那么, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类tensorflow.python.platform.tf_logging的用法示例。
在下文中一共展示了tf_logging.ERROR属性的3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: log
# 需要导入模块: from tensorflow.python.platform import tf_logging [as 别名]
# 或者: from tensorflow.python.platform.tf_logging import ERROR [as 别名]
def log(level, message, *args):
"""Conditionally logs `message % args` at the level `level`.
Note that tensorboard_logging verbosity and logging verbosity are separate;
the message will always be passed through to the logging module regardless of
whether it passes the tensorboard_logging verbosity check.
Args:
level: The verbosity level to use. Must be one of
tensorboard_logging.{DEBUG, INFO, WARN, ERROR, FATAL}.
message: The message template to use.
*args: Arguments to interpolate to the message template, if any.
Raises:
ValueError: If `level` is not a valid logging level.
RuntimeError: If the `SummaryWriter` to use has not been set.
"""
if _summary_writer is _sentinel_summary_writer:
raise RuntimeError('Must call set_summary_writer before doing any '
'logging from tensorboard_logging')
_check_verbosity(level)
proto_level = _LEVEL_PROTO_MAP[level]
if proto_level >= _LEVEL_PROTO_MAP[_verbosity]:
log_message = event_pb2.LogMessage(level=proto_level,
message=message % args)
event = event_pb2.Event(wall_time=time.time(), log_message=log_message)
if _summary_writer:
_summary_writer.add_event(event)
logging.log(_PLATFORM_LOGGING_LEVEL_MAP[level], message, *args) 示例2: error
# 需要导入模块: from tensorflow.python.platform import tf_logging [as 别名]
# 或者: from tensorflow.python.platform.tf_logging import ERROR [as 别名]
def error(message, *args):
log(ERROR, message, *args) 示例3: _ProcessHealthPillSummary
# 需要导入模块: from tensorflow.python.platform import tf_logging [as 别名]
# 或者: from tensorflow.python.platform.tf_logging import ERROR [as 别名]
def _ProcessHealthPillSummary(self, value, event):
"""Process summaries containing health pills.
These summaries are distinguished by the fact that they have a Tensor field
and have a special tag value.
This method emits ERROR-level messages to the logs if it encounters Tensor
summaries that it cannot process.
Args:
value: A summary_pb2.Summary.Value with a Tensor field.
event: The event_pb2.Event containing that value.
"""
elements = tensor_util.MakeNdarray(value.tensor)
# The node_name property of the value object is actually a watch key: a
# combination of node name, output slot, and a suffix. We capture the
# actual node name and the output slot with a regular expression.
match = re.match(r'^(.*):(\d+):DebugNumericSummary$', value.node_name)
if not match:
logging.log_first_n(
logging.ERROR,
'Unsupported watch key %s for health pills; skipping this sequence.',
1,
value.node_name)
return
node_name = match.group(1)
output_slot = int(match.group(2))
self._ProcessHealthPill(
event.wall_time, event.step, node_name, output_slot, elements)