本文整理汇总了Python中official.utils.logs.logger.BaseBenchmarkLogger方法的典型用法代码示例。如果您正苦于以下问题：Python logger.BaseBenchmarkLogger方法的具体用法？Python logger.BaseBenchmarkLogger怎么用？Python logger.BaseBenchmarkLogger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类official.utils.logs.logger的用法示例。
在下文中一共展示了logger.BaseBenchmarkLogger方法的9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: __init__
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def __init__(self,
batch_size,
every_n_steps=None,
every_n_secs=None,
warm_steps=0,
metric_logger=None):
"""Initializer for ExamplesPerSecondHook.
Args:
batch_size: Total batch size across all workers used to calculate
examples/second from global time.
every_n_steps: Log stats every n steps.
every_n_secs: Log stats every n seconds. Exactly one of the
`every_n_steps` or `every_n_secs` should be set.
warm_steps: The number of steps to be skipped before logging and running
average calculation. warm_steps steps refers to global steps across all
workers, not on each worker
metric_logger: instance of `BenchmarkLogger`, the benchmark logger that
hook should use to write the log. If None, BaseBenchmarkLogger will
be used.
Raises:
ValueError: if neither `every_n_steps` or `every_n_secs` is set, or
both are set.
"""
if (every_n_steps is None) == (every_n_secs is None):
raise ValueError("exactly one of every_n_steps"
" and every_n_secs should be provided.")
self._logger = metric_logger or logger.BaseBenchmarkLogger()
self._timer = tf.estimator.SecondOrStepTimer(
every_steps=every_n_steps, every_secs=every_n_secs)
self._step_train_time = 0
self._total_steps = 0
self._batch_size = batch_size
self._warm_steps = warm_steps
# List of examples per second logged every_n_steps.
self.current_examples_per_sec_list = [] 示例2: test_get_default_benchmark_logger
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def test_get_default_benchmark_logger(self):
with flagsaver.flagsaver(benchmark_logger_type="foo"):
self.assertIsInstance(logger.get_benchmark_logger(),
logger.BaseBenchmarkLogger) 示例3: test_config_base_benchmark_logger
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def test_config_base_benchmark_logger(self):
with flagsaver.flagsaver(benchmark_logger_type="BaseBenchmarkLogger"):
logger.config_benchmark_logger()
self.assertIsInstance(logger.get_benchmark_logger(),
logger.BaseBenchmarkLogger) 示例4: test_log_metric
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def test_log_metric(self):
log = logger.BaseBenchmarkLogger()
log.log_metric("accuracy", 0.999, global_step=1e4, extras={"name": "value"})
expected_log_prefix = "Benchmark metric:"
self.assertRegexpMatches(str(self.logged_message), expected_log_prefix) 示例5: test_get_default_benchmark_logger
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def test_get_default_benchmark_logger(self):
with flagsaver.flagsaver(benchmark_logger_type='foo'):
self.assertIsInstance(logger.get_benchmark_logger(),
logger.BaseBenchmarkLogger) 示例6: test_config_base_benchmark_logger
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def test_config_base_benchmark_logger(self):
with flagsaver.flagsaver(benchmark_logger_type='BaseBenchmarkLogger'):
logger.config_benchmark_logger()
self.assertIsInstance(logger.get_benchmark_logger(),
logger.BaseBenchmarkLogger) 示例7: test_get_default_benchmark_logger
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def test_get_default_benchmark_logger(self):
self.assertIsInstance(logger.get_benchmark_logger(),
logger.BaseBenchmarkLogger) 示例8: test_config_base_benchmark_logger
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def test_config_base_benchmark_logger(self):
logger.config_benchmark_logger("")
self.assertIsInstance(logger.get_benchmark_logger(),
logger.BaseBenchmarkLogger) 示例9: __init__
# 需要导入模块: from official.utils.logs import logger [as 别名]
# 或者: from official.utils.logs.logger import BaseBenchmarkLogger [as 别名]
def __init__(self,
batch_size,
every_n_steps=None,
every_n_secs=None,
warm_steps=0,
metric_logger=None):
"""Initializer for ExamplesPerSecondHook.
Args:
batch_size: Total batch size across all workers used to calculate
examples/second from global time.
every_n_steps: Log stats every n steps.
every_n_secs: Log stats every n seconds. Exactly one of the
`every_n_steps` or `every_n_secs` should be set.
warm_steps: The number of steps to be skipped before logging and running
average calculation. warm_steps steps refers to global steps across all
workers, not on each worker
metric_logger: instance of `BenchmarkLogger`, the benchmark logger that
hook should use to write the log. If None, BaseBenchmarkLogger will
be used.
Raises:
ValueError: if neither `every_n_steps` or `every_n_secs` is set, or
both are set.
"""
if (every_n_steps is None) == (every_n_secs is None):
raise ValueError("exactly one of every_n_steps"
" and every_n_secs should be provided.")
self._logger = metric_logger or logger.BaseBenchmarkLogger()
self._timer = tf.train.SecondOrStepTimer(
every_steps=every_n_steps, every_secs=every_n_secs)
self._step_train_time = 0
self._total_steps = 0
self._batch_size = batch_size
self._warm_steps = warm_steps