本文整理汇总了Python中nets.mobilenet.mobilenet.training_scope方法的典型用法代码示例。如果您正苦于以下问题：Python mobilenet.training_scope方法的具体用法？Python mobilenet.training_scope怎么用？Python mobilenet.training_scope使用的例子？那么, 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nets.mobilenet.mobilenet的用法示例。
在下文中一共展示了mobilenet.training_scope方法的5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: training_scope
# 需要导入模块: from nets.mobilenet import mobilenet [as 别名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 别名]
def training_scope(**kwargs):
"""Defines MobilenetV2 training scope.
Usage:
with tf.contrib.slim.arg_scope(mobilenet_v2.training_scope()):
logits, endpoints = mobilenet_v2.mobilenet(input_tensor)
with slim.
Args:
**kwargs: Passed to mobilenet.training_scope. The following parameters
are supported:
weight_decay- The weight decay to use for regularizing the model.
stddev- Standard deviation for initialization, if negative uses xavier.
dropout_keep_prob- dropout keep probability
bn_decay- decay for the batch norm moving averages.
Returns:
An `arg_scope` to use for the mobilenet v2 model.
"""
return lib.training_scope(**kwargs) 示例2: training_scope
# 需要导入模块: from nets.mobilenet import mobilenet [as 别名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 别名]
def training_scope(**kwargs):
"""Defines MobilenetV2 training scope.
Usage:
with tf.contrib.slim.arg_scope(mobilenet_v2.training_scope()):
logits, endpoints = mobilenet_v2.mobilenet(input_tensor)
with slim.
Args:
**kwargs: Passed to mobilenet.training_scope. The following parameters
are supported:
weight_decay- The weight decay to use for regularizing the model.
stddev- Standard deviation for initialization, if negative uses xavier.
dropout_keep_prob- dropout keep probability
bn_decay- decay for the batch norm moving averages.
Returns:
An `arg_scope` to use for the mobilenet v2 model.
"""
return lib.training_scope(**kwargs) 示例3: training_scope
# 需要导入模块: from nets.mobilenet import mobilenet [as 别名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 别名]
def training_scope(**kwargs):
"""Defines MobilenetV2 training scope.
Usage:
with slim.arg_scope(mobilenet_v2.training_scope()):
logits, endpoints = mobilenet_v2.mobilenet(input_tensor)
Args:
**kwargs: Passed to mobilenet.training_scope. The following parameters
are supported:
weight_decay- The weight decay to use for regularizing the model.
stddev- Standard deviation for initialization, if negative uses xavier.
dropout_keep_prob- dropout keep probability
bn_decay- decay for the batch norm moving averages.
Returns:
An `arg_scope` to use for the mobilenet v2 model.
"""
return lib.training_scope(**kwargs) 示例4: testBatchNormScopeDoesNotHaveIsTrainingWhenItsSetToNone
# 需要导入模块: from nets.mobilenet import mobilenet [as 别名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 别名]
def testBatchNormScopeDoesNotHaveIsTrainingWhenItsSetToNone(self):
sc = mobilenet.training_scope(is_training=None)
self.assertNotIn('is_training', sc[slim.arg_scope_func_key(
slim.batch_norm)]) 示例5: testBatchNormScopeDoesHasIsTrainingWhenItsNotNone
# 需要导入模块: from nets.mobilenet import mobilenet [as 别名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 别名]
def testBatchNormScopeDoesHasIsTrainingWhenItsNotNone(self):
sc = mobilenet.training_scope(is_training=False)
self.assertIn('is_training', sc[slim.arg_scope_func_key(slim.batch_norm)])
sc = mobilenet.training_scope(is_training=True)
self.assertIn('is_training', sc[slim.arg_scope_func_key(slim.batch_norm)])
sc = mobilenet.training_scope()
self.assertIn('is_training', sc[slim.arg_scope_func_key(slim.batch_norm)])