本文整理匯總了Python中nets.mobilenet.mobilenet.training_scope方法的典型用法代碼示例。如果您正苦於以下問題：Python mobilenet.training_scope方法的具體用法？Python mobilenet.training_scope怎麽用？Python mobilenet.training_scope使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類nets.mobilenet.mobilenet的用法示例。
在下文中一共展示了mobilenet.training_scope方法的5個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: training_scope
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 別名]
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
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 別名]
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
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 別名]
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
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 別名]
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
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import training_scope [as 別名]
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)])