本文整理匯總了Python中nets.inception.inception_resnet_v2_arg_scope方法的典型用法代碼示例。如果您正苦於以下問題：Python inception.inception_resnet_v2_arg_scope方法的具體用法？Python inception.inception_resnet_v2_arg_scope怎麽用？Python inception.inception_resnet_v2_arg_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.inception的用法示例。
在下文中一共展示了inception.inception_resnet_v2_arg_scope方法的4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: testNoBatchNormScaleByDefault
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_resnet_v2_arg_scope [as 別名]
def testNoBatchNormScaleByDefault(self):
height, width = 299, 299
num_classes = 1000
inputs = tf.placeholder(tf.float32, (1, height, width, 3))
with tf.contrib.slim.arg_scope(inception.inception_resnet_v2_arg_scope()):
inception.inception_resnet_v2(inputs, num_classes, is_training=False)
self.assertEqual(tf.global_variables('.*/BatchNorm/gamma:0$'), []) 示例2: testBatchNormScale
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_resnet_v2_arg_scope [as 別名]
def testBatchNormScale(self):
height, width = 299, 299
num_classes = 1000
inputs = tf.placeholder(tf.float32, (1, height, width, 3))
with tf.contrib.slim.arg_scope(
inception.inception_resnet_v2_arg_scope(batch_norm_scale=True)):
inception.inception_resnet_v2(inputs, num_classes, is_training=False)
gamma_names = set(
v.op.name for v in tf.global_variables('.*/BatchNorm/gamma:0$'))
self.assertGreater(len(gamma_names), 0)
for v in tf.global_variables('.*/BatchNorm/moving_mean:0$'):
self.assertIn(v.op.name[:-len('moving_mean')] + 'gamma', gamma_names) 示例3: testNoBatchNormScaleByDefault
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_resnet_v2_arg_scope [as 別名]
def testNoBatchNormScaleByDefault(self):
height, width = 299, 299
num_classes = 1000
inputs = tf.placeholder(tf.float32, (1, height, width, 3))
with slim.arg_scope(inception.inception_resnet_v2_arg_scope()):
inception.inception_resnet_v2(inputs, num_classes, is_training=False)
self.assertEqual(tf.global_variables('.*/BatchNorm/gamma:0$'), []) 示例4: testBatchNormScale
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_resnet_v2_arg_scope [as 別名]
def testBatchNormScale(self):
height, width = 299, 299
num_classes = 1000
inputs = tf.placeholder(tf.float32, (1, height, width, 3))
with slim.arg_scope(
inception.inception_resnet_v2_arg_scope(batch_norm_scale=True)):
inception.inception_resnet_v2(inputs, num_classes, is_training=False)
gamma_names = set(
v.op.name
for v in tf.global_variables('.*/BatchNorm/gamma:0$'))
self.assertGreater(len(gamma_names), 0)
for v in tf.global_variables('.*/BatchNorm/moving_mean:0$'):
self.assertIn(v.op.name[:-len('moving_mean')] + 'gamma', gamma_names)