本文整理匯總了Python中inception.slim.losses.l1_regularizer方法的典型用法代碼示例。如果您正苦於以下問題：Python losses.l1_regularizer方法的具體用法？Python losses.l1_regularizer怎麽用？Python losses.l1_regularizer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inception.slim.losses的用法示例。
在下文中一共展示了losses.l1_regularizer方法的3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: testL1Regularizer
# 需要導入模塊: from inception.slim import losses [as 別名]
# 或者: from inception.slim.losses import l1_regularizer [as 別名]
def testL1Regularizer(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
tensor = tf.constant(1.0, shape=shape)
loss = losses.l1_regularizer()(tensor)
self.assertEquals(loss.op.name, 'L1Regularizer/value')
self.assertAlmostEqual(loss.eval(), num_elem, 5) 示例2: testL1RegularizerWithScope
# 需要導入模塊: from inception.slim import losses [as 別名]
# 或者: from inception.slim.losses import l1_regularizer [as 別名]
def testL1RegularizerWithScope(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
tensor = tf.constant(1.0, shape=shape)
loss = losses.l1_regularizer(scope='L1')(tensor)
self.assertEquals(loss.op.name, 'L1/value')
self.assertAlmostEqual(loss.eval(), num_elem, 5) 示例3: testL1RegularizerWithWeight
# 需要導入模塊: from inception.slim import losses [as 別名]
# 或者: from inception.slim.losses import l1_regularizer [as 別名]
def testL1RegularizerWithWeight(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
tensor = tf.constant(1.0, shape=shape)
weight = 0.01
loss = losses.l1_regularizer(weight)(tensor)
self.assertEquals(loss.op.name, 'L1Regularizer/value')
self.assertAlmostEqual(loss.eval(), num_elem * weight, 5)