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Python learning_rate_decay.exponential_decay函数代码示例

本文整理汇总了Python中tensorflow.python.training.learning_rate_decay.exponential_decay函数的典型用法代码示例。如果您正苦于以下问题:Python exponential_decay函数的具体用法?Python exponential_decay怎么用?Python exponential_decay使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。


在下文中一共展示了exponential_decay函数的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: testStaircase

 def testStaircase(self):
     with self.test_session():
         step = state_ops.variable_op([], dtypes.int32)
         assign_100 = state_ops.assign(step, 100)
         assign_1 = state_ops.assign(step, 1)
         assign_2 = state_ops.assign(step, 2)
         decayed_lr = learning_rate_decay.exponential_decay(0.1, step, 3, 0.96, staircase=True)
         # No change to learning rate
         assign_1.op.run()
         self.assertAllClose(decayed_lr.eval(), 0.1, 1e-6)
         assign_2.op.run()
         self.assertAllClose(decayed_lr.eval(), 0.1, 1e-6)
         # Decayed learning rate
         assign_100.op.run()
         expected = 0.1 * 0.96 ** (100 // 3)
         self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
开发者ID:peace195,项目名称:tensorflow,代码行数:16,代码来源:learning_rate_decay_test.py

示例2: testVariables

 def testVariables(self):
   step = variables.VariableV1(1)
   assign_1 = step.assign(1)
   assign_2 = step.assign(2)
   assign_100 = step.assign(100)
   decayed_lr = learning_rate_decay.exponential_decay(
       .1, step, 3, 0.96, staircase=True)
   self.evaluate(variables.global_variables_initializer())
   # No change to learning rate
   self.evaluate(assign_1.op)
   self.assertAllClose(self.evaluate(decayed_lr), .1, 1e-6)
   self.evaluate(assign_2.op)
   self.assertAllClose(self.evaluate(decayed_lr), .1, 1e-6)
   # Decayed learning rate
   self.evaluate(assign_100.op)
   expected = .1 * 0.96**(100 // 3)
   self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
开发者ID:aeverall,项目名称:tensorflow,代码行数:17,代码来源:learning_rate_decay_test.py

示例3: testVariables

 def testVariables(self):
     with self.test_session():
         step = variables.Variable(1)
         assign_1 = step.assign(1)
         assign_2 = step.assign(2)
         assign_100 = step.assign(100)
         decayed_lr = learning_rate_decay.exponential_decay(0.1, step, 3, 0.96, staircase=True)
         variables.initialize_all_variables().run()
         # No change to learning rate
         assign_1.op.run()
         self.assertAllClose(decayed_lr.eval(), 0.1, 1e-6)
         assign_2.op.run()
         self.assertAllClose(decayed_lr.eval(), 0.1, 1e-6)
         # Decayed learning rate
         assign_100.op.run()
         expected = 0.1 * 0.96 ** (100 // 3)
         self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
开发者ID:peace195,项目名称:tensorflow,代码行数:17,代码来源:learning_rate_decay_test.py

示例4: testStaircase

 def testStaircase(self):
   with self.test_session():
     step = gen_state_ops._variable(shape=[], dtype=dtypes.int32,
         name="step", container="", shared_name="")
     assign_100 = state_ops.assign(step, 100)
     assign_1 = state_ops.assign(step, 1)
     assign_2 = state_ops.assign(step, 2)
     decayed_lr = learning_rate_decay.exponential_decay(.1, step, 3, 0.96,
                                                        staircase=True)
     # No change to learning rate
     assign_1.op.run()
     self.assertAllClose(decayed_lr.eval(), .1, 1e-6)
     assign_2.op.run()
     self.assertAllClose(decayed_lr.eval(), .1, 1e-6)
     # Decayed learning rate
     assign_100.op.run()
     expected = .1 * 0.96 ** (100 // 3)
     self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
开发者ID:1000sprites,项目名称:tensorflow,代码行数:18,代码来源:learning_rate_decay_test.py

示例5: testStaircase

  def testStaircase(self):
    if context.executing_eagerly():
      step = resource_variable_ops.ResourceVariable(0)
      self.evaluate(variables.global_variables_initializer())
      decayed_lr = learning_rate_decay.exponential_decay(
          .1, step, 3, 0.96, staircase=True)

      # No change to learning rate due to staircase
      expected = .1
      self.evaluate(step.assign(1))
      self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)

      expected = .1
      self.evaluate(step.assign(2))
      self.assertAllClose(self.evaluate(decayed_lr), .1, 1e-6)

      # Decayed learning rate
      expected = .1 * 0.96 ** (100 // 3)
      self.evaluate(step.assign(100))
      self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
开发者ID:aeverall,项目名称:tensorflow,代码行数:20,代码来源:learning_rate_decay_test.py

示例6: testContinuous

 def testContinuous(self):
   with self.test_session():
     step = 5
     decayed_lr = learning_rate_decay.exponential_decay(0.05, step, 10, 0.96)
     expected = .05 * 0.96 ** (5.0 / 10.0)
     self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
开发者ID:821760408-sp,项目名称:tensorflow,代码行数:6,代码来源:learning_rate_decay_test.py

示例7: testContinuous

 def testContinuous(self):
   self.evaluate(variables.global_variables_initializer())
   step = 5
   decayed_lr = learning_rate_decay.exponential_decay(0.05, step, 10, 0.96)
   expected = .05 * 0.96**(5.0 / 10.0)
   self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
开发者ID:aeverall,项目名称:tensorflow,代码行数:6,代码来源:learning_rate_decay_test.py

示例8: f2

 def f2():
   return learning_rate_decay.exponential_decay(lr_init, lr_gstep,
                                                decay_steps, lr_dec, True)
开发者ID:neuroradiology,项目名称:tensorflow,代码行数:3,代码来源:hierarchical_controller.py

示例9: make_opt

 def make_opt():
   gstep = training_util.get_or_create_global_step()
   lr = learning_rate_decay.exponential_decay(1.0, gstep, 10, 0.9)
   return training.GradientDescentOptimizer(lr)
开发者ID:AbhinavJain13,项目名称:tensorflow,代码行数:4,代码来源:gan_estimator_test.py


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