Python _create_learning_rate Examples

Example #1

 def testRaiseErrorOnEmptyLearningRate(self):
   learning_rate_text_proto = """
   """
   learning_rate_proto = optimizer_pb2.LearningRate()
   text_format.Merge(learning_rate_text_proto, learning_rate_proto)
   with self.assertRaises(ValueError):
     optimizer_builder._create_learning_rate(learning_rate_proto)

Example #2

File: optimizer_builder_test.py Project: zgsxwsdxg/Tensorflow_SceneText_Oriented_Box_Predictor

 def testBuildConstantLearningRate(self):
     learning_rate_text_proto = """
   constant_learning_rate {
     learning_rate: 0.004
   }
 """
     global_summaries = set([])
     learning_rate_proto = optimizer_pb2.LearningRate()
     text_format.Merge(learning_rate_text_proto, learning_rate_proto)
     learning_rate = optimizer_builder._create_learning_rate(
         learning_rate_proto, global_summaries)
     self.assertAlmostEqual(learning_rate, 0.004)

Example #3

 def testBuildConstantLearningRate(self):
   learning_rate_text_proto = """
     constant_learning_rate {
       learning_rate: 0.004
     }
   """
   learning_rate_proto = optimizer_pb2.LearningRate()
   text_format.Merge(learning_rate_text_proto, learning_rate_proto)
   learning_rate = optimizer_builder._create_learning_rate(
       learning_rate_proto)
   with self.test_session():
     learning_rate_out = learning_rate.eval()
   self.assertAlmostEqual(learning_rate_out, 0.004)

Example #4

 def testBuildCosineDecayLearningRate(self):
   learning_rate_text_proto = """
     cosine_decay_learning_rate {
       learning_rate_base: 0.002
       total_steps: 20000
       warmup_learning_rate: 0.0001
       warmup_steps: 1000
     }
   """
   learning_rate_proto = optimizer_pb2.LearningRate()
   text_format.Merge(learning_rate_text_proto, learning_rate_proto)
   learning_rate = optimizer_builder._create_learning_rate(
       learning_rate_proto)
   self.assertTrue(isinstance(learning_rate, tf.Tensor))

Example #5

 def testBuildExponentialDecayLearningRate(self):
   learning_rate_text_proto = """
     exponential_decay_learning_rate {
       initial_learning_rate: 0.004
       decay_steps: 99999
       decay_factor: 0.85
       staircase: false
     }
   """
   learning_rate_proto = optimizer_pb2.LearningRate()
   text_format.Merge(learning_rate_text_proto, learning_rate_proto)
   learning_rate = optimizer_builder._create_learning_rate(
       learning_rate_proto)
   self.assertTrue(isinstance(learning_rate, tf.Tensor))

Example #6

 def testBuildManualStepLearningRate(self):
   learning_rate_text_proto = """
     manual_step_learning_rate {
       schedule {
         step: 0
         learning_rate: 0.006
       }
       schedule {
         step: 90000
         learning_rate: 0.00006
       }
     }
   """
   learning_rate_proto = optimizer_pb2.LearningRate()
   text_format.Merge(learning_rate_text_proto, learning_rate_proto)
   learning_rate = optimizer_builder._create_learning_rate(
       learning_rate_proto)
   self.assertTrue(isinstance(learning_rate, tf.Tensor))