Python tensorflow.moving_average_variables() Examples

The following are 30 code examples of tensorflow.moving_average_variables(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow , or try the search function .
Example #1
Source File: ops.py    From pix2vox with GNU General Public License v3.0 6 votes vote down vote up 
def batch_norm(x, train, name, decay=0.99, epsilon=1e-5):
    shape = x.get_shape().as_list()
    with tf.variable_scope(name):
        beta = tf.get_variable('beta', [shape[-1]], initializer=tf.constant_initializer(0.))
        gamma = tf.get_variable('gamma', [shape[-1]], initializer=tf.random_normal_initializer(1., 0.02))
        pop_mean = tf.get_variable('pop_mean', [shape[-1]], initializer=tf.constant_initializer(0.), trainable=False)
        pop_var = tf.get_variable('pop_var', [shape[-1]], initializer=tf.constant_initializer(1.), trainable=False)

        if pop_mean not in tf.moving_average_variables():
            tf.add_to_collection(tf.GraphKeys.MOVING_AVERAGE_VARIABLES, pop_mean)
            tf.add_to_collection(tf.GraphKeys.MOVING_AVERAGE_VARIABLES, pop_var)

        def func1():
            # Execute at training time
            batch_mean, batch_var = tf.nn.moments(x, range(len(shape) - 1))
            update_mean = tf.assign_sub(pop_mean, (1 - decay)*(pop_mean - batch_mean))
            update_var = tf.assign_sub(pop_var, (1 - decay)*(pop_var - batch_var))
            with tf.control_dependencies([update_mean, update_var]):
                return tf.nn.batch_normalization(x, batch_mean, batch_var, beta, gamma, epsilon)

        def func2():
            # Execute at test time
            return tf.nn.batch_normalization(x, pop_mean, pop_var, beta, gamma, epsilon)

        return tf.cond(train, func1, func2)
Example #2
Source File: ops_test.py    From Action_Recognition_Zoo with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithoutScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=False)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #3
Source File: ops_test.py    From models with Apache License 2.0 5 votes vote down vote up 
def testMovingAverageVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #4
Source File: ops_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=True)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #5
Source File: ops_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithoutScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=False)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #6
Source File: ops_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def testCreateVariablesWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      beta = variables.get_variables_by_name('beta')[0]
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #7
Source File: ops_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithoutScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=False)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #8
Source File: ops_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=True)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #9
Source File: ops_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def testCreateVariablesWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      beta = variables.get_variables_by_name('beta')[0]
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #10
Source File: ops_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def testCreateVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images)
      beta = variables.get_variables_by_name('beta')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #11
Source File: ops_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def testMovingAverageVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #12
Source File: ops_test.py    From ECO-pytorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithoutScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=False)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #13
Source File: ops_test.py    From ECO-pytorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=True)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #14
Source File: ops_test.py    From ECO-pytorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def testCreateVariablesWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      beta = variables.get_variables_by_name('beta')[0]
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #15
Source File: ops_test.py    From ECO-pytorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def testCreateVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images)
      beta = variables.get_variables_by_name('beta')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #16
Source File: ops_test.py    From Action_Recognition_Zoo with MIT License 5 votes vote down vote up 
def testMovingAverageVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #17
Source File: ops_test.py    From ECO-pytorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def testMovingAverageVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #18
Source File: ops_test.py    From Action_Recognition_Zoo with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=True)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #19
Source File: ops_test.py    From Action_Recognition_Zoo with MIT License 5 votes vote down vote up 
def testCreateVariablesWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      beta = variables.get_variables_by_name('beta')[0]
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #20
Source File: ops_test.py    From Action_Recognition_Zoo with MIT License 5 votes vote down vote up 
def testCreateVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images)
      beta = variables.get_variables_by_name('beta')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #21
Source File: east_multi_infer.py    From uai-sdk with Apache License 2.0 5 votes vote down vote up 
def begin(self):
       """ Create restoring operations before the graph been finalized. """
       east_variables = tf.moving_average_variables()
       self._restore_ops = [tf.assign(x, self._east.average(x)) for x in east_variables]
Example #22
Source File: ops_test.py    From piecewisecrf with MIT License 5 votes vote down vote up 
def testMovingAverageVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #23
Source File: ops_test.py    From piecewisecrf with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithoutScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=False)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #24
Source File: ops_test.py    From piecewisecrf with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=True)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #25
Source File: ops_test.py    From piecewisecrf with MIT License 5 votes vote down vote up 
def testCreateVariablesWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      beta = variables.get_variables_by_name('beta')[0]
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #26
Source File: ops_test.py    From piecewisecrf with MIT License 5 votes vote down vote up 
def testCreateVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images)
      beta = variables.get_variables_by_name('beta')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #27
Source File: ops_test.py    From DeepSolar with MIT License 5 votes vote down vote up 
def testMovingAverageVariables(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #28
Source File: ops_test.py    From DeepSolar with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithoutScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=False)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')
      self.assertEquals(gamma, [])
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #29
Source File: ops_test.py    From DeepSolar with MIT License 5 votes vote down vote up 
def testCreateVariablesWithoutCenterWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, center=False, scale=True)
      beta = variables.get_variables_by_name('beta')
      self.assertEquals(beta, [])
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')
Example #30
Source File: ops_test.py    From DeepSolar with MIT License 5 votes vote down vote up 
def testCreateVariablesWithScale(self):
    height, width = 3, 3
    with self.test_session():
      images = tf.random_uniform((5, height, width, 3), seed=1)
      ops.batch_norm(images, scale=True)
      beta = variables.get_variables_by_name('beta')[0]
      gamma = variables.get_variables_by_name('gamma')[0]
      self.assertEquals(beta.op.name, 'BatchNorm/beta')
      self.assertEquals(gamma.op.name, 'BatchNorm/gamma')
      moving_mean = tf.moving_average_variables()[0]
      moving_variance = tf.moving_average_variables()[1]
      self.assertEquals(moving_mean.op.name, 'BatchNorm/moving_mean')
      self.assertEquals(moving_variance.op.name, 'BatchNorm/moving_variance')