What is RMSprop in TF learn explain with example

This recipe explains what is RMSprop in TF learn with example

Recipe Objective

This recipe explains what is RMSProp in TFLayer.

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RMSProp

Its syntax is tflearn.optimizers.RMSProp (learning_rate=0.001, decay=0.9, momentum=0.0, epsilon=1e-10, use_locking=False, name='RMSProp')
where its arguments learning_rate which is learning rate, use_locking which if true uses locks for update operation, name which is the optional name prefix for the operations, epsilon which is a small value to avoid zero as denominator ,and decay which is coming gradient.

class RMSProp(Optimizer):
    def __init__(self, lr=0.001, d=0.9, m=0.0, e=1e-10, ul=False, N="RMSProp"):
       super(RMSProp, self).__init__(lr, ul, N)
       self.d = d
       self.m = m
       self.e = e

    def build(self, st=None):
       self.Built = True
       self.Tensor = tf.train.RMSPropOptimizer(lr=self.lr, d=self.d, m=self.m, e=self.e, ul=self.ul, N=self.N)
rmsprop = RMSProp

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