class_docstr: RMSProp optimiser with default hyper parameters
class_docstr_tok: ["RMSProp","optimiser","with","default","hyper","parameters"]
docstr: create an instance of the optimiser
docstr_tok: ["create","an","instance","of","the","optimiser"]
code: def get_instance(learning_rate):
      """
      create an instance of the optimiser
      """
      return tf.train.RMSPropOptimizer(
          learning_rate=learning_rate,
          decay=0.9,
          momentum=0.0,
          epsilon=1e-10,
          use_locking=False,
          centered=False,
          name="RMSProp",
      )
  
file_path: NiftyNet/niftynet/engine/application_optimiser.py
imports: from __future__ import absolute_import, print_function
  import tensorflow
label_desc: Use image node_id 1 for calling the RMSProp obj's underlying member method code with example usage: obj.get_instance(learning_rate) and returns: tf