code: def test_adagrad_output_effective_lr_and_update(
      self, inputs, lr, epsilon, gc, dc
  ):
      param, momentum, grad = inputs
      momentum = np.abs(momentum)
      lr = np.array([lr], dtype=np.float32)
  
      op = core.CreateOperator(
          "Adagrad",
          ["param", "momentum", "grad", "lr"],
          ["param", "momentum", "effective_lr", "update"],
          epsilon=epsilon,
          device_option=gc,
      )
  
      self.assertReferenceChecks(
          gc,
          op,
          [param, momentum, grad, lr],
          functools.partial(
              ref_adagrad,
              epsilon=epsilon,
              output_effective_lr_and_update=True,
          ),
      )
  
file_path: pytorch/caffe2/python/operator_test/adagrad_test.py
imports: import functools
  import caffe2.python.hypothesis_test_util
  import caffe2.python.serialized_test.serialized_test_util
  import hypothesis.strategies
  import numpy
  from caffe2.python import core
  from caffe2.python.operator_test.adagrad_test_helper import adagrad_sparse_test_helper, ref_adagrad
  from hypothesis import HealthCheck, given, settings
label_desc: Use image node_id 3 for calling the TestAdagrad obj's underlying member method code with example usage: obj.test_adagrad_output_effective_lr_and_update(inputs, lr, epsilon, gc, dc) without return types