class_docstr: AdaGrad optimizer.
  
  See: http://jmlr.org/papers/v12/duchi11a.html
  
  Args:
      lr (float): Learning rate.
      eps (float): Small value for the numerical stability.
class_docstr_tok: ["AdaGrad","optimizer",".","See",":","http",":","\/\/jmlr.org\/papers\/v12\/duchi11a.html","Args",":","lr","(","float",")",":","Learning","rate",".","eps","(","float",")",":","Small","value","for","the","numerical","stability","."]
code: def create_update_rule(self):
      return AdaGradRule(self.hyperparam)
  
file_path: chainer/chainer/optimizers/ada_grad.py
imports: import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import optimizer
  from chainer import types
label_desc: Use image node_id 2 for calling the AdaGrad obj's underlying member method code with example usage: obj.create_update_rule() and returns: AdaGradRule