path: "tensorflow.optimizers.Adagrad"
tf_class {
  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.adagrad.Adagrad\'>"
  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
  is_instance: "<class \'tensorflow.python.training.tracking.base.Trackable\'>"
  is_instance: "<type \'object\'>"
  member {
    name: "iterations"
    mtype: "<type \'property\'>"
  }
  member {
    name: "weights"
    mtype: "<type \'property\'>"
  }
  member_method {
    name: "__init__"
    argspec: "args=[\'self\', \'learning_rate\', \'initial_accumulator_value\', \'epsilon\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.1\', \'1e-07\', \'Adagrad\'], "
  }
  member_method {
    name: "add_slot"
    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
  }
  member_method {
    name: "add_weight"
    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
  }
  member_method {
    name: "apply_gradients"
    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "from_config"
    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "get_config"
    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "get_gradients"
    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "get_slot"
    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "get_slot_names"
    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "get_updates"
    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "get_weights"
    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "minimize"
    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
  }
  member_method {
    name: "set_weights"
    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "variables"
    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
  }
}