class_docstr: Estimator class for training and evaluation BigDL models.
  
  Estimator wraps a model, and provide an uniform training, evaluation or prediction operation on
  both local host and distributed spark environment.
class_docstr_tok: ["Estimator","class","for","training","and","evaluation","BigDL","models",".","Estimator","wraps","a","model",",","and","provide","an","uniform","training",",","evaluation","or","prediction","operation","on","both","local","host","and","distributed","spark","environment","."]
code: def __init__(
      self,
      model,
      optim_methods=None,
      model_dir=None,
      jvalue=None,
      bigdl_type="float",
  ):
      self.bigdl_type = bigdl_type
      self.value = (
          jvalue
          if jvalue
          else callZooFunc(
              bigdl_type,
              self.jvm_class_constructor(),
              model,
              optim_methods,
              model_dir,
          )
      )
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/estimator/estimator.py
imports: from bigdl.util.common import JavaValue
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 1 to create a new Estimator object from inherited base classes: JavaValue with example: obj = Estimator(model, optim_methods, model_dir, jvalue, bigdl_type)