class_docstr: Estimator implementation for Mask-RCNN.
  
  Parameters
  ----------
  config : dict
      Config in nested dict.
  logger : logging.Logger, default is None
      Optional logger for this estimator, can be `None` when default setting is used.
  reporter : callable, default is None
      If set, use reporter callback to report the metrics of the current estimator.
  
  Attributes
  ----------
  _logger : logging.Logger
      The customized/default logger for this estimator.
  _logdir : str
      The temporary dir for logs.
  _cfg : autocfg.dataclass
      The configurations.
class_docstr_tok: ["Estimator","implementation","for","Mask-RCNN",".","Parameters","--","--","--","--","--","config",":","dict","Config","in","nested","dict",".","logger",":","logging.Logger",",","default","is","None","Optional","logger","for","this","estimator",",","can","be","`","None","`","when","default","setting","is","used",".","reporter",":","callable",",","default","is","None","If","set",",","use","reporter","callback","to","report","the","metrics","of","the","current","estimator",".","Attributes","--","--","--","--","--","_logger",":","logging.Logger","The","customized\/default","logger","for","this","estimator",".","_logdir",":","str","The","temporary","dir","for","logs",".","_cfg",":","autocfg.dataclass","The","configurations","."]
docstr: Evaluate the current model on dataset.
          
docstr_tok: ["Evaluate","the","current","model","on","dataset","."]
code: def _evaluate(self, val_data):
      """Evaluate the current model on dataset."""
      # TODO(zhreshold): remove self._val_data, use passed in val_data at runtime
      return self._validate(
          self._val_data,
          self.async_eval_processes,
          self.ctx,
          self.eval_metric,
          self._logger,
          self.epoch,
          self.best_map,
      )
  
imports: import os
  import math
  import time
  import logging
  from multiprocessing import Process
  import numpy
  import mxnet
  from mxnet import gluon
  from mxnet.contrib import amp
  from ....None import data
  from ....None import utils
  from ....data import COCODetection, VOCDetection
  from ....data.transforms import presets
  from ....data.transforms.presets.rcnn import MaskRCNNDefaultTrainTransform, MaskRCNNDefaultValTransform
  from ....model_zoo import get_model
  from ....model_zoo.rcnn.mask_rcnn.data_parallel import ForwardBackwardTask
  from ....nn.bbox import BBoxClipToImage
  from ....utils.parallel import Parallel
  from ....utils.metrics.rcnn import RPNAccMetric, RPNL1LossMetric, RCNNAccMetric, RCNNL1LossMetric, MaskAccMetric, MaskFGAccMetric
  from ..base_estimator import BaseEstimator, set_default
  from .utils import _get_dataset, _get_dataloader, _save_params, _split_and_load, _get_lr_at_iter
  from .default import MaskRCNNCfg
label_desc: Use image node_id 4 for calling the MaskRCNNEstimator obj's underlying member method code with example usage: obj._evaluate(val_data) and returns: self