docstr: Get the scalar from model validation summary
  Return 2-D array like object which could be converted
  by np.array()
  
  Note: The metric and tag may not be consistent
  Please look up following form to pass tag parameter
  Left side is your metric during compile
  Right side is the tag you should pass
  'Accuracy'                  |   'Top1Accuracy'
  'BinaryAccuracy'            |   'Top1Accuracy'
  'CategoricalAccuracy'       |   'Top1Accuracy'
  'SparseCategoricalAccuracy' |   'Top1Accuracy'
  'AUC'                       |   'AucScore'
  'HitRatio'                  |   'HitRate@k' (k is Top-k)
  'Loss'                      |   'Loss'
  'MAE'                       |   'MAE'
  'NDCG'                      |   'NDCG'
  'TFValidationMethod'        |   '${name + " " + valMethod.toString()}'
  'Top5Accuracy'              |   'Top5Accuracy'
  'TreeNNAccuracy'            |   'TreeNNAccuracy()'
  'MeanAveragePrecision'      |   'MAP@k' (k is Top-k) (BigDL)
  'MeanAveragePrecision'      |   'PascalMeanAveragePrecision' (Zoo)
  'StatelessMetric'           |   '${name}'
  # Arguments
  tag: The string variable represents the scalar wanted
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code: def get_validation_summary(self, tag=None):
      """
      Get the scalar from model validation summary
      Return 2-D array like object which could be converted
      by np.array()
  
      Note: The metric and tag may not be consistent
      Please look up following form to pass tag parameter
      Left side is your metric during compile
      Right side is the tag you should pass
      'Accuracy'                  |   'Top1Accuracy'
      'BinaryAccuracy'            |   'Top1Accuracy'
      'CategoricalAccuracy'       |   'Top1Accuracy'
      'SparseCategoricalAccuracy' |   'Top1Accuracy'
      'AUC'                       |   'AucScore'
      'HitRatio'                  |   'HitRate@k' (k is Top-k)
      'Loss'                      |   'Loss'
      'MAE'                       |   'MAE'
      'NDCG'                      |   'NDCG'
      'TFValidationMethod'        |   '${name + " " + valMethod.toString()}'
      'Top5Accuracy'              |   'Top5Accuracy'
      'TreeNNAccuracy'            |   'TreeNNAccuracy()'
      'MeanAveragePrecision'      |   'MAP@k' (k is Top-k) (BigDL)
      'MeanAveragePrecision'      |   'PascalMeanAveragePrecision' (Zoo)
      'StatelessMetric'           |   '${name}'
      # Arguments
      tag: The string variable represents the scalar wanted
      """
      return callZooFunc(
          self.bigdl_type,
          "zooGetScalarFromSummary",
          self.value,
          tag,
          "Validation",
      )
  
imports: import zoo.pipeline.api.autograd
  from zoo.feature.image import ImageSet
  from zoo.feature.text import TextSet
  from zoo.feature.common import FeatureSet
  from zoo.pipeline.api.keras.base import ZooKerasLayer
  from zoo.pipeline.api.keras.utils import *
  from bigdl.nn.layer import Layer
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 6 for calling the KerasNet obj's underlying member method code with example usage: obj.get_validation_summary(tag) and returns: callZooFunc