class_docstr: BaseClass for systems that want to provide training labels for examples.
  
  A VariantLabeler provides methods to assign a genotype label to each of a
  series of candidate variants using data from a truth set of variants
  accessible with vcf_reader and an optional RangeSet of confident regions.
  
  The basic logic of this class is something like:
  
  candidates = [third_party.nucleus.protos.Variant(...), ...]
  labeler = ConcreteSubclassOfVariantLabeler(vcf_reader, confident_regions)
  for label in labeler.label_variants(candidates):
    if label.is_confident:
      for i in range(len(label.variant.alternate_bases)
        genotype_label_value = label.label_for_alt_alleles([i])
  
  See the docs on each individual function to get a better understanding of what
  each function does and the meaning of the return values.
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docstr: Gets the LabelingMetrics proto tracking metrics for this labeler.
  
  A variant labeler may provide information information about the labeling of
  variants via the metrics property. If the labeler provides metrics, a
  filled in LabelingMetrics protobuf will be returned by this property. If
  metrics aren't supported, a None value will be returned.
docstr_tok: ["Gets","the","LabelingMetrics","proto","tracking","metrics","for","this","labeler",".","A","variant","labeler","may","provide","information","information","about","the","labeling","of","variants","via","the","metrics","property",".","If","the","labeler","provides","metrics",",","a","filled","in","LabelingMetrics","protobuf","will","be","returned","by","this","property",".","If","metrics","are","n't","supported",",","a","None","value","will","be","returned","."]
code: def metrics(self):
      """Gets the LabelingMetrics proto tracking metrics for this labeler.
  
      A variant labeler may provide information information about the labeling of
      variants via the metrics property. If the labeler provides metrics, a
      filled in LabelingMetrics protobuf will be returned by this property. If
      metrics aren't supported, a None value will be returned.
      """
      return None
  
file_path: deepvariant/deepvariant/labeler/variant_labeler.py
imports: import abc
  from absl import logging
  from third_party.nucleus.util import variant_utils
  from third_party.nucleus.util import variantcall_utils
  from deepvariant import dv_utils
label_desc: Use image node_id 2 for calling the VariantLabeler obj's underlying member method code with example usage: obj.metrics() and returns: None