class_docstr: Combines the ValidationResults protos.
  
  Combines PCollection of ValidationResults for different metrics and slices.
class_docstr_tok: ["Combines","the","ValidationResults","protos",".","Combines","PCollection","of","ValidationResults","for","different","metrics","and","slices","."]
code: def __init__(
      self,
      eval_config: config_pb2.EvalConfig,
      rubber_stamp: bool = False,
  ):
      self._eval_config = eval_config
      self._rubber_stamp = rubber_stamp
  
imports: import itertools
  import os
  from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple, Union
  from absl import logging
  import apache_beam
  import numpy
  import pyarrow
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.evaluators import evaluator
  from tensorflow_model_analysis.evaluators import metrics_validator
  from tensorflow_model_analysis.metrics import calibration_plot
  from tensorflow_model_analysis.metrics import confusion_matrix_plot
  from tensorflow_model_analysis.metrics import metric_specs
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.post_export_metrics import metric_keys
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from tensorflow_model_analysis.proto import validation_result_pb2
  from tensorflow_model_analysis.slicer import slicer_lib
  from tensorflow_model_analysis.utils import math_util
  from tensorflow_model_analysis.writers import writer
  from google.protobuf import wrappers_pb2
label_desc: Use image node_id 1 to create a new CombineValidations object from inherited base classes: beam with example: obj = CombineValidations(eval_config, rubber_stamp)