class_docstr: Analyzes ModelHandlerManager results.
class_docstr_tok: ["Analyzes","ModelHandlerManager","results","."]
code: def __init__(
      self,
      use_cpu_latency_baseline: bool,
      use_cpu_numerics_baseline: bool,
      perf_checkers: Sequence[Callable[[DataFrame], bool]],
      acc_checkers: Sequence[Callable[[DataFrame], bool]],
  ):
      self._use_cpu_latency_baseline = use_cpu_latency_baseline
      self._use_cpu_numerics_baseline = use_cpu_numerics_baseline
      self._perf_checkers = perf_checkers
      self._acc_checkers = acc_checkers
  
imports: import itertools
  import json
  from typing import Any, Callable, Optional, Sequence, Tuple, Union
  from collections import namedtuple
  import numpy
  from tensorflow.python.compiler.tensorrt.model_tests import model_handler
  import tensorflow.python.compiler.tensorrt.trt_convert
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 1 to create a new ResultAnalyzer object  with example: obj = ResultAnalyzer(use_cpu_latency_baseline, use_cpu_numerics_baseline, perf_checkers, acc_checkers)