class_docstr: User-facing API for accessing the NASBench dataset.
docstr: Returns the metrics for all epochs and all repeats of a hash.
  
  This method is for dataset analysis and should not be used for benchmarking.
  As such, it does not increment any of the budget counters.
  
  Args:
    module_hash: MD5 hash, i.e., the values yielded by hash_iterator().
  
  Returns:
    fixed stats and computed stats of the model spec provided.
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code: def get_metrics_from_hash(self, module_hash):
      """Returns the metrics for all epochs and all repeats of a hash.
  
      This method is for dataset analysis and should not be used for benchmarking.
      As such, it does not increment any of the budget counters.
  
      Args:
        module_hash: MD5 hash, i.e., the values yielded by hash_iterator().
  
      Returns:
        fixed stats and computed stats of the model spec provided.
      """
      fixed_stat = copy.deepcopy(self.fixed_statistics[module_hash])
      computed_stat = copy.deepcopy(
          self.computed_statistics[module_hash]
      )
      return fixed_stat, computed_stat
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import random
  import time
  import shelve
  import hashlib
  import _pickle
  import numpy
label_desc: Use image node_id 7 for calling the NASBench obj's underlying member method code with example usage: obj.get_metrics_from_hash(module_hash) and returns: fixed_stat,  computed_stat