class_docstr: Synthetic Reasoning benchmark inspired by
  "LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning"
      https://arxiv.org/abs/2101.06223
class_docstr_tok: ["Synthetic","Reasoning","benchmark","inspired","by","''","LIME",":","Learning","Inductive","Bias","for","Primitives","of","Mathematical","Reasoning","''","https",":","\/\/arxiv.org\/abs\/2101.06223"]
code: def __init__(self, mode: str, random_seed=42):
      super().__init__()
      self.num_train_instances: int = 1000
      self.num_val_instances: int = 5000
      self.num_test_instances: int = 5000
      self.rng = np.random.RandomState(random_seed)
      self.mode = mode
      assert self.mode in [
          "variable_substitution",
          "pattern_match",
          "induction",
      ], f"Unsupported mode: {self.mode}"
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/scenarios/synthetic_reasoning_scenario.py
imports: import numpy
  from typing import List, Dict, Tuple
  from .scenario import Scenario, Instance, Reference, TRAIN_SPLIT, VALID_SPLIT, TEST_SPLIT, CORRECT_TAG, Input, Output
label_desc: Use image node_id 1 to create a new SyntheticReasoningScenario object from inherited base classes: Scenario with example: obj = SyntheticReasoningScenario(mode, random_seed)