eval_llama_7b_test.py

from mmengine.config import read_base

with read_base():
    from .configs.lark import lark_bot_url
    ########################DATASET##################
    # Standard Benchmarks
    from .configs.datasets.SuperGLUE_BoolQ.SuperGLUE_BoolQ_ppl import BoolQ_datasets
    from .configs.datasets.piqa.piqa_ppl import piqa_datasets
    from .configs.datasets.siqa.siqa_ppl import siqa_datasets
    from .configs.datasets.hellaswag.hellaswag_ppl import hellaswag_datasets
    from .configs.datasets.winogrande.winogrande_ppl import winogrande_datasets
    from .configs.datasets.ARC_e.ARC_e_ppl import ARC_e_datasets
    from .configs.datasets.ARC_c.ARC_c_ppl import ARC_c_datasets
    from .configs.datasets.obqa.obqa_ppl import obqa_datasets
    from .configs.datasets.commonsenseqa.commonsenseqa_ppl_e51e32 import commonsenseqa_datasets
    from .configs.datasets.mmlu.mmlu_ppl import mmlu_datasets
    # Code Generation
    from .configs.datasets.humaneval.humaneval_gen import humaneval_datasets
    from .configs.datasets.mbpp.mbpp_gen import mbpp_datasets
    # World Knowledge           need NaturalQuestions
    from .configs.datasets.nq.nq_gen import nq_datasets
    from .configs.datasets.triviaqa.triviaqa_gen import triviaqa_datasets
    
    # Reading Comprehension       need QUAC
    from .configs.datasets.squad20.squad20_gen import squad20_datasets

    # Exams
    from .configs.datasets.gsm8k.gsm8k_gen import gsm8k_datasets
    from .configs.datasets.math.math_gen import math_datasets
    from .configs.datasets.TheoremQA.TheoremQA_gen import TheoremQA_datasets
    # ceval and cmmlu
    from .configs.datasets.ceval.ceval_ppl import ceval_datasets
    from .configs.datasets.cmmlu.cmmlu_ppl import cmmlu_datasets

    #########################MODEL###################
    from .hf_llama_7b import models

    ######################SUMMERIZER#################
    from .summarizer import dataset_abbrs, summary_groups

datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])

models = models

summarizer = dict(dataset_abbrs=dataset_abbrs, summary_groups=summary_groups, )