from mmengine.config import read_base with read_base(): # choose a list of datasets from opencompass.configs.datasets.gpqa.gpqa_openai_simple_evals_gen_5aeece import \ gpqa_datasets # noqa: F401, E501 from opencompass.configs.datasets.gsm8k.gsm8k_gen_17d0dc import \ gsm8k_datasets # noqa: F401, E501 from opencompass.configs.datasets.race.race_ppl import \ race_datasets # noqa: F401, E501 from opencompass.configs.datasets.winogrande.winogrande_5shot_ll_252f01 import \ winogrande_datasets # noqa: F401, E501 # read hf models - chat models from opencompass.configs.models.chatglm.lmdeploy_glm4_9b import \ models as lmdeploy_glm4_9b_model # noqa: F401, E501 from opencompass.configs.models.deepseek.hf_deepseek_7b_base import \ models as hf_deepseek_7b_base_model # noqa: F401, E501 from opencompass.configs.models.deepseek.lmdeploy_deepseek_7b_base import \ models as lmdeploy_deepseek_7b_base_model # noqa: F401, E501 from opencompass.configs.models.deepseek.lmdeploy_deepseek_67b_base import \ models as lmdeploy_deepseek_67b_base_model # noqa: F401, E501 from opencompass.configs.models.deepseek.lmdeploy_deepseek_v2 import \ lmdeploy_deepseek_v2_model # noqa: F401, E501 from opencompass.configs.models.deepseek.vllm_deepseek_moe_16b_base import \ models as vllm_deepseek_moe_16b_base_model # noqa: F401, E501 from opencompass.configs.models.gemma.hf_gemma2_2b import \ models as hf_gemma2_2b_model # noqa: F401, E501 from opencompass.configs.models.gemma.hf_gemma2_9b import \ models as hf_gemma2_9b_model # noqa: F401, E501 from opencompass.configs.models.gemma.hf_gemma_2b import \ models as hf_gemma_2b_model # noqa: F401, E501 from opencompass.configs.models.gemma.hf_gemma_7b import \ models as hf_gemma_7b_model # noqa: F401, E501 from opencompass.configs.models.gemma.lmdeploy_gemma_9b import \ models as lmdeploy_gemma_9b_model # noqa: F401, E501 from opencompass.configs.models.gemma.vllm_gemma_2b import \ models as vllm_gemma_2b_model # noqa: F401, E501 from opencompass.configs.models.gemma.vllm_gemma_7b import \ models as vllm_gemma_7b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.hf_internlm2_5_7b import \ models as hf_internlm2_5_7b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.hf_internlm2_7b import \ models as hf_internlm2_7b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_1_8b import \ models as lmdeploy_internlm2_1_8b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_5_7b import \ models as lmdeploy_internlm2_5_7b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_7b import \ models as lmdeploy_internlm2_7b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_20b import \ models as lmdeploy_internlm2_20b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_base_7b import \ models as lmdeploy_internlm2_base_7b_model # noqa: F401, E501 from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_base_20b import \ models as lmdeploy_internlm2_base_20b_model # noqa: F401, E501 from opencompass.configs.models.hf_llama.hf_llama2_7b import \ models as hf_llama2_7b_model # noqa: F401, E501 from opencompass.configs.models.hf_llama.hf_llama3_1_8b import \ models as hf_llama3_1_8b_model # noqa: F401, E501 from opencompass.configs.models.hf_llama.hf_llama3_8b import \ models as hf_llama3_8b_model # noqa: F401, E501 from opencompass.configs.models.hf_llama.lmdeploy_llama3_1_8b import \ models as lmdeploy_llama3_1_8b_model # noqa: F401, E501 from opencompass.configs.models.hf_llama.lmdeploy_llama3_8b import \ models as lmdeploy_llama3_8b_model # noqa: F401, E501 from opencompass.configs.models.hf_llama.lmdeploy_llama3_70b import \ models as lmdeploy_llama3_70b_model # noqa: F401, E501 from opencompass.configs.models.mistral.hf_mistral_7b_v0_3 import \ models as hf_mistral_7b_v0_3_model # noqa: F401, E501 from opencompass.configs.models.qwen2_5.hf_qwen_2_5_7b import \ models as hf_qwen_2_5_7b_model # noqa: F401, E501 from opencompass.configs.models.qwen2_5.hf_qwen_2_5_14b import \ models as hf_qwen_2_5_14b_model # noqa: F401, E501 from opencompass.configs.models.qwen2_5.hf_qwen_2_5_32b import \ models as hf_qwen_2_5_32b_model # noqa: F401, E501 from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_1_5b import \ models as lmdeploy_qwen2_5_1_5b_model # noqa: F401, E501 from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_7b import \ models as lmdeploy_qwen2_5_7b_model # noqa: F401, E501 from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_32b import \ models as lmdeploy_qwen2_5_32b_model # noqa: F401, E501 from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_72b import \ models as lmdeploy_qwen2_5_72b_model # noqa: F401, E501 from opencompass.configs.models.qwen.hf_qwen1_5_moe_a2_7b import \ models as hf_qwen1_5_moe_a2_7b_model # noqa: F401, E501 from opencompass.configs.models.qwen.hf_qwen2_0_5b import \ models as hf_qwen2_0_5b_model # noqa: F401, E501 from opencompass.configs.models.qwen.hf_qwen2_1_5b import \ models as hf_qwen2_1_5b_model # noqa: F401, E501 from opencompass.configs.models.qwen.hf_qwen2_7b import \ models as hf_qwen2_7b_model # noqa: F401, E501 from opencompass.configs.models.qwen.lmdeploy_qwen2_1_5b import \ models as lmdeploy_qwen2_1_5b_model # noqa: F401, E501 from opencompass.configs.models.qwen.lmdeploy_qwen2_7b import \ models as lmdeploy_qwen2_7b_model # noqa: F401, E501 from opencompass.configs.models.qwen.vllm_qwen1_5_0_5b import \ models as vllm_qwen1_5_0_5b_model # noqa: F401, E501 from opencompass.configs.models.yi.hf_yi_1_5_6b import \ models as hf_yi_1_5_6b_model # noqa: F401, E501 from opencompass.configs.models.yi.hf_yi_1_5_9b import \ models as hf_yi_1_5_9b_model # noqa: F401, E501 from opencompass.configs.models.yi.lmdeploy_yi_1_5_9b import \ models as lmdeploy_yi_1_5_9b_model # noqa: F401, E501 from ...volc import infer as volc_infer # noqa: F401, E501 race_datasets = [race_datasets[1]] models = sum([v for k, v in locals().items() if k.endswith('_model')], []) datasets = sum([v for k, v in locals().items() if k.endswith('_datasets')], []) for d in datasets: d['reader_cfg']['test_range'] = '[0:32]' for m in models: if 'turbomind' in m['abbr'] or 'lmdeploy' in m['abbr']: m['engine_config']['max_batch_size'] = 1 m['batch_size'] = 1 models = sorted(models, key=lambda x: x['run_cfg']['num_gpus']) summarizer = dict( dataset_abbrs=[ ['gsm8k', 'accuracy'], ['GPQA_diamond', 'accuracy'], ['race-high', 'accuracy'], ['winogrande', 'accuracy'], ], summary_groups=sum( [v for k, v in locals().items() if k.endswith('_summary_groups')], []), )