# Copyright (c) 2024, EleutherAI # This file is based on code by the authors denoted below and has been modified from its original version. # # Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Evaluation tasks - modified from https://github.com/EleutherAI/lm-evaluation-harness""" import os import sys sys.path.append( os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir)) ) from megatron.training import forward_step from megatron.utils import setup_for_inference_or_eval, init_wandb from megatron.logging import tb_wandb_log from eval_tasks import run_eval_harness from pprint import pprint from datetime import datetime import json def main(input_args=None, overwrite_values=None): model, neox_args = setup_for_inference_or_eval( use_cache=False, input_args=input_args, overwrite_values=overwrite_values ) results = run_eval_harness( model, forward_step, neox_args, eval_tasks=neox_args.eval_tasks, bootstrap_iters=10000, ) if neox_args.rank == 0: init_wandb(neox_args=neox_args) # log to wandb for k, v in results["results"].items(): if isinstance(v, dict): for k2, v2 in v.items(): k3 = "_".join([k, k2]) tb_wandb_log( f"eval/{k3}", v2, neox_args.iteration, use_wandb=neox_args.use_wandb, ) else: tb_wandb_log( f"eval/{k}", v, neox_args.iteration, use_wandb=neox_args.use_wandb, ) pprint(results) results_path = ( f'eval_results_{datetime.now().strftime("%m-%d-%Y-%H-%M-%S")}.json' ) if neox_args.eval_results_prefix: results_path = f"{neox_args.eval_results_prefix}_{results_path}" with open(results_path, "w") as f: json.dump(results, f, indent=4) if __name__ == "__main__": main()