task_list to tasks (#343)

Author: HDCharles

scripts/hf_eval.py

@@ -16,7 +16,7 @@
 torch._inductor.config.force_fuse_int_mm_with_mul = True
 torch._inductor.config.fx_graph_cache = True
 
-def run_evaluation(repo_id, task_list, limit, device, precision, quantization, compile, batch_size, max_length):
+def run_evaluation(repo_id, tasks, limit, device, precision, quantization, compile, batch_size, max_length):
 
     tokenizer = AutoTokenizer.from_pretrained(repo_id)
     model = AutoModelForCausalLM.from_pretrained(repo_id).to(device="cpu", dtype=precision)
@@ -41,7 +41,7 @@ def run_evaluation(repo_id, task_list, limit, device, precision, quantization, c
                 tokenizer=tokenizer, 
                 batch_size=batch_size, 
                 max_length=max_length),
-            get_task_dict(task_list),
+            get_task_dict(tasks),
             limit = limit,
         )
     for task, res in result["results"].items():
@@ -52,7 +52,7 @@ def run_evaluation(repo_id, task_list, limit, device, precision, quantization, c
     import argparse
     parser = argparse.ArgumentParser(description='Run HF Model Evaluation')
     parser.add_argument('--repo_id', type=str, default="meta-llama/Meta-Llama-3-8B", help='Repository ID to download from HF.')
-    parser.add_argument('--task_list', nargs='+', type=str, default=["wikitext"], help='List of lm-eluther tasks to evaluate usage: --tasks task1 task2')
+    parser.add_argument('--tasks', nargs='+', type=str, default=["wikitext"], help='List of lm-eluther tasks to evaluate usage: --tasks task1 task2')
     parser.add_argument('--limit', type=int, default=None, help='Number of eval samples to evaluate')
     parser.add_argument('--precision', type=lambda x: getattr(torch, x.split(".")[-1]), default=torch.bfloat16, help='dtype precision to use')
     parser.add_argument('--device', type=str, default="cuda", help='Device to use for evaluation')
@@ -62,4 +62,4 @@ def run_evaluation(repo_id, task_list, limit, device, precision, quantization, c
     parser.add_argument('--max_length', type=int, default=None, help='Length of text to process at one time')
 
     args = parser.parse_args()
-    run_evaluation(args.repo_id, args.task_list, args.limit, args.device, args.precision, args.quantization, args.compile, args.batch_size, args.max_length)
+    run_evaluation(args.repo_id, args.tasks, args.limit, args.device, args.precision, args.quantization, args.compile, args.batch_size, args.max_length)