fix Sampler in distributed training - evaluation

2020-01-08 15:50:42 -05:00
parent af1ee9e648
commit 45634f87f8
1 changed files with 1 additions and 1 deletions
--- a/examples/distillation/run_squad_w_distillation.py
+++ b/examples/distillation/run_squad_w_distillation.py
@@ -264,7 +264,7 @@ def evaluate(args, model, tokenizer, prefix=""):

    args.eval_batch_size = args.per_gpu_eval_batch_size * max(1, args.n_gpu)
    # Note that DistributedSampler samples randomly
-    eval_sampler = SequentialSampler(dataset) if args.local_rank == -1 else DistributedSampler(dataset)
+    eval_sampler = SequentialSampler(dataset)
    eval_dataloader = DataLoader(dataset, sampler=eval_sampler, batch_size=args.eval_batch_size)

    # Eval!