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Fix trainer evaluation (#4363)

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* fix loss calculation in evaluation

* fix evaluation on TPU when prediction_loss_only is True
This commit is contained in:
Suraj Patil
2020-05-15 00:09:44 +05:30
committed by GitHub
parent 035678efdb
commit 2d05480174
1 changed files with 2 additions and 2 deletions
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src/transformers/trainer.py
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@@ -679,7 +679,7 @@ class Trainer:
model.eval() model.eval()
for inputs in tqdm(dataloader, desc=description): for inputs in tqdm(dataloader, desc=description):
has_labels = any(inputs.get(k) is not None for k in ["labels", "masked_lm_labels"]) has_labels = any(inputs.get(k) is not None for k in ["labels", "lm_labels", "masked_lm_labels"])
for k, v in inputs.items(): for k, v in inputs.items():
inputs[k] = v.to(self.args.device) inputs[k] = v.to(self.args.device)
@@ -703,7 +703,7 @@ class Trainer:
else: else:
label_ids = np.append(label_ids, inputs["labels"].detach().cpu().numpy(), axis=0) label_ids = np.append(label_ids, inputs["labels"].detach().cpu().numpy(), axis=0)
if is_tpu_available(): if is_tpu_available() and preds is not None and label_ids is not None:
# tpu-comment: Get all predictions and labels from all worker shards of eval dataset # tpu-comment: Get all predictions and labels from all worker shards of eval dataset
preds = xm.mesh_reduce("eval_preds", preds, np.concatenate) preds = xm.mesh_reduce("eval_preds", preds, np.concatenate)
label_ids = xm.mesh_reduce("eval_out_label_ids", label_ids, np.concatenate) label_ids = xm.mesh_reduce("eval_out_label_ids", label_ids, np.concatenate)