SUMIN/HuggingFace_transformer
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fix merge

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This commit is contained in:
thomwolf
2019-07-09 17:14:52 +02:00
parent e468192e2f
commit ed6c8d37f4
2 changed files with 3 additions and 3 deletions
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4
examples/run_glue.py
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@@ -183,10 +183,10 @@ def evalutate(args, eval_task, eval_output_dir, dataset, model):
nb_eval_steps += 1 nb_eval_steps += 1
if preds is None: if preds is None:
preds = logits.detach().cpu().numpy() preds = logits.detach().cpu().numpy()
out_label_ids = label_ids.detach().cpu().numpy() out_label_ids = inputs['labels'].detach().cpu().numpy()
else: else:
preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) preds = np.append(preds, logits.detach().cpu().numpy(), axis=0)
out_label_ids = np.append(out_label_ids, label_ids.detach().cpu().numpy(), axis=0) out_label_ids = np.append(out_label_ids, inputs['labels'].detach().cpu().numpy(), axis=0)
eval_loss = eval_loss / nb_eval_steps eval_loss = eval_loss / nb_eval_steps
if args.output_mode == "classification": if args.output_mode == "classification":

2
pytorch_transformers/modeling_bert.py
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@@ -176,7 +176,7 @@ class BertConfig(PretrainedConfig):
initializing all weight matrices. initializing all weight matrices.
layer_norm_eps: The epsilon used by LayerNorm. layer_norm_eps: The epsilon used by LayerNorm.
""" """
pretrained_config_archive_map = PRETRAINED_CONFIG_ARCHIVE_MAP pretrained_config_archive_map = BERT_PRETRAINED_CONFIG_ARCHIVE_MAP
def __init__(self, def __init__(self,
vocab_size_or_config_json_file=30522, vocab_size_or_config_json_file=30522,