diff --git a/examples/information_extraction/waybill_ie/run_bigru_crf.py b/examples/information_extraction/waybill_ie/run_bigru_crf.py index d506944f67db12..db8b5ba4838d24 100644 --- a/examples/information_extraction/waybill_ie/run_bigru_crf.py +++ b/examples/information_extraction/waybill_ie/run_bigru_crf.py @@ -87,9 +87,9 @@ def predict(model, data_loader, ds, label_vocab): test_ds.map(trans_func) batchify_fn = lambda samples, fn=Tuple( - Pad(axis=0, pad_val=word_vocab.get('OOV', 0)), # token_ids - Stack(), # seq_len - Pad(axis=0, pad_val=label_vocab.get('O', 0)) # label_ids + Pad(axis=0, pad_val=word_vocab.get('OOV', 0), dtype='int32'), # token_ids + Stack(dtype='int64'), # seq_len + Pad(axis=0, pad_val=label_vocab.get('O', 0), dtype='int64') # label_ids ): fn(samples) train_loader = paddle.io.DataLoader( diff --git a/examples/information_extraction/waybill_ie/run_ernie.py b/examples/information_extraction/waybill_ie/run_ernie.py index fd10e100dbfaf1..532562ff82942f 100644 --- a/examples/information_extraction/waybill_ie/run_ernie.py +++ b/examples/information_extraction/waybill_ie/run_ernie.py @@ -83,10 +83,10 @@ def predict(model, data_loader, ds, label_vocab): ignore_label = -1 batchify_fn = lambda samples, fn=Tuple( - Pad(axis=0, pad_val=tokenizer.pad_token_id), # input_ids - Pad(axis=0, pad_val=tokenizer.pad_token_type_id), # token_type_ids - Stack(), # seq_len - Pad(axis=0, pad_val=ignore_label) # labels + Pad(axis=0, pad_val=tokenizer.pad_token_id, dtype='int32'), # input_ids + Pad(axis=0, pad_val=tokenizer.pad_token_type_id, dtype='int32'), # token_type_ids + Stack(dtype='int64'), # seq_len + Pad(axis=0, pad_val=ignore_label, dtype='int64') # labels ): fn(samples) train_loader = paddle.io.DataLoader( diff --git a/examples/information_extraction/waybill_ie/run_ernie_crf.py b/examples/information_extraction/waybill_ie/run_ernie_crf.py index f2d428fb8b674c..3bf11df1515e01 100644 --- a/examples/information_extraction/waybill_ie/run_ernie_crf.py +++ b/examples/information_extraction/waybill_ie/run_ernie_crf.py @@ -81,10 +81,10 @@ def predict(model, data_loader, ds, label_vocab): test_ds.map(trans_func) batchify_fn = lambda samples, fn=Tuple( - Pad(axis=0, pad_val=tokenizer.pad_token_id), # input_ids - Pad(axis=0, pad_val=tokenizer.pad_token_type_id), # token_type_ids - Stack(), # seq_len - Pad(axis=0, pad_val=label_vocab.get("O", 0)) # labels + Pad(axis=0, pad_val=tokenizer.pad_token_id, dtype='int32'), # input_ids + Pad(axis=0, pad_val=tokenizer.pad_token_type_id, dtype='int32'), # token_type_ids + Stack(dtype='int64'), # seq_len + Pad(axis=0, pad_val=label_vocab.get("O", 0), dtype='int64') # labels ): fn(samples) train_loader = paddle.io.DataLoader(