Fix ernie_gen evaluation bug

modules/text/text_generation/ernie_gen/README.md

@@ -170,9 +170,9 @@ https://github.com/PaddlePaddle/ERNIE/blob/repro/ernie-gen/
 
 ### 依赖
 
-paddlepaddle >= 1.8.2
+paddlepaddle >= 2.0.0
 
-paddlehub >= 1.7.0
+paddlehub >= 2.0.0
 
 paddlenlp >= 2.0.0
 

modules/text/text_generation/ernie_gen/module.py

@@ -42,7 +42,7 @@ from .model import StackModel
     author_email="",
     type="nlp/text_generation",
 )
-class ErnieGen(hub.Module):
+class ErnieGen():
     def __init__(self):
         """
         initialize with the necessary elements
@@ -119,8 +119,7 @@ class ErnieGen(hub.Module):
 
         train_dataset = self._load_dataset(train_path)
         attn_id = self.tokenizer.vocab['[MASK]']
-        trans_func = convert_example(
-            tokenizer=self.tokenizer,
+        trans_func = convert_example(tokenizer=self.tokenizer,
                                      attn_id=attn_id,
                                      tgt_type_id=1,
                                      max_encode_len=max_encode_len,
@@ -139,8 +138,7 @@ class ErnieGen(hub.Module):
             Pad(axis=0, pad_val=self.tokenizer.pad_token_id),  # attn_ids
             Pad(axis=0, pad_val=self.tokenizer.pad_token_id),  # tgt_labels
         ): after_padding(fn(samples))
-        train_data_loader = DataLoader(
-            dataset=train_dataset,
+        train_data_loader = DataLoader(dataset=train_dataset,
                                        batch_sampler=train_batch_sampler,
                                        collate_fn=batchify_fn,
                                        num_workers=0,
@@ -149,8 +147,11 @@ class ErnieGen(hub.Module):
         if dev_path:
             dev_dataset = self._load_dataset(dev_path)
             dev_dataset = dev_dataset.map(trans_func)
-            dev_data_loader = DataLoader(
-                dataset=dev_dataset, batch_size=batch_size, collate_fn=batchify_fn, num_workers=0, return_list=True)
+            dev_data_loader = DataLoader(dataset=dev_dataset,
+                                         batch_size=batch_size,
+                                         collate_fn=batchify_fn,
+                                         num_workers=0,
+                                         return_list=True)
 
         label_num = self.model.word_emb.weight.shape[0]
         train_model = StackModel(self.model)
@@ -158,8 +159,7 @@ class ErnieGen(hub.Module):
         # Generate parameter names needed to perform weight decay.
         # All bias and LayerNorm parameters are excluded.
         decay_params = [p.name for n, p in self.model.named_parameters() if not any(nd in n for nd in ["bias", "norm"])]
-        optimizer = paddle.optimizer.AdamW(
-            learning_rate=lr_scheduler,
+        optimizer = paddle.optimizer.AdamW(learning_rate=lr_scheduler,
                                            parameters=self.model.parameters(),
                                            weight_decay=weight_decay,
                                            grad_clip=nn.ClipGradByGlobalNorm(1.0),
@@ -175,8 +175,8 @@ class ErnieGen(hub.Module):
                 (src_ids, src_tids, src_pids, tgt_ids, tgt_tids, tgt_pids, attn_ids, mask_src_2_src, mask_tgt_2_srctgt,
                  mask_attn_2_srctgtattn, tgt_labels, _) = batch
                 if label_smooth > 0.:
-                    tgt_labels = nn.functional.label_smooth(
-                        nn.functional.one_hot(tgt_labels, label_num), epsilon=label_smooth)
+                    tgt_labels = nn.functional.label_smooth(nn.functional.one_hot(tgt_labels, label_num),
+                                                            epsilon=label_smooth)
 
                 tgt_pos = paddle.nonzero(attn_ids == attn_id)
                 loss = train_model(src_ids, src_tids, src_pids, tgt_ids, tgt_tids, tgt_pids, attn_ids, mask_src_2_src,
@@ -190,8 +190,8 @@ class ErnieGen(hub.Module):
                 if global_step % log_interval == 0 and paddle.distributed.get_rank() == 0:
                     loss_np = loss.numpy()
                     ppl = np.exp(loss_np)
-                    logger.info('[step %d / %d]train loss %.5f, ppl %.5f, elr %.3e' % (global_step, max_steps, loss_np,
-                                                                                       ppl, lr_scheduler.get_lr()))
+                    logger.info('[step %d / %d]train loss %.5f, ppl %.5f, elr %.3e' %
+                                (global_step, max_steps, loss_np, ppl, lr_scheduler.get_lr()))
                 if save_dir and global_step % save_interval == 0 and global_step > 0:
                     loss_np = loss.numpy()
                     ppl = np.exp(loss_np)
@@ -214,8 +214,8 @@ class ErnieGen(hub.Module):
         if global_step % save_interval != 0:
             loss_np = loss.numpy()
             ppl = np.exp(loss_np)
-            logger.info('[final step %d]train loss %.5f, ppl %.5f, elr %.3e' % (global_step, loss_np, ppl,
-                                                                                lr_scheduler.get_lr()))
+            logger.info('[final step %d]train loss %.5f, ppl %.5f, elr %.3e' %
+                        (global_step, loss_np, ppl, lr_scheduler.get_lr()))
             if save_dir:
                 save_name = "step_%s_ppl_%.5f.pdparams" % (global_step, ppl)
                 save_path = os.path.join(save_dir, save_name)
@@ -291,6 +291,7 @@ class ErnieGen(hub.Module):
 
     def _evaluate(self, model, data_loader, tokenizer, rouge1, rouge2, attn_id, max_decode_len, max_encode_len,
                   beam_width, length_penalty):
+        paddle.disable_static()
         model.eval()
 
         vocab = tokenizer.vocab
@@ -305,8 +306,7 @@ class ErnieGen(hub.Module):
         for data in data_loader:
             (src_ids, src_tids, src_pids, _, _, _, _, _, _, _, _, raw_tgt_labels) = data  # never use target when infer
             # Use greedy_search_infilling or beam_search_infilling to get predictions
-            output_ids = beam_search_infilling(
-                model,
+            output_ids = beam_search_infilling(model,
                                                src_ids,
                                                src_tids,
                                                eos_id=eos_id,
@@ -361,8 +361,7 @@ class ErnieGen(hub.Module):
 
 if __name__ == "__main__":
     module = ErnieGen()
-    result = module.finetune(
-        train_path='test_data/train.txt',
+    result = module.finetune(train_path='test_data/train.txt',
                              dev_path='test_data/dev.txt',
                              max_steps=30,
                              batch_size=2,

modules/text/text_generation/ernie_gen_acrostic_poetry/README.md

@@ -99,9 +99,9 @@ https://github.com/PaddlePaddle/ERNIE/blob/repro/ernie-gen/
 
 ### 依赖
 
-paddlepaddle >= 1.8.2
+paddlepaddle >= 2.0.0
 
-paddlehub >= 1.7.0
+paddlehub >= 2.0.0
 
 paddlenlp >= 2.0.0
 

modules/text/text_generation/ernie_gen_couplet/README.md

@@ -87,9 +87,9 @@ https://github.com/PaddlePaddle/ERNIE/blob/repro/ernie-gen/
 
 ### 依赖
 
-paddlepaddle >= 1.8.2
+paddlepaddle >= 2.0.0
 
-paddlehub >= 1.7.0
+paddlehub >= 2.0.0
 
 paddlenlp >= 2.0.0
 

modules/text/text_generation/ernie_gen_lover_words/README.md

@@ -87,9 +87,9 @@ https://github.com/PaddlePaddle/ERNIE/blob/repro/ernie-gen/
 
 ### 依赖
 
-paddlepaddle >= 1.8.2
+paddlepaddle >= 2.0.0
 
-paddlehub >= 1.7.0
+paddlehub >= 2.0.0
 
 paddlenlp >= 2.0.0
 

modules/text/text_generation/ernie_gen_poetry/README.md

@@ -87,11 +87,11 @@ https://github.com/PaddlePaddle/ERNIE/blob/repro/ernie-gen/
 
 ### 依赖
 
-paddlepaddle >= 1.8.2
+paddlepaddle >= 2.0.0
 
-paddlehub >= 1.7.0
+paddlehub >= 2.0.0
 
-PaddleNLP >= 2.0.0
+paddlenlp >= 2.0.0
 
 
 ## 更新历史