Fix windows dtype (#1480)

* fix variable name

* fix windows dtype

Author: linjieccc

examples/few_shot/efl/deploy/python/predict.py

@@ -163,8 +163,8 @@ def predict(self, data, tokenizer):
             examples.append((input_ids, segment_ids))
 
         batchify_fn = lambda samples, fn=Tuple(
-            Pad(axis=0, pad_val=tokenizer.pad_token_id),  # input
-            Pad(axis=0, pad_val=tokenizer.pad_token_id),  # segment
+            Pad(axis=0, pad_val=tokenizer.pad_token_id, dtype="int64"),  # input
+            Pad(axis=0, pad_val=tokenizer.pad_token_id, dtype="int64"),  # segment
         ): fn(samples)
 
         if args.benchmark:

examples/sentiment_analysis/skep/deploy/python/predict.py

@@ -43,8 +43,8 @@ def convert_example(example,
                     is_test=False):
     text = example
     encoded_inputs = tokenizer(text=text, max_seq_len=max_seq_length)
-    input_ids = np.array(tokenized_input['input_ids'], dtype="int64")
-    token_type_ids = np.array(tokenized_input['token_type_ids'], dtype="int64")
+    input_ids = np.array(encoded_inputs['input_ids'], dtype="int64")
+    token_type_ids = np.array(encoded_inputs['token_type_ids'], dtype="int64")
     return input_ids, token_type_ids
 
 

examples/text_matching/ernie_matching/README.md

@@ -153,14 +153,18 @@ python -u -m paddle.distributed.launch --gpus "0" \
 #### 模型导出
 使用动态图训练结束之后，可以使用静态图导出工具 `export_model.py` 将动态图参数导出成静态图参数。 执行如下命令：
 
-`python export_model.py --params_path ernie_ckpt/model_80.pdparams --output_path=./output`
+```shell
+python export_model.py --params_path checkpoints/model_300/model_state.pdparams --output_path=./output
+```
 
 其中`params_path`是指动态图训练保存的参数路径，`output_path`是指静态图参数导出路径。
 
 #### 预测部署
 导出静态图模型之后，可以基于静态图模型进行预测，`deploy/python/predict.py` 文件提供了静态图预测示例。执行如下命令：
 
-`python deploy/python/predict.py --model_dir ./output`
+```shell
+python deploy/python/predict.py --model_dir ./output
+```
 
 ## Reference
 [1] Xin Liu, Qingcai Chen, Chong Deng, Huajun Zeng, Jing Chen, Dongfang Li, Buzhou Tang, LCQMC: A Large-scale Chinese Question Matching Corpus,COLING2018.

examples/text_matching/ernie_matching/deploy/python/predict.py

@@ -176,8 +176,8 @@ def predict(self, data, tokenizer, label_map):
             examples.append((input_ids, segment_ids))
 
         batchify_fn = lambda samples, fn=Tuple(
-            Pad(axis=0, pad_val=tokenizer.pad_token_id),  # input
-            Pad(axis=0, pad_val=tokenizer.pad_token_id),  # segment
+            Pad(axis=0, pad_val=tokenizer.pad_token_id, dtype="int64"),  # input
+            Pad(axis=0, pad_val=tokenizer.pad_token_id, dtype="int64"),  # segment
         ): fn(samples)
 
         if args.benchmark: