pre-commit

ppocr/postprocess/vqa_token_ser_layoutlm_postprocess.py

@@ -68,7 +68,8 @@ class VQASerTokenLayoutLMPostProcess(object):
     def _infer(self, preds, segment_offset_ids, ocr_infos):
         results = []
 
-        for pred, segment_offset_id, ocr_info in zip(preds, segment_offset_ids, ocr_infos):
+        for pred, segment_offset_id, ocr_info in zip(preds, segment_offset_ids,
+                                                     ocr_infos):
             pred = np.argmax(pred, axis=1)
             pred = [self.id2label_map[idx] for idx in pred]
 

ppstructure/utility.py

@@ -40,7 +40,6 @@ def init_args():
         type=ast.literal_eval,
         default=None,
         help='label map according to ppstructure/layout/README_ch.md')
-
     # params for vqa
     parser.add_argument("--vqa_algorithm", type=str, default='LayoutXLM')
     parser.add_argument("--ser_model_dir", type=str)

tools/export_model.py

@@ -97,8 +97,9 @@ def export_single_model(model,
                 shape=[None, 1, 32, 100], dtype="float32"),
         ]
         model = to_static(model, input_spec=other_shape)
+
     elif arch_config["algorithm"] in ["LayoutLM", "LayoutLMv2", "LayoutXLM"]:
-        input_spec=[
+        input_spec = [
             paddle.static.InputSpec(
                 shape=[None, 512], dtype="int64"),  # input_ids
             paddle.static.InputSpec(

tools/infer/utility.py

@@ -318,7 +318,7 @@ def create_predictor(args, mode, logger):
         # create predictor
         predictor = inference.create_predictor(config)
         input_names = predictor.get_input_names()
-        if mode in ['ser','re']:
+        if mode in ['ser', 're']:
             input_tensor = []
             for name in input_names:
                 input_tensor.append(predictor.get_input_handle(name))

tools/infer_vqa_token_ser.py

@@ -72,7 +72,10 @@ class SerPredictor(object):
 
         from paddleocr import PaddleOCR
 
-        self.ocr_engine = PaddleOCR(use_angle_cls=False, show_log=False, use_gpu=global_config['use_gpu'])
+        self.ocr_engine = PaddleOCR(
+            use_angle_cls=False,
+            show_log=False,
+            use_gpu=global_config['use_gpu'])
 
         # create data ops
         transforms = []
@@ -82,8 +85,8 @@ class SerPredictor(object):
                 op[op_name]['ocr_engine'] = self.ocr_engine
             elif op_name == 'KeepKeys':
                 op[op_name]['keep_keys'] = [
-                    'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels',
-                    'segment_offset_id', 'ocr_info',
+                    'input_ids', 'bbox', 'attention_mask', 'token_type_ids',
+                    'image', 'labels', 'segment_offset_id', 'ocr_info',
                     'entities'
                 ]
 
@@ -105,9 +108,7 @@ class SerPredictor(object):
             preds = preds[0]
 
         post_result = self.post_process_class(
-            preds,
-            segment_offset_ids=batch[6],
-            ocr_infos=batch[7])
+            preds, segment_offset_ids=batch[6], ocr_infos=batch[7])
         return post_result, batch
 
 
@@ -154,4 +155,3 @@ if __name__ == '__main__':
 
             logger.info("process: [{}/{}], save result to {}".format(
                 idx, len(infer_imgs), save_img_path))
-