siamese uie supports string-type schema input

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/11655620

modelscope/pipelines/nlp/siamese_uie_pipeline.py

@@ -8,6 +8,7 @@ from math import ceil
 from time import time
 from typing import Any, Dict, Generator, List, Mapping, Optional, Union
 
+import json
 import torch
 from scipy.special import softmax
 from torch.cuda.amp import autocast
@@ -89,7 +90,7 @@ class SiameseUiePipeline(Pipeline):
         """
         Args:
             input(str): sentence to extract
-            schema: (dict) schema of uie task
+            schema: (dict or str) schema of uie task
         Default Returns:
             List[List]:  predicted info list i.e.
             [[{'type': '人物', 'span': '谷口清太郎', 'offset': [18, 23]}],
@@ -111,6 +112,8 @@ class SiameseUiePipeline(Pipeline):
         # sanitize the parameters
         text = input
         schema = kwargs.pop('schema')
+        if type(schema) == str:
+            schema = json.loads(schema)
         output_all_prefix = kwargs.pop('output_all_prefix', False)
         tokenized_text = self.preprocessor([text])[0]
         pred_info_list = []

tests/pipelines/test_siamese_uie.py

@@ -1,6 +1,8 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 import unittest
 
+import json
+
 from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.models import Model
 from modelscope.models.nlp import SiameseUieModel
@@ -38,7 +40,8 @@ class ZeroShotClassificationTest(unittest.TestCase, DemoCompatibilityCheck):
 
         print(
             f'sentence: {self.sentence}\n'
-            f'pipeline1:{pipeline1(input=self.sentence, schema=self.schema)}')
+            f'pipeline1:{pipeline1(input=self.sentence, schema=json.dumps(self.schema, ensure_ascii=False))}'
+        )
         print(f'sentence: {self.sentence}\n'
               f'pipeline2: {pipeline2(self.sentence, schema=self.schema)}')