[to #42322933] Add bloom model

添加 bloom 模型
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10509187

modelscope/metainfo.py

@@ -80,6 +80,7 @@ class Models(object):
     bert_for_ds = 'bert-for-document-segmentation'
     ponet = 'ponet'
     T5 = 'T5'
+    bloom = 'bloom'
 
     # audio models
     sambert_hifigan = 'sambert-hifigan'

modelscope/models/nlp/bloom/backbone.py

@@ -0,0 +1,15 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
+from transformers import BloomConfig
+from transformers import BloomModel as BloomModelTransform
+
+from modelscope.metainfo import Models
+from modelscope.models.builder import BACKBONES
+from modelscope.utils.constant import Fields
+
+
+@BACKBONES.register_module(group_key=Fields.nlp, module_name=Models.bloom)
+class BloomModel(BloomModelTransform):
+
+    def __init__(self, **kwargs):
+        config = BloomConfig(**kwargs)
+        super().__init__(config)

modelscope/models/nlp/task_models/text_generation.py

@@ -51,12 +51,9 @@ class TaskModelForTextGeneration(SingleBackboneTaskModelBase, PreTrainedModel):
         return addict.Dict(outputs)
 
     def prepare_inputs_for_generation(self, input_ids, past=None, **kwargs):
-        token_type_ids = kwargs.get('token_type_ids', None)
         # only last token for inputs_ids if past is defined in kwargs
         if past:
             input_ids = input_ids[:, -1].unsqueeze(-1)
-            if token_type_ids is not None:
-                token_type_ids = token_type_ids[:, -1].unsqueeze(-1)
 
         attention_mask = kwargs.get('attention_mask', None)
         position_ids = kwargs.get('position_ids', None)
@@ -75,5 +72,8 @@ class TaskModelForTextGeneration(SingleBackboneTaskModelBase, PreTrainedModel):
             'use_cache': kwargs.get('use_cache'),
             'position_ids': position_ids,
             'attention_mask': attention_mask,
-            'token_type_ids': token_type_ids,
         }
+
+    def generate(self, inputs, *args, **kwargs):
+        input_ids = inputs['input_ids'] if isinstance(inputs, Dict) else inputs
+        return super().generate(input_ids, *args, **kwargs)

modelscope/pipelines/nlp/text_generation_pipeline.py

@@ -79,7 +79,7 @@ class TextGenerationPipeline(Pipeline):
             return self.model.generate(inputs, **forward_params)
 
     def sentence_piece(self, inputs) -> Dict[str, Tensor]:
-        return self.preprocessor.tokenizer.decode(inputs.tolist())[0]
+        return self.preprocessor.tokenizer.decode(inputs.tolist()[0])
 
     def postprocess(self, inputs: Dict[str, Tensor],
                     **postprocess_params) -> Dict[str, str]:

tests/pipelines/test_text_generation.py

@@ -182,6 +182,12 @@ class TextGenerationTest(unittest.TestCase, DemoCompatibilityCheck):
                 max_length=20,
                 repetition_penalty=0.5))
 
+    @unittest.skip("Langboat's checkpoint has not been uploaded to modelhub")
+    def test_bloom(self):
+        pipe = pipeline(
+            task=Tasks.text_generation, model='Langboat/bloom-1b4-zh')
+        print(pipe('中国的首都是'))
+
 
 if __name__ == '__main__':
     unittest.main()