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Merge pull request #676 from slin000111/master

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fix embedding and inference device in faq question answering pipeline
This commit is contained in:
wenmeng zhou
2023-12-19 21:44:43 +08:00
committed by GitHub
parent 71ed5e7598 262e0d6df0
commit c12323572a
2 changed files with 5 additions and 0 deletions
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2
modelscope/models/nlp/structbert/faq_question_answering.py
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@@ -375,6 +375,8 @@ class ProtoNet(nn.Module):
input_ids = torch.IntTensor(input_ids)
if not isinstance(input_mask, Tensor):
input_mask = torch.IntTensor(input_mask)
input_ids = input_ids.to(self.bert.device)
input_mask = input_mask.to(self.bert.device)
rst = self.bert(input_ids, input_mask)
last_hidden_states = rst.last_hidden_state
if len(input_mask.shape) == 2:

3
modelscope/pipelines/nlp/faq_question_answering_pipeline.py
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@@ -50,6 +50,9 @@ class FaqQuestionAnsweringPipeline(Pipeline):
return pipeline_parameters, pipeline_parameters, pipeline_parameters
def get_sentence_embedding(self, inputs, max_len=None):
if (self.model or (self.has_multiple_models and self.models[0])):
if not self._model_prepare:
self.prepare_model()
inputs = self.preprocessor.batch_encode(inputs, max_length=max_len)
sentence_vecs = self.model.forward_sentence_embedding(inputs)
sentence_vecs = sentence_vecs.detach().tolist()