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import spacy
import pandas as pd
def inference(model: spacy, texts: list, batch_size: int=8):
"""
To perform batch inferencing
Parameters:
model: type of model
texts: input text example
batch_size: batch size of the inference
Returns:
data: pandas.DataFrame of the output from inference
"""
docs = model.pipe(texts,batch_size=batch_size)
records = []
for no, doc in enumerate(docs):
if len(doc.ents)>0:
records.append([{'id':no+1,'text':doc.text,'span': entity.text,
'entity': entity.label_, 'start': entity.start, 'end': entity.end}
for entity in doc.ents])
else:
records.append([{'id':no+1,'text':doc.text,'span': None,
'entity': None, 'start':None, 'end': None}])
data = pd.DataFrame.from_dict(sum(records,[])).set_index(['text','id'])
return data
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