使用烧瓶部署ml模型时发生名称错误

Question

当我在jupyter笔记本中运行该代码时，它将正确执行。

import numpy as np
import pandas as pd
import pickle
import json
import requests

df=pd.read_csv('ner_dataset.csv',encoding = "ISO-8859-1")

class SentenceGetter(object):
    def __init__(self, df):
        self.n_sent = 1
        self.df = df
        self.empty = False
        agg_func = lambda s: [(w, t) for w,t in zip(s["Word"].values.tolist(),
                                                        s["Tag"].values.tolist())]
        self.grouped = self.df.groupby("Sentence #").apply(agg_func)
        self.sentences = [s for s in self.grouped]

def get_next(self):
        try:
            s = self.grouped["Sentence: {}".format(self.n_sent)]
            self.n_sent += 1
            return s
        except:
            return None

 getter = SentenceGetter(df)

        sentence = getter.sentences

        words = list(set(df["Word"].values))
        words.append("ENDPAD")
        n_words=len(words)
        print(n_words)
        tags = list(set(df["Tag"].values))
        tag=len(tags)
        print(tag)
        word2idx = {w: i for i, w in enumerate(words)}
        tag2idx = {t: i for i, t in enumerate(tags)}

       from  tensorflow.keras.preprocessing.sequence import pad_sequences
         X = [[word2idx[w[0]] for w in s] for s in sentence]
          X = pad_sequences(maxlen=140, sequences=X, padding="post",value=n_words - 1)
            y = [[tag2idx[w[1]] for w in s] for s in sentence]