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[英]How to solve “ NameError: name 'model' is not defined ” error?
[英]How can I solve this error? NameError: name ‘model’ is not defined
當我嘗試輸入文本以進行預測時,執行給我“NameError: name 'model' is not defined”
def evaluate_mode(Xtrain, ytrain, Xtest, ytest):
scores = list()
n_repeats = 2
n_words = Xtest.shape[1]
for i in range(n_repeats):
# define network
model = Sequential()
model.add(Dense(50, input_shape=(n_words,), activation='relu'))
model.add(Dense(1, activation='sigmoid'))
# compile network
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
# fit network
model.fit(Xtrain, ytrain, epochs=10, verbose=2)
# evaluate
loss, acc = model.evaluate(Xtest, ytest, verbose=0)
scores.append(acc)
print('%d accuracy: %s' % ((i+1), acc))
return scores
def prepare_data(train_docs, test_docs, mode):
# create the tokenizer
tokenizer = Tokenizer()
# fit the tokenizer on the documents
tokenizer.fit_on_texts(train_docs)
# encode training data set
Xtrain = tokenizer.texts_to_matrix(train_docs, mode=mode)
# encode testing data set
Xtest = tokenizer.texts_to_matrix(test_docs, mode=mode)
return Xtrain, Xtest
def predict_sentiment(review, vocab, tokenizer, model):
# clean
tokens = clean_doc(review)
# filter by vocab
tokens = [w for w in tokens if w in vocab]
# convert to line
line = ' '.join(tokens)
# encode
encoded = tokenizer.texts_to_matrix([line], mode='freq')
# prediction
yhat = model.predict(encoded, verbose=0)
return round(yhat[0,0])
如果在evaluate_mode()
中evaluate_mode()
訓練過程,則模型是局部變量,不能與predict_sentiment()
共享。 您應該讓evaluate_mode()
返回model
並讓predict_sentiment()
將其作為第四個參數。
在evaluate_mode
函數中,您不會在不返回模型的情況下返回模型,因此會出現這種錯誤。在predict_statement 中返回下一個預測的模型。
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