Question

我已经使用keras训练了许多字符级语言模型。当我第一次拟合模型时，可以使用它，但是当我保存模型然后尝试使用它时，会出现值错误：

ValueError: Error when checking input: expected lstm_1_input to have shape (3, 54) but got array with shape (3, 52)

为什么仅在加载模型时出现此错误，如何使用已保存的模型？

我试图在线找到该问题的解决方案，但大多数google结果似乎都与尺寸变化有关。在我看来，所有发生的变化是，保存的模型似乎期望一个热矢量，该热矢量比应有的长两个。

为清楚起见，共有52个字符，因此（3，52）应该正确。

这是我用来构建模型的代码：

model = Sequential()
model.add(LSTM(40, return_sequences=True, input_shape=(x_train.shape[1], x_train.shape[2])))
model.add(LSTM(40, input_shape=(x_train.shape[1], x_train.shape[2])))
model.add(Dense(vocab_size, activation='softmax'))
print(model.summary())
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=1000, verbose=2)

这是我的保存方式：

model.save('n3_Tokeniser.h5')

这是我的加载方式：

model = load_model('n3_Tokeniser.h5')

这是我尝试称呼它的方式：

def generate_seq(model, mapping, seq_length, seed_text, n_chars):
    in_text = seed_text
    for _ in range(n_chars):
        encoded = [mapping[char] for char in in_text]
        encoded = pad_sequences([encoded], maxlen=seq_length, truncating='pre')
        encoded = to_categorical(encoded, num_classes=len(mapping))
        yhat = model.predict_classes(encoded, verbose=0)
        out_char = ''
        for char, index in mapping.items():
            if index == yhat:
                out_char = char
                break
        in_text += char
    return in_text

这是完整的追溯：

Traceback (most recent call last):
  File "/Users/ade/PycharmProjects/Wbp/LSTM.py", line 263, in <module>
    print(generate_seq(model, chardict, pre_characters, '$$$$$$$$$$', 20))
  File "/Users/ade/PycharmProjects/Wbp/LSTM.py", line 250, in generate_seq
    yhat = model.predict_classes(encoded, verbose=0)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/engine/sequential.py", line 267, in predict_classes
    proba = self.predict(x, batch_size=batch_size, verbose=verbose)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/engine/training.py", line 1149, in predict
    x, _, _ = self._standardize_user_data(x)
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/engine/training.py", line 751, in _standardize_user_data
    exception_prefix='input')
  File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/engine/training_utils.py", line 138, in standardize_input_data
    str(data_shape))
ValueError: Error when checking input: expected lstm_1_input to have shape (3, 54) but got array with shape (3, 52)

为什么只有在加载我的keras模型时却出现“ ValueError：检查输入时出现错误：...”，而在我第一次拟合时却没有得到？

0 个答案: