目前我正在学习聊bot编程的基础知识，对TensorFlow和Keras几乎没有经验。在编写程序时，我遇到了一个错误消息：AttributeError: module ‘keras.optimizers’ has no attribute ‘TFOptimizer’版本：TensorFlow 2.1.0：Keras 2.3.1：Python 3.7
import nltkfrom nltk.stem import WordNetLemmatizerlemmatizer = WordNetLemmatizer()import jsonimport pickleimport tensorflow from tensorflow import kerasfrom tensorflow.keras import layersfrom tensorflow.keras import optimizersfrom tensorflow.python.keras.optimizers import TFOptimizerimport numpy as npnp.array(object, dtype=object, copy=True, order='K', subok=False, ndmin=0)from keras.models import Sequential, Modelfrom keras.layers import Dense, Activation, Dropout, Lambdaimport tensorflow as tfphysical_devices = tf.config.list_physical_devices('GPU') tf.config.experimental.set_memory_growth(physical_devices[0], True)import randomwords=[]classes = []documents = []ignore_words = ['?', '!']data_file = open('intents.json' , encoding='utf-8').read()intents = json.loads(data_file)问题：
model = Sequential()model.add(Dense(128, input_shape=(len(train_x[0]),), activation='relu'))model.add(Dropout(0.5))model.add(Dense(64, activation='relu'))model.add(Dropout(0.5))model.add(Dense(len(train_y[0]), activation='softmax'))sgd = keras.optimizers.Adam(lr=0.01, decay=1e-6)model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy']) hist = model.fit(np.array(train_x), np.array(train_y), epochs=200, batch_size=5, verbose=1)model.save('chatbot_model.h5', hist)print("model created")错误消息：
AttributeError Traceback (most recent call last)<ipython-input-25-54920be00d53> in <module> 12 #fitting and saving the model 13 hist = model.fit(np.array(train_x), np.array(train_y), epochs=200, batch_size=5, verbose=1)---> 14 model.save('chatbot_model.h5', hist) 15 print("model created")~\anaconda3\envs\tensorflow\lib\site-packages\keras\engine\network.py in save(self, filepath, overwrite, include_optimizer) 1150 raise NotImplementedError 1151 from ..models import save_model-> 1152 save_model(self, filepath, overwrite, include_optimizer) 1153 1154 @saving.allow_write_to_gcs~\anaconda3\envs\tensorflow\lib\site-packages\keras\engine\saving.py in save_wrapper(obj, filepath, overwrite, *args, **kwargs) 447 os.remove(tmp_filepath) 448 else:--> 449 save_function(obj, filepath, overwrite, *args, **kwargs) 450 451 return save_wrapper~\anaconda3\envs\tensorflow\lib\site-packages\keras\engine\saving.py in save_model(model, filepath, overwrite, include_optimizer) 539 return 540 with H5Dict(filepath, mode='w') as h5dict:--> 541 _serialize_model(model, h5dict, include_optimizer) 542 elif hasattr(filepath, 'write') and callable(filepath.write): 543 # write as binary stream~\anaconda3\envs\tensorflow\lib\site-packages\keras\engine\saving.py in _serialize_model(model, h5dict, include_optimizer) 161 layer_group[name] = val 162 if include_optimizer and model.optimizer:--> 163 if isinstance(model.optimizer, optimizers.TFOptimizer): 164 warnings.warn( 165 'TensorFlow optimizers do not 'AttributeError: module 'keras.optimizers' has no attribute 'TFOptimizer'回答：
keras 和 tensorflow.keras 是Keras API的两种不同实现，因此不应混用。根据Keras API的创建者，用户应该在未来优先使用 tensorflow.keras 实现。
Keras多后端的新版本发布：2.3.0
https://github.com/keras-team/keras/releases/tag/2.3.0
- 首个支持TF 2的多后端Keras版本
- 继续支持Theano/CNTK
- 将是多后端Keras的最后一个主要版本
我们建议您将Keras代码切换到tf.keras。
