我正在使用keras并尝试使用tensorboard绘制日志。下面您可以找到我得到的错误,以及我正在使用的软件包版本列表。我不能理解它给我的错误是“顺序”对象没有属性“获取分布策略”
包装: Keras 2.3.1 Keras应用程序1.0.8 Keras预处理1.1.0 张力板2.1.0 tensorflow 2.1.0 张量流估计器2.1.0
型号:
model = Sequential()
model.add(Embedding(MAX_NB_WORDS, EMBEDDING_DIM, input_shape=(X.shape[1],)))
model.add(GlobalAveragePooling1D())
#model.add(Dense(10, activation='sigmoid'))
model.add(Dense(len(CATEGORIES), activation='softmax'))
model.summary()
#opt = 'adam' # Here we can choose a certain optimizer for our model
opt = 'rmsprop'
model.compile(loss='categorical_crossentropy', optimizer=opt, metrics=['accuracy']) # Here we choose the loss function, input our optimizer choice, and set our metrics.
# Create a TensorBoard instance with the path to the logs directory
tensorboard = TensorBoard(log_dir='logs/{}'.format(time()),
histogram_freq = 1,
embeddings_freq = 1,
embeddings_data = X)
history = model.fit(X, Y, epochs=epochs, batch_size=batch_size, validation_split=0.1, callbacks=[tensorboard])
错误:
C:\Users\Bruno\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\callbacks\tensorboard_v2.py:102: UserWarning: The TensorBoard callback does not support embeddings display when using TensorFlow 2.0. Embeddings-related arguments are ignored.
warnings.warn('The TensorBoard callback does not support '
C:\Users\Bruno\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\framework\indexed_slices.py:433: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
Train on 1123 samples, validate on 125 samples
Traceback (most recent call last):
File ".\NN_Training.py", line 128, in <module>
history = model.fit(X, Y, epochs=epochs, batch_size=batch_size, validation_split=0.1, callbacks=[tensorboard]) # Feed in the train
set for X and y and run the model!!!
File "C:\Users\Bruno\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\engine\training.py", line 1239, in fit
validation_freq=validation_freq)
File "C:\Users\Bruno\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\engine\training_arrays.py", line 119, in fit_loop
callbacks.set_model(callback_model)
File "C:\Users\Bruno\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\callbacks\callbacks.py", line 68, in set_model
callback.set_model(model)
File "C:\Users\Bruno\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\callbacks\tensorboard_v2.py", line 116, in set_model
super(TensorBoard, self).set_model(model)
File "C:\Users\Bruno\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\callbacks.py", line 1532, in
set_model
self.log_dir, self.model._get_distribution_strategy()) # pylint: disable=protected-access
AttributeError: 'Sequential' object has no attribute '_get_distribution_strategy'```
您的python环境似乎混合了来自
keras
和tensorflow.keras
的导入。试着像这样使用顺序模块:或者将导入内容更改为类似的内容
…等等
您正在
keras
和tf.keras
之间混合导入,它们不是同一个库,不支持这样做您应该从其中一个库
keras
或tf.keras
进行所有导入相关问题 更多 >
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