尝试在Keras中使用HDF5数据集时出错

尝试使用包含keras的HDF5数据集时出现以下错误。似乎Sequential.fit（）在创建验证数据切片时遇到切片的关键字没有“停止”属性。我不知道这是HDF5数据集还是其他格式化问题。任何帮助，将不胜感激。尝试在Keras中使用HDF5数据集时出错

Traceback (most recent call last):
File "autoencoder.py", line 73, in module

validation_split=0.2)

File "/home/ben/.local/lib/python2.7/site-packages/keras/models.py", line 672, in fit

initial_epoch=initial_epoch)

File "/home/ben/.local/lib/python2.7/site-packages/keras/engine/training.py", line 1143, in fit

x, val_x = (slice_X(x, 0, split_at), slice_X(x, split_at))

File "/home/ben/.local/lib/python2.7/site-packages/keras/engine/training.py", line 301, in slice_X

return [x[start:stop] for x in X]

File "/home/ben/.local/lib/python2.7/site-packages/keras/utils/io_utils.py", line 71, in getitem

if key.stop + self.start <= self.end:

TypeError: unsupported operand type(s) for +: 'NoneType' and 'int'

training_input = HDF5Matrix("../../media/patches/data_rotated.h5", 'training_input_rotated') 
    training_target = HDF5Matrix("../../media/patches/data_rotated.h5", 'training_target_rotated') 

    # Model definition 
    autoencoder = Sequential() 

    autoencoder.add(Convolution2D(32, 3, 3, activation='relu', border_mode='same',input_shape=(64, 64, 3))) 
    autoencoder.add(MaxPooling2D((2, 2), border_mode='same')) 
    autoencoder.add(Convolution2D(64, 3, 3, activation='relu', border_mode='same')) 
    autoencoder.add(MaxPooling2D((2, 2), border_mode='same')) 
    autoencoder.add(Convolution2D(128, 3, 3, activation='relu', border_mode='same')) 
    autoencoder.add(Deconvolution2D(64, 3, 3, activation='relu', border_mode='same',output_shape=(None, 16, 16, 64),subsample=(2, 2))) 
    autoencoder.add(UpSampling2D((2, 2))) 
    autoencoder.add(Deconvolution2D(32, 3, 3, activation='relu', border_mode='same',output_shape=(None, 32, 32, 32),subsample=(2, 2))) 
    autoencoder.add(UpSampling2D((2, 2))) 
    autoencoder.add(Deconvolution2D(3, 3, 3, activation='sigmoid', border_mode='same',output_shape=(None, 64, 64, 3),subsample=(2, 2))) 
    autoencoder.compile(optimizer='adadelta', loss='binary_crossentropy') 
    autoencoder.summary() 

    # Callback configure 
    csv_logger = CSVLogger('../../runs/training_' + start_time + '.log') 
    prog_logger = ProgbarLogger() 
    checkpointer = ModelCheckpoint(filepath='../../runs/model_' + start_time + '.hdf5', verbose=1, save_best_only=False) 

    # Training call 
    history = autoencoder.fit(
        x=training_input, 
        y=training_target, 
        batch_size=256, 
        nb_epoch=1000, 
        verbose=2, 
        callbacks=[csv_logger, prog_logger, checkpointer], 
        validation_split=0.2)

来源

2017-01-25 Ben

Try + str（start_time） –

对不起，我不明白。我应该在哪里添加？ – Ben

在Csv记录器定义中。 –

我没有修复错误，但我在我的配合使用电话而不是validation_data的validation_split了周围。

来源

2017-01-26 18:26:33 Ben

尝试在Keras中使用HDF5数据集时出错

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