datagen = ImageDataGenerator(
featurewise_center=False, # set input mean to 0 over the dataset
samplewise_center=False, # set each sample mean to 0
featurewise_std_normalization=False, # divide inputs by std of the dataset
samplewise_std_normalization=False, # divide each input by its std
zca_whitening=False, # apply ZCA whitening
rotation_range=10, # randomly rotate images in the range (degrees, 0 to 180)
zoom_range = 0.1, # Randomly zoom image
width_shift_range=0.1, # randomly shift images horizontally (fraction of total width)
height_shift_range=0.1, # randomly shift images vertically (fraction of total height)
horizontal_flip=False, # randomly flip images
vertical_flip=False) # randomly flip images
datagen.fit（X_train）
history = model.fit_generator(datagen.flow(X_train,Y_train,batch_size=batch_size,),
epochs=epochs,validation_data=(X_val,Y_val),
verbose=2,steps_per_epoch=X_train.shape[0] // batch_size,
callbacks= [learning_rate_reduction])
[InternalError：Blas GEMM启动失败：a.shape =（86，3136），b.shape =（3136，256），m = 86，n = 256，k = 3136[[node density_1 / MatMul（在c：\ users \ shahj \ appdata \ local \ programs \ python \ python35 \ lib \ site-packages \ tensorflow_core \ python \ framework \ ops.py：1751定义）]] [操作：__ inference_keras_scratch_graph_1528 ]
函数调用堆栈：keras_scratch_graph