Keras Tensorboard callback not writing images -


i trying visualize weights of keras model tensorboard. here model using:

model = sequential([     conv2d(filters=32, kernel_size=(3,3), padding="same", activation='relu', input_shape=(40,40,3)),     maxpooling2d(pool_size=(2, 2)),     conv2d(filters=64, kernel_size=(5,5), padding="same", activation='relu'),     maxpooling2d(pool_size=(2, 2)),     flatten(),     dense(1024, activation='relu'),     dropout(0.5),     dense(43, activation='softmax'), ]) model.compile(optimizer='sgd',               loss='categorical_crossentropy',               metrics=['accuracy']) 

and training call:

model.fit_generator(     ...     callbacks = [         modelcheckpoint('models/gtsrb1-{epoch}.hdf5', verbose=1, save_best_only = true),         tensorboard(log_dir='tblogs/', write_graph=true, write_grads=true, write_images=true),         earlystopping(patience=5, verbose=1),     ],) 

however, when start tensorboard, get:

tensorboard images

scalars , graphs looks okay not problem of wrong logdir. doing wrong here?

you need add histogram_freq=x, x should different zero, writing of images enabled.

but if this, might still fail, depending on version of keras (see https://github.com/fchollet/keras/issues/6096)


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