如何使用 TensorBoard write_grads 函数？

Question

i am using keras to train my sequential model with 3 layers and want to visualize gradient histograms in TensorBoard. For that there is the function "write_grads" in keras.callbacks.Tensorboard which should work if you define histogram_freq greater than 0 ( keras docu ). What i did:

### tensorboard call
callback_tb = keras.callbacks.TensorBoard(log_dir="logs/"+ name, write_graph = True, write_grads = True, histogram_freq=10 )
### some other callbacks
reduce_lr = keras.callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=10, min_lr=0.001, verbose = 1)
early = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=5, patience=10, verbose=1, mode='auto')
checkpointer = keras.callbacks.ModelCheckpoint(filepath='tmp/'+name+'.hdf5', verbose=1, save_best_only=True)

### model fit
model.fit(
        X_train, y_train,
        batch_size=1, nb_epoch=epochs, validation_split=0.05, verbose = 1,class_weight ={0: 1, 1: 0.5}, callbacks = [callback_tb, reduce_lr, early, checkpointer])

I have this model configuartion:

model = Sequential()
layers = [1, 100, 100, 100, 1]

model.add(GRU(
        layers[1],
        #batch_size = 209,
        input_shape=(sequence_length, anzahl_features),
        return_sequences=True))
model.add(Dropout(dropout_1))
model.add(LSTM(
        layers[2],
        #batch_size = 209,
        return_sequences=True))
model.add(Dropout(dropout_2))
model.add(GRU(
        layers[3],
        #batch_size = 209,
        return_sequences=False))
model.add(Dropout(dropout_3))
model.add(Dense(
         layers[4]))
model.add(Activation('sigmoid'))

print(model.summary())

And the error message that i get is the following one:

TypeError: init () got an unexpected keyword argument 'write_grads'

Is there something wrong with my configuartion? Can i use this model and get the gradient histograms? Or are those histograms just available for a certain type of model?

Answer 1

You need to upgrade Keras to the latest release (2.0.5). Previous versions do not support the write_grads argument.

pip install keras --upgrade

Answer 2

write_grads seems to be depecrated. Here it is not among the parameters fo the callbacks, and on githubs there is a request to un-deprecate it.