Keras, append to logs from callback

Question

I have a callback that computes a couple of additional metrics in on_epoch_end for validation data and every 10 epochs for test data.

I also have a CSVLogger callback that saves normal metrics to a log file.

Is there an easy way from my callback to add a column or two to the logs that gets properly written by CSVLogger?

Answer 1

You can insert your additional metrics into the dictionary logs.

from keras.callbacks import Callback  class ComputeMetrics(Callback):     def on_epoch_end(self, epoch, logs):         logs['val_metric'] = epoch ** 2  # replace it with your metrics         if (epoch + 1) % 10 == 0:             logs['test_metric'] = epoch ** 3  # same         else:             logs['test_metric'] = np.nan 

Just remember to place this callback before CSVLogger in your fit call. Callbacks that appear later in the list would receive a modified version of logs. For example,

model = Sequential([Dense(1, input_shape=(10,))]) model.compile(loss='mse', optimizer='adam') model.fit(np.random.rand(100, 10),           np.random.rand(100),           epochs=30,           validation_data=(np.random.rand(100, 10), np.random.rand(100)),           callbacks=[ComputeMetrics(), CSVLogger('1.log')]) 

Now if you take a look at the output log file, you'll see two additional columns test_metric and val_metric:

epoch,loss,test_metric,val_loss,val_metric 0,0.547923130989,nan,0.370979120433,0 1,0.525437340736,nan,0.35585285902,1 2,0.501358469725,nan,0.341958616376,4 3,0.479624577463,nan,0.329370084703,9 4,0.460121934414,nan,0.317930338383,16 5,0.440655426979,nan,0.307486981452,25 6,0.422990380526,nan,0.298160370588,36 7,0.406809270382,nan,0.289906248748,49 8,0.3912438941,nan,0.282540213466,64 9,0.377326357365,729,0.276457450986,81 10,0.364721306562,nan,0.271435074806,100 11,0.353612961769,nan,0.266939682364,121 12,0.343238875866,nan,0.263228923082,144 13,0.333940329552,nan,0.260326927304,169 14,0.325931007862,nan,0.25773427248,196 15,0.317790198028,nan,0.255648627281,225 16,0.310636150837,nan,0.25411529541,256 17,0.304091459513,nan,0.252928718328,289 18,0.298703012466,nan,0.252127869725,324 19,0.292693507671,6859,0.251701972485,361 20,0.287824733257,nan,0.251610517502,400 21,0.283586999774,nan,0.251790778637,441 22,0.27927801609,nan,0.252100949883,484 23,0.276239238977,nan,0.252632959485,529 24,0.273072380424,nan,0.253150621653,576 25,0.270296501517,nan,0.253555388451,625 26,0.268056542277,nan,0.254015884399,676 27,0.266158599854,nan,0.254496408701,729 28,0.264166412354,nan,0.254723013639,784 29,0.262506003976,24389,0.255338237286,841