Datasets:
HenryAI
/
KerasCodeExamples.txt

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# Return a dict mapping metric names to current value
return {m.name: m.result() for m in self.metrics}
model = get_model()
model.compile(
optimizer=keras.optimizers.SGD(learning_rate=1e-2),
loss=\"sparse_categorical_crossentropy\",
metrics=[\"accuracy\"],
run_eagerly=True,
)
model.step_counter = 0
# We pass epochs=1 and steps_per_epoch=10 to only run 10 steps of training.
model.fit(x_train, y_train, epochs=1, batch_size=1024, verbose=0, steps_per_epoch=10)
----Start of step: 0
Max of dl_dw[0]: 0.0236
Min of dl_dw[0]: -0.0198
Mean of dl_dw[0]: 0.0001
-
Max of d2l_dw2[0]: 2.6148
Min of d2l_dw2[0]: -1.8798
Mean of d2l_dw2[0]: 0.0401
----Start of step: 1
Max of dl_dw[0]: 0.0611
Min of dl_dw[0]: -0.0233
Mean of dl_dw[0]: 0.0009
-
Max of d2l_dw2[0]: 8.3185
Min of d2l_dw2[0]: -4.0696
Mean of d2l_dw2[0]: 0.1708
----Start of step: 2
Max of dl_dw[0]: 0.0528
Min of dl_dw[0]: -0.0200
Mean of dl_dw[0]: 0.0010
-
Max of d2l_dw2[0]: 3.4744
Min of d2l_dw2[0]: -3.1926
Mean of d2l_dw2[0]: 0.0559
----Start of step: 3
Max of dl_dw[0]: 0.0983
Min of dl_dw[0]: -0.0174
Mean of dl_dw[0]: 0.0014
-
Max of d2l_dw2[0]: 2.2682
Min of d2l_dw2[0]: -0.7935
Mean of d2l_dw2[0]: 0.0253
----Start of step: 4
Max of dl_dw[0]: 0.0732
Min of dl_dw[0]: -0.0125
Mean of dl_dw[0]: 0.0009
-
Max of d2l_dw2[0]: 5.1099
Min of d2l_dw2[0]: -2.4236
Mean of d2l_dw2[0]: 0.0860
----Start of step: 5
Max of dl_dw[0]: 0.1309
Min of dl_dw[0]: -0.0103
Mean of dl_dw[0]: 0.0007
-
Max of d2l_dw2[0]: 5.1275
Min of d2l_dw2[0]: -0.6684
Mean of d2l_dw2[0]: 0.0349
----Start of step: 6
Max of dl_dw[0]: 0.0484
Min of dl_dw[0]: -0.0128
Mean of dl_dw[0]: 0.0001
-
Max of d2l_dw2[0]: 5.3465
Min of d2l_dw2[0]: -0.2145
Mean of d2l_dw2[0]: 0.0618
----Start of step: 7
Max of dl_dw[0]: 0.0049
Min of dl_dw[0]: -0.0093
Mean of dl_dw[0]: -0.0001
-
Max of d2l_dw2[0]: 0.2465
Min of d2l_dw2[0]: -0.0313
Mean of d2l_dw2[0]: 0.0075
----Start of step: 8
Max of dl_dw[0]: 0.0050
Min of dl_dw[0]: -0.0120
Mean of dl_dw[0]: -0.0001
-
Max of d2l_dw2[0]: 0.1978
Min of d2l_dw2[0]: -0.0291
Mean of d2l_dw2[0]: 0.0063
----Start of step: 9
Max of dl_dw[0]: 0.0050
Min of dl_dw[0]: -0.0125
Mean of dl_dw[0]: -0.0001
-
Max of d2l_dw2[0]: 0.1594
Min of d2l_dw2[0]: -0.0238
Mean of d2l_dw2[0]: 0.0055
<tensorflow.python.keras.callbacks.History at 0x17f65f410>
What did we learn?
The first order and second order gradients can have values that differ by orders of magnitudes.
Sometimes, they may not even have the same sign.