In Chapter3 the third section “Finetune a model with the Traniner API or Keras”, Tensorflow application:
when we want to predict the exact labels for our evaluation dataset, the guide says
preds = model.predict(tf_validation_dataset)["logits"]
class_preds = np.argmax(preds, axis=1)
print(preds.shape, class_preds.shape)
I think it should add softmax function to the predictions other than using the argmax directly. Am I right? The same question about the code in pytorch code as well