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QUESTION
I am trying to implement grad-cam for a tensorflow 2.0 model (created using the keras-api), but the gradients returned from the tape are always None.
I am following the example given on https://keras.io/examples/vision/grad_cam/.
My model is fairly simple, but I swapped it out for the builtin Xception model provided by tf.keras.applications in order to debug (no difference in behavior, so the problem must be with my code).
...ANSWER
Answered 2022-Mar-09 at 14:22Like @AloneTogether mentionned, the result of argmax
is not differentiable, thus the None result after applying tape.gradients(...)
is normal, since no gradient can be computed.
While the result of argmax
cannot be differentiated, it can be used to select the correct activation in the following way:
QUESTION
My env is created by pycharm, it has the followings packages: tensorflow==1.13.0rc1, CUDA = 11 andcorresponding cudn.but run https://github.com/keras-team/keras-io/blob/master/examples/nlp/semantic_similarity_with_bert.py from 1 to 269 line,print(f"Strategy: {strategy}") model.summary() After execution, the following error is reported:
...ANSWER
Answered 2021-Sep-06 at 03:34Tensorflow 2.6.0 works
QUESTION
I am running the following code. I am trying to display the probability of the predicted label next to the prediction but I have a hard time trying in doing so.
...ANSWER
Answered 2021-Jun-20 at 16:43I did not run the code, but I beleive preds
variable will be having all the probabilities.
For a particular input that you are trying to predict, if you want to see the maximum prediction value, you can do max(pred)
.
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