Multi-output will only pass the first output to the score funuction

[frank-qcd-qk]

tf-keras-vis/tf_keras_vis/gradcam.py

Line 62 in ddd9513

loss_values = [loss(y) for y, loss in zip(outputs, losses)]

Say if I have an output of [tf.tensor , tf.tensor], after this line executed even I use my own scoring function, the obtained "output" is now only the first tf.tensor.

I don't think this is the expected behavior...

Sample model: https://github.com/duckietown/challenge-aido_LF-baseline-behavior-cloning/blob/master/duckieChallenger/frankModel.py

[bersbersbers]

Do you base this on experiments or code analysis? losses should have the same length as self.model.outputs, so this list comprehension should return more than one element:

tf-keras-vis/tf_keras_vis/gradcam.py

Line 51 in ddd9513

losses = self._get_losses_for_multiple_outputs(loss)

tf-keras-vis/tf_keras_vis/__init__.py

Lines 42 to 50 in b420516

	def _get_losses_for_multiple_outputs(self, loss):
	losses = listify(loss)
	if len(losses) == 1 and len(losses) < len(self.model.outputs):
	losses = losses * len(self.model.outputs)
	if len(losses) != len(self.model.outputs):
	raise ValueError(('The model has {} outputs, '
	'but the number of loss-functions you passed is {}.').format(
	len(self.model.outputs), len(losses)))
	return losses

Or what am I missing?

[frank-qcd-qk]

I did this base on an experiment...

But maybe I have misunderstood something that could also happen...

I am not sure this losses was working tho... I am using v0.6.0 if that helps.

[bersbersbers]

I did this base on an experiment...

In that case, a short reproducible example would be helpful, I'm pretty sure.

I am using v0.6.0 if that helps.

Note that this has not been released yet as far as I can see.

Also, you may want to look into this code to see what may be going wrong: 9ebe940, although much seems the same except for renamed variables:

tf-keras-vis/tf_keras_vis/gradcam.py

Line 69 in 9ebe940

scores = self._get_scores_for_multiple_outputs(score)

tf-keras-vis/tf_keras_vis/gradcam.py

Line 80 in 9ebe940

score_values = [score(y) for y, score in zip(outputs, scores)]

tf-keras-vis/tf_keras_vis/__init__.py

Lines 42 to 50 in 9ebe940

	def _get_scores_for_multiple_outputs(self, score):
	scores = listify(score)
	if len(scores) == 1 and len(scores) < len(self.model.outputs):
	scores = scores * len(self.model.outputs)
	if len(scores) != len(self.model.outputs):
	raise ValueError(('The model has {} outputs, '
	'but the number of score-functions you passed is {}.').format(
	len(self.model.outputs), len(scores)))
	return scores

[keisen]

@frank-qcd-qk , I'm so sorry for late reply.
@bersbersbers , Thank you for the detailed explanation!

So Was your problem solved?
If not, please let me know that. I will help you resolve it.
If resolved, please close this issue.

Thanks!

[ck37]

Would it be possible to show an example of using tf-keras-vis with a multi-output model? I'm trying to use it for a 3-output model (EfficientNet backbone) but am struggling with how to define the score functions, etc.