OcclusionSensitivity callback issue - get stucks or index error

[druzkaya]

TF 2.1, tf-explain 0.2.0

Hello,

I'm using tf-explain (callbacks) on about 70.000 images, 56563, and two labels (0: 13%, 1: 87%), in order to explain class 0 classification. Whereas GradCAM works perfectly, I systematically have issues with OcclusionSensitivity.
With class_index=0, it gets stuck forever, with class_index=1 I get the following error message.

cb_gradcam = GradCAMCallback(
validation_data=(X_val, y_val),
class_index=1,
output_dir=log_dir)

cb_occlusion = OcclusionSensitivityCallback(
validation_data=(X_val, y_val),
class_index=1,
patch_size=4,
output_dir=log_dir)

model.fit(x=X_train_sc, y=y_train,
epochs=1,
batch_size=batch_size,
validation_split=0.2,
validation_freq=1,
use_multiprocessing=True,
callbacks=[tensorboard_callback, cb_occlusion],
)
--> with cb_gradcam I get good results in TensorBoard

Error for class_index=1 (and for class_index=0, just get stucks, no error message, but I have to kill the code) :

---

IndexError Traceback (most recent call last)
in
5 validation_freq=1,
6 use_multiprocessing=True,
----> 7 callbacks=[tensorboard_callback, cb_occlusion],
8
9 )

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
817 max_queue_size=max_queue_size,
818 workers=workers,
--> 819 use_multiprocessing=use_multiprocessing)
820
821 def evaluate(self,

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
395 total_epochs=1)
396 cbks.make_logs(model, epoch_logs, eval_result, ModeKeys.TEST,
--> 397 prefix='val_')
398
399 return model.history

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/contextlib.py in exit(self, type, value, traceback)
117 if type is None:
118 try:
--> 119 next(self.gen)
120 except StopIteration:
121 return False

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py in on_epoch(self, epoch, mode)
769 if mode == ModeKeys.TRAIN:
770 # Epochs only apply to fit.
--> 771 self.callbacks.on_epoch_end(epoch, epoch_logs)
772 self.progbar.on_epoch_end(epoch, epoch_logs)
773

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow_core/python/keras/callbacks.py in on_epoch_end(self, epoch, logs)
300 logs = logs or {}
301 for callback in self.callbacks:
--> 302 callback.on_epoch_end(epoch, logs)
303
304 def on_train_batch_begin(self, batch, logs=None):

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tf_explain/callbacks/occlusion_sensitivity.py in on_epoch_end(self, epoch, logs)
54 explainer = OcclusionSensitivity()
55 grid = explainer.explain(
---> 56 self.validation_data, self.model, self.class_index, self.patch_size
57 )
58

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tf_explain/core/occlusion_sensitivity.py in explain(self, validation_data, model, class_index, patch_size, colormap)
47 [
48 self.get_sensitivity_map(model, image, class_index, patch_size)
---> 49 for image in images
50 ]
51 )

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tf_explain/core/occlusion_sensitivity.py in (.0)
47 [
48 self.get_sensitivity_map(model, image, class_index, patch_size)
---> 49 for image in images
50 ]
51 )

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tf_explain/core/occlusion_sensitivity.py in get_sensitivity_map(self, model, image, class_index, patch_size)
96 predictions = model.predict(np.array(patches), batch_size=self.batch_size)
97 target_class_predictions = [
---> 98 prediction[class_index] for prediction in predictions
99 ]
100

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tf_explain/core/occlusion_sensitivity.py in (.0)
96 predictions = model.predict(np.array(patches), batch_size=self.batch_size)
97 target_class_predictions = [
---> 98 prediction[class_index] for prediction in predictions
99 ]
100

IndexError: index 1 is out of bounds for axis 0 with size 1

---

Any help would be much appreciated ! Thanks

[RaphaelMeudec]

@druzkaya I see you closed the issue, I'm still curious about what was going wrong?