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Prevent none value in gradients when some of the inputs have not impact to the target #987

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Prevent none value in gradients when some of the inputs have not impact to the target #987

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9eef9c4
Prevent none gradient when there is input has not impact to the traget
badcount Dec 5, 2023
c9f653f
get shape from x based on x's type
badcount Dec 5, 2023
408f12d
Change to only fix none gradient when x is list
badcount Dec 6, 2023
8dd5883
fix comment and change to use x[idx] instead of x[0]
badcount Dec 6, 2023
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11 changes: 10 additions & 1 deletion alibi/explainers/integrated_gradients.py
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Original file line number Diff line number Diff line change
Expand Up @@ -400,6 +400,11 @@ def _gradients_input(model: Union[tf.keras.models.Model],

grads = tape.gradient(preds, x)

# If certain inputs don't impact the target, the gradient is None, but we need to return a tensor
if isinstance(x, list):
for idx, grad in enumerate(grads):
if grad is None:
grads[idx] = tf.convert_to_tensor(np.zeros(x[idx].shape), dtype=x[idx].dtype)
return grads


Expand Down Expand Up @@ -497,7 +502,11 @@ def wrapper(*args, **kwargs):
grads = tape.gradient(preds, layer.inp)
else:
grads = tape.gradient(preds, layer.result)

# If certain inputs don't impact the target, the gradient is None, but we need to return a tensor
if isinstance(x, list):
for idx, grad in enumerate(grads):
if grad is None:
grads[idx] = tf.convert_to_tensor(np.zeros(x[idx].shape), dtype=x[idx].dtype)
delattr(layer, 'inp')
delattr(layer, 'result')
layer.call = orig_call
Expand Down