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Hi,
As far as I understand, TensorFI is capable of injecting faults at the level of nodes but not in the nodes rather the output of one node acts as the input to the other nodes.
If we want to study the effects of bit flips in the weights of a model, how can we achieve it with TensorFI?
Is there a way to inject the bit flips inside the 'weight node'?
The text was updated successfully, but these errors were encountered:
Hi @abhishek-t-naive thanks for your question - we consider injection in the weights in our latest version of the tool: TensorFI2 which works with TensorFlow 2 and Python 3.
I am trying to work with a network implemented with TensorFlow 1 and Python 2.7. Do you suggest any method by which injection in weights could be done with TensorFlow 1 or TensorFlow 2 back-compatible?
Hi,
As far as I understand, TensorFI is capable of injecting faults at the level of nodes but not in the nodes rather the output of one node acts as the input to the other nodes.
If we want to study the effects of bit flips in the weights of a model, how can we achieve it with TensorFI?
Is there a way to inject the bit flips inside the 'weight node'?
The text was updated successfully, but these errors were encountered: