def add_noise_to_inputs()

in captum/attr/_core/noise_tunnel.py [0:0]

• 19 lines of code
• 4 McCabe index (conditional complexity)

        def add_noise_to_inputs(nt_samples_partition: int) -> Tuple[Tensor, ...]:
            if isinstance(stdevs, tuple):
                assert len(stdevs) == len(inputs), (
                    "The number of input tensors "
                    "in {} must be equal to the number of stdevs values {}".format(
                        len(inputs), len(stdevs)
                    )
                )
            else:
                assert isinstance(
                    stdevs, float
                ), "stdevs must be type float. " "Given: {}".format(type(stdevs))
                stdevs_ = (stdevs,) * len(inputs)
            return tuple(
                add_noise_to_input(input, stdev, nt_samples_partition).requires_grad_()
                if self.is_gradient_method
                else add_noise_to_input(input, stdev, nt_samples_partition)
                for (input, stdev) in zip(inputs, stdevs_)
            )