27 мая 2023 г. · A gradient norm is just the computed "norm" of a gradient function - which is essentially the magnitude.

27 мая 2023 г. · A gradient is basically a derivative. Norm means magnitude in this case. You are interested in the norm of the gradient because you don't want ...

27 мая 2023 г. · It's when you scale the gradient so that it's norm is within a threshold. You can think of it as if you step too far in 1 direction and it causes issues.

28 сент. 2023 г. · The gradient of 2Ax does not make sense since 2Ax is a function from R^n to R^m. The gradient is defined on scalar functions, from R^n to R.

1 нояб. 2020 г. · The gradient should be a vector, so out of the two, it must be aw. The magnitude of the gradient is |a|*||w||.

4 янв. 2021 г. · How do I choose the max value to use for global gradient norm clipping? The value must somehow depend on the number of parameters because ...

28 февр. 2020 г. · I see different ways to compute the l2 gradient norm. The difference is how they consider the biases. First way In the PyTorch codebase, ...

27 мая 2023 г. · Without any other context, "norm" is usually referring to the "L2-norm", aka euclidean distance. This should be intuitive at least for vectors.

28 апр. 2022 г. · I think of gradient clipping as a form of defensive programming. You first look at the gradients when everything runs well and trains well, This ...

25 мар. 2020 г. · I just came across the following proof that requires the gradient of g(x) = (1/2) (x^T A^T A x) / (x^Tx), the matrix 2-norm, ...