altRoom.useGenParams : (KinkyDungeonMapIndex[MiniGameKinkyDungeonCheckpoint] || MiniGameKinkyDungeonCheckpoint)]; @@ -809,6 +812,7 @@ let KDBarricades = { lifetime: 9999, }, "BarricadeRobot": { minlevel: 4, filter: (enemy, x, y, checkpoint, type) => { return (enemy.Enemy.tags....
Optimizer state when using Adam: 4 bytes * 0.11B trainable params * 3 = 1.32GB Adding all of the above -> 9.51 GB ~10GB -> 1 A100 40GB GPU required 🤯. The reason for A100 40GB GPU is that the intermediate activations for long sequence lengths of 2048 and batch si...
针对这种小的错误,有一种梯度检验(Gradient checking)的方法,通过数值梯度检验,你能肯定确实是在正确地计算代价函数(Cost Function)的导数。 GC需要对params中的每一个参数进行check,也就是依次给每一个参数一个极小量。 overfitting: 就是训练误差Ein很小,但是实际的真实误差就可能很大,也就是模型的泛化能力很差(...
7 @@ export function setViewState(next: (...params: unknown[]) => unknown) { const path = state?.state?.file; if ( isMarkdownView && - fileViewTypeCache[path] && + fileViewTypeCache[path]?.viewType === FILE_VIEW_TYPE && !state.state.inlineEditor ) { const newState = { diff...
Optimizer state when using Adam: 4 bytes * 0.11B trainable params * 3 = 1.32GB Adding all of the above -> 9.51 GB ~10GB -> 1 A100 40GB GPU required 🤯. The reason for A100 40GB GPU is that the intermediate activations for long sequence lengths of 2048 and batch size of 4 fo...
Optimizer state when using Adam: 4 bytes * 0.11B trainable params * 3 = 1.32GB Adding all of the above -> 9.51 GB ~10GB -> 1 A100 40GB GPU required 🤯. The reason for A100 40GB GPU is that the intermediate activations for long sequence lengths of 2048 and batch size of ...