为了不重复选取，sampler会将每个样本都返回，这样就失去weight参数的意义了。
help='do not optimize, reload weights and render out render_poses path')# 渲染测试集而不是render_poses路径parser.add_argument("--render_test",action='store_true',help='render the test set instead of render_poses path')# 下采样因子以加快渲染速度,设置为 4 或 8 用于快速预览parser.add_argu...
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We find that these problems are often due to the use of weight clipping in WGAN to enforce a Lipschitz constraint on the critic, which can lead to undesired behavior. We propose an alternative to clipping weights: penalize the norm of gradient of the critic with respect to its input. Our ...
task.base->not_done.notify_all(); } } else { // If it's a task initiated from this thread, decrease the counter, but // don't do anything - loop condition will do all checks for us next. if (base_owner == worker_device) { ...
See this excellent blog post on why using weight decay instead of L2-regularization makes a difference for Adam. Both Adam and AdamW work well with the 1Cycle policy described above. There are also a few not-yet-native optimizers that have received a lot of attention recently, most notably ...
(self, weights): assert self.use_viewdirs, "Not implemented if use_viewdirs=False" # Load pts_linears for i in range(self.D): idx_pts_linears = 2 * i self.pts_linears[i].weight.data = torch.from_numpy(np.transpose(weights[idx_pts_linears])) self.pts_linears[i].bias.data ...
pytorch是python语言下的深度学习框架, 它可以帮助你实现深度学习的算法, 所以它可以做的就是深度学习可以...
For the models below, the model code and weight porting from Tensorflow or MXNet Gluon to Pytorch was done by myself. There are weights/models ported by others included in this repository, they are not listed below. ModelPrec@1 (Err)Prec@5 (Err)Param #Image ScalingImage Size ...
🐛 Describe the bug I've noticed a significant performance slowdown in torch 2.0 when enabling determinism. Here is a simple example using the diffusers library: def set_deterministic(mode=True): import torch import os torch.backends.cudn...