你的代码片段from timm.models.layers import droppath正确地指出了如何从timm库的models.layers模块中导入droppath功能或类。timm(PyTorch Image Models)是一个流行的库,它提供了许多预训练的图像模型,并且这些模型往往基于改进或优化的架构。 droppath的作用: 在timm库中,droppath通常是一个用于在训练过程中随机丢弃...
self.drop_path = DropPath(drop_path) if drop_path > 0. else nn.Identity() self.norm2 = norm_layer(dim) mlp_hidden_dim = int(dim * mlp_ratio) self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop) def forward(self, x): x = x + s...
import torch import torch.nn as nn import torch.nn.functional as F from torch import Tensor from timm.models.layers import DropPath, Mlp from .position_embedding import build_position_encoding def remap_uv(feat: Tensor, uv_coord: Tensor) -> Tensor: """ args: feat; [N, C, H, W] uv...
Can you provide a call stack or anything to help me figure out where you're running into this issue. The title doesn't help. I did just change the name, but the model unit tests pass and I checked it multiple times. Are you sure you have the whole code checked out in sync?
https://github.com/nickd16/Diffusion-Models-from-Scratch How it works -> The forward and Reverse Process Image from [2] Understand Deep Learning by Simon J.D. Prince Diffusion process包括一个forward process和reverse process。Forward process是基于一个noise schedule的预先确定的马尔科夫链(predetermine...