conda create -p D:/AworkStation/Anaconda3/envs/gpy38torch python=3.8 【不知为何,管理员的windows身份了,仍然需要使用管理员身份运行】 pip install pandas transformers scipy ipykernel pip install torch==1.13.0+cu116 --extra-index-url https://download.pytorch.org/whl/cu116 python -m ipykernel...
安装mmcv:(详情可见mmcv官方安装链接) pip install mmcv-full -fhttps://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html 例如:pip install mmcv-full -fhttps://download.openmmlab.com/mmcv/dist/cu102/torch1.11.0/index.html 安装mmdet: 根据mmdet安装文档链接查找适配的mmdet版本...
pe =torch.zeros(max_len, d_model).float() pe.require_grad = False position = torch.arange(0, max_len).float().unsqueeze(1) div_term = (torch.arange(0, d_model, 2).float() * -(math.log(10000.0) / d_model)).exp() pe[:, 0::2] = torch.sin(position * div_term) pe[:,...
我们以ResNet50为例,代码如下: import torchvisionimport torchfrom torch.autograd import Variableimport onnxprint(torch.__version__) input_name = ['input']output_name = ['output']input = Variable(torch.randn(1, 3, 224, 224)).cuda()model = torchvision.models.resnet50(pretrained=True).cuda(...
在Real Time Object Detection榜单上，没看到transformer
import torch import torch.nn as nn # 定义模型 class LinearRegression(nn.Module): def __init__(self, input_size, output_size): super(LinearRegression, self).__init__() self.linear = nn.Linear(input_size, output_size) def forward(self, x): return self.linear(x) # 初始化模型 model...
Python version 3.8.11 and R version 4.0.5 were used for downstream analysis with the following packages: torch (version 1.7.1), scanpy (version 1.7.1), Seurat (version 4.1.0), ggplot2 (3.3.5), ComplexHeatmap (2.10.0), gam (1.22), and their dependent packages. Attention embedding prep...
pip install mmcv-full==1.2.4-f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html 两个注意的点,看上面的链接。 A:"cu101",这个指的是cuda的版本,我这边是10.1,所以写101 # 查找cuda的版本方法 cat /usr/local/cuda/version.txt ...
"layernorm_epsilon":1e-05,"max_sequence_length":2048,"model_type":"chatglm","num_attention_heads":32,"num_layers":28,"position_encoding_2d":true,"quantization_bit":4,"quantization_embeddings":false,"torch_dtype":"float16","transformers_version":"4.27.1","use_cache":true,"vocab_size...
@staticmethoddefgenerate_square_subsequent_mask(sz:int)->Tensor:r"""用来生成步骤4中attention mask."""returntorch.triu(torch.full((sz,sz),float('-inf')),diagonal=1) 关键参数说明 batch_first:默认False,在pytorch中,rnn、Transformer层的输入维度一般是(seq, batch, feature),第一个维度表示seq的长度...