安装 pytorch

查看Cuda版本

nvidia-smi

+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 531.88                 Driver Version: 531.88       CUDA Version: 12.1     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                      TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf            Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 3050 4...  WDDM | 00000000:01:00.0 Off |                  N/A |
| N/A   40C    P0                8W /  N/A|      0MiB /  4096MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|  No running processes found                                                           |
+---------------------------------------------------------------------------------------+

添加镜像源

conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/

# 查看渠道列表
conda config --show channels

# pip3 安装pytorch
pip3 install pytorch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 -i https://pypi.tuna.tsinghua.edu.cn/simple

pytorch API

• torch.cat 拼接张量
  • 维度
    • 0：按行拼接
    • 1：按列拼接

>>> x = torch.randn(2, 3)
>>> x
tensor([[ 0.6580, -1.0969, -0.4614],
        [-0.1034, -0.5790,  0.1497]])
>>> torch.cat((x, x, x), 0)
tensor([[ 0.6580, -1.0969, -0.4614],
        [-0.1034, -0.5790,  0.1497],
        [ 0.6580, -1.0969, -0.4614],
        [-0.1034, -0.5790,  0.1497],
        [ 0.6580, -1.0969, -0.4614],
        [-0.1034, -0.5790,  0.1497]])
>>> torch.cat((x, x, x), 1)
tensor([[ 0.6580, -1.0969, -0.4614,  0.6580, -1.0969, -0.4614,  0.6580,
         -1.0969, -0.4614],
        [-0.1034, -0.5790,  0.1497, -0.1034, -0.5790,  0.1497, -0.1034,
         -0.5790,  0.1497]])