(new_env) D:\Miniconda3\envs\new_env>conda clean --all

There are no unused tarball(s) to remove.

There are no index cache(s) to remove.

There are no unused package(s) to remove.

There are no tempfile(s) to remove.

There are no logfile(s) to remove.

(new_env) D:\Miniconda3\envs\new_env>conda create -n new_env python=3.10

WARNING: A conda environment already exists at 'D:\Miniconda3\envs\new_env'

Remove existing environment (y/[n])? y

Channels:

defaults

Platform: win-64

Collecting package metadata (repodata.json): done

Solving environment: done

Package Plan

environment location: D:\Miniconda3\envs\new_env

added / updated specs:

python=3.10

The following packages will be downloaded:

package | build

---------------------------|-----------------

vc-14.40 | haa95532_2 10 KB

Total: 10 KB

The following NEW packages will be INSTALLED:

bzip2 pkgs/main/win-64::bzip2-1.0.8-h2bbff1b_6

ca-certificates pkgs/main/win-64::ca-certificates-2024.11.26-haa95532_0

libffi pkgs/main/win-64::libffi-3.4.4-hd77b12b_1

openssl pkgs/main/win-64::openssl-3.0.15-h827c3e9_0

pip pkgs/main/win-64::pip-24.2-py310haa95532_0

python pkgs/main/win-64::python-3.10.15-h4607a30_1

setuptools pkgs/main/win-64::setuptools-75.1.0-py310haa95532_0

sqlite pkgs/main/win-64::sqlite-3.45.3-h2bbff1b_0

tk pkgs/main/win-64::tk-8.6.14-h0416ee5_0

tzdata pkgs/main/noarch::tzdata-2024b-h04d1e81_0

vc pkgs/main/win-64::vc-14.40-haa95532_2

vs2015_runtime pkgs/main/win-64::vs2015_runtime-14.42.34433-h9531ae6_2

wheel pkgs/main/win-64::wheel-0.44.0-py310haa95532_0

xz pkgs/main/win-64::xz-5.4.6-h8cc25b3_1

zlib pkgs/main/win-64::zlib-1.2.13-h8cc25b3_1

Proceed ([y]/n)? y

Downloading and Extracting Packages:

Preparing transaction: done

Verifying transaction: done

Executing transaction: done

To activate this environment, use

$ conda activate new_env

To deactivate an active environment, use

$ conda deactivate

(new_env) D:\Miniconda3\envs\new_env>conda activate new_env

(new_env) D:\Miniconda3\envs\new_env>conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

Channels:

pytorch
nvidia
defaults

Platform: win-64

Collecting package metadata (repodata.json): | Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'SSLEOFError(8, '[SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1007)')': /pkgs/r/win-64/repodata.json.zst

done

Solving environment: done

Package Plan

environment location: D:\Miniconda3\envs\new_env

added / updated specs:

pytorch
pytorch-cuda=11.8
torchaudio
torchvision

The following packages will be downloaded:

package | build

---------------------------|-----------------

blas-1.0 | mkl 6 KB

brotli-python-1.0.9 | py310hd77b12b_8 346 KB

certifi-2024.8.30 | py310haa95532_0 163 KB

charset-normalizer-3.3.2 | pyhd3eb1b0_0 44 KB

cuda-cccl-12.6.77 | 0 16 KB nvidia

cuda-cccl_win-64-12.6.77 | 0 1.0 MB nvidia

cuda-cudart-11.8.89 | 0 1.4 MB nvidia

cuda-cudart-dev-11.8.89 | 0 723 KB nvidia

cuda-cupti-11.8.87 | 0 11.5 MB nvidia

cuda-libraries-11.8.0 | 0 1 KB nvidia

cuda-libraries-dev-11.8.0 | 0 1 KB nvidia

cuda-nvrtc-11.8.89 | 0 72.1 MB nvidia

cuda-nvrtc-dev-11.8.89 | 0 16.1 MB nvidia

cuda-nvtx-11.8.86 | 0 43 KB nvidia

cuda-profiler-api-12.6.77 | 0 19 KB nvidia

cuda-runtime-11.8.0 | 0 1 KB nvidia

cuda-version-12.6 | 3 16 KB nvidia

filelock-3.13.1 | py310haa95532_0 22 KB

freetype-2.12.1 | ha860e81_0 490 KB

giflib-5.2.2 | h7edc060_0 105 KB

gmpy2-2.1.2 | py310h7f96b67_0 160 KB

idna-3.7 | py310haa95532_0 132 KB

intel-openmp-2023.1.0 | h59b6b97_46320 2.7 MB

jinja2-3.1.4 | py310haa95532_1 281 KB

jpeg-9e | h827c3e9_3 334 KB

lcms2-2.12 | h83e58a3_0 454 KB

lerc-3.0 | hd77b12b_0 120 KB

libcublas-11.11.3.6 | 0 33 KB nvidia

libcublas-dev-11.11.3.6 | 0 375.9 MB nvidia

libcufft-10.9.0.58 | 0 6 KB nvidia

libcufft-dev-10.9.0.58 | 0 144.6 MB nvidia

libcurand-10.3.7.77 | 0 41.6 MB nvidia

libcurand-dev-10.3.7.77 | 0 262 KB nvidia

libcusolver-11.4.1.48 | 0 29 KB nvidia

libcusolver-dev-11.4.1.48 | 0 94.1 MB nvidia

libcusparse-11.7.5.86 | 0 13 KB nvidia

libcusparse-dev-11.7.5.86 | 0 175.7 MB nvidia

libdeflate-1.17 | h2bbff1b_1 153 KB

libjpeg-turbo-2.0.0 | h196d8e1_0 618 KB

libnpp-11.8.0.86 | 0 294 KB nvidia

libnpp-dev-11.8.0.86 | 0 143.2 MB nvidia

libnvjpeg-11.9.0.86 | 0 4 KB nvidia

libnvjpeg-dev-11.9.0.86 | 0 1.9 MB nvidia

libpng-1.6.39 | h8cc25b3_0 369 KB

libtiff-4.5.1 | hd77b12b_0 1.1 MB

libuv-1.48.0 | h827c3e9_0 322 KB

libwebp-1.3.2 | hbc33d0d_0 73 KB

libwebp-base-1.3.2 | h3d04722_1 303 KB

lz4-c-1.9.4 | h2bbff1b_1 152 KB

markupsafe-2.1.3 | py310h2bbff1b_0 25 KB

mkl-2023.1.0 | h6b88ed4_46358 155.9 MB

mkl-service-2.4.0 | py310h2bbff1b_1 44 KB

mkl_fft-1.3.11 | py310h827c3e9_0 168 KB

mkl_random-1.2.8 | py310hc64d2fc_0 257 KB

mpc-1.1.0 | h7edee0f_1 260 KB

mpfr-4.0.2 | h62dcd97_1 1.5 MB

mpir-3.0.0 | hec2e145_1 1.3 MB

mpmath-1.3.0 | py310haa95532_0 834 KB

networkx-3.2.1 | py310haa95532_0 2.4 MB

numpy-2.0.1 | py310h055cbcc_1 11 KB

numpy-base-2.0.1 | py310h65a83cf_1 9.1 MB

openjpeg-2.5.2 | hae555c5_0 268 KB

pillow-11.0.0 | py310hb5480e2_0 767 KB

pysocks-1.7.1 | py310haa95532_0 28 KB

pytorch-2.5.1 |py3.10_cuda11.8_cudnn9_0 1.38 GB pytorch

pytorch-cuda-11.8 | h24eeafa_6 7 KB pytorch

pytorch-mutex-1.0 | cuda 3 KB pytorch

pyyaml-6.0.2 | py310h827c3e9_0 174 KB

requests-2.32.3 | py310haa95532_1 101 KB

sympy-1.13.2 | py310haa95532_0 11.3 MB

tbb-2021.8.0 | h59b6b97_0 149 KB

torchaudio-2.5.1 | py310_cu118 7.0 MB pytorch

torchvision-0.20.1 | py310_cu118 7.7 MB pytorch

typing_extensions-4.11.0 | py310haa95532_0 62 KB

urllib3-2.2.3 | py310haa95532_0 184 KB

win_inet_pton-1.1.0 | py310haa95532_0 9 KB

yaml-0.2.5 | he774522_0 62 KB

zstd-1.5.6 | h8880b57_0 708 KB

Total: 2.64 GB

The following NEW packages will be INSTALLED:

blas pkgs/main/win-64::blas-1.0-mkl

brotli-python pkgs/main/win-64::brotli-python-1.0.9-py310hd77b12b_8

certifi pkgs/main/win-64::certifi-2024.8.30-py310haa95532_0

charset-normalizer pkgs/main/noarch::charset-normalizer-3.3.2-pyhd3eb1b0_0

cuda-cccl nvidia/win-64::cuda-cccl-12.6.77-0

cuda-cccl_win-64 nvidia/noarch::cuda-cccl_win-64-12.6.77-0

cuda-cudart nvidia/win-64::cuda-cudart-11.8.89-0

cuda-cudart-dev nvidia/win-64::cuda-cudart-dev-11.8.89-0

cuda-cupti nvidia/win-64::cuda-cupti-11.8.87-0

cuda-libraries nvidia/win-64::cuda-libraries-11.8.0-0

cuda-libraries-dev nvidia/win-64::cuda-libraries-dev-11.8.0-0

cuda-nvrtc nvidia/win-64::cuda-nvrtc-11.8.89-0

cuda-nvrtc-dev nvidia/win-64::cuda-nvrtc-dev-11.8.89-0

cuda-nvtx nvidia/win-64::cuda-nvtx-11.8.86-0

cuda-profiler-api nvidia/win-64::cuda-profiler-api-12.6.77-0

cuda-runtime nvidia/win-64::cuda-runtime-11.8.0-0

cuda-version nvidia/noarch::cuda-version-12.6-3

filelock pkgs/main/win-64::filelock-3.13.1-py310haa95532_0

freetype pkgs/main/win-64::freetype-2.12.1-ha860e81_0

giflib pkgs/main/win-64::giflib-5.2.2-h7edc060_0

gmpy2 pkgs/main/win-64::gmpy2-2.1.2-py310h7f96b67_0

idna pkgs/main/win-64::idna-3.7-py310haa95532_0

intel-openmp pkgs/main/win-64::intel-openmp-2023.1.0-h59b6b97_46320

jinja2 pkgs/main/win-64::jinja2-3.1.4-py310haa95532_1

jpeg pkgs/main/win-64::jpeg-9e-h827c3e9_3

lcms2 pkgs/main/win-64::lcms2-2.12-h83e58a3_0

lerc pkgs/main/win-64::lerc-3.0-hd77b12b_0

libcublas nvidia/win-64::libcublas-11.11.3.6-0

libcublas-dev nvidia/win-64::libcublas-dev-11.11.3.6-0

libcufft nvidia/win-64::libcufft-10.9.0.58-0

libcufft-dev nvidia/win-64::libcufft-dev-10.9.0.58-0

libcurand nvidia/win-64::libcurand-10.3.7.77-0

libcurand-dev nvidia/win-64::libcurand-dev-10.3.7.77-0

libcusolver nvidia/win-64::libcusolver-11.4.1.48-0

libcusolver-dev nvidia/win-64::libcusolver-dev-11.4.1.48-0

libcusparse nvidia/win-64::libcusparse-11.7.5.86-0

libcusparse-dev nvidia/win-64::libcusparse-dev-11.7.5.86-0

libdeflate pkgs/main/win-64::libdeflate-1.17-h2bbff1b_1

libjpeg-turbo pkgs/main/win-64::libjpeg-turbo-2.0.0-h196d8e1_0

libnpp nvidia/win-64::libnpp-11.8.0.86-0

libnpp-dev nvidia/win-64::libnpp-dev-11.8.0.86-0

libnvjpeg nvidia/win-64::libnvjpeg-11.9.0.86-0

libnvjpeg-dev nvidia/win-64::libnvjpeg-dev-11.9.0.86-0

libpng pkgs/main/win-64::libpng-1.6.39-h8cc25b3_0

libtiff pkgs/main/win-64::libtiff-4.5.1-hd77b12b_0

libuv pkgs/main/win-64::libuv-1.48.0-h827c3e9_0

libwebp pkgs/main/win-64::libwebp-1.3.2-hbc33d0d_0

libwebp-base pkgs/main/win-64::libwebp-base-1.3.2-h3d04722_1

lz4-c pkgs/main/win-64::lz4-c-1.9.4-h2bbff1b_1

markupsafe pkgs/main/win-64::markupsafe-2.1.3-py310h2bbff1b_0

mkl pkgs/main/win-64::mkl-2023.1.0-h6b88ed4_46358

mkl-service pkgs/main/win-64::mkl-service-2.4.0-py310h2bbff1b_1

mkl_fft pkgs/main/win-64::mkl_fft-1.3.11-py310h827c3e9_0

mkl_random pkgs/main/win-64::mkl_random-1.2.8-py310hc64d2fc_0

mpc pkgs/main/win-64::mpc-1.1.0-h7edee0f_1

mpfr pkgs/main/win-64::mpfr-4.0.2-h62dcd97_1

mpir pkgs/main/win-64::mpir-3.0.0-hec2e145_1

mpmath pkgs/main/win-64::mpmath-1.3.0-py310haa95532_0

networkx pkgs/main/win-64::networkx-3.2.1-py310haa95532_0

numpy pkgs/main/win-64::numpy-2.0.1-py310h055cbcc_1

numpy-base pkgs/main/win-64::numpy-base-2.0.1-py310h65a83cf_1

openjpeg pkgs/main/win-64::openjpeg-2.5.2-hae555c5_0

pillow pkgs/main/win-64::pillow-11.0.0-py310hb5480e2_0

pysocks pkgs/main/win-64::pysocks-1.7.1-py310haa95532_0

pytorch pytorch/win-64::pytorch-2.5.1-py3.10_cuda11.8_cudnn9_0

pytorch-cuda pytorch/win-64::pytorch-cuda-11.8-h24eeafa_6

pytorch-mutex pytorch/noarch::pytorch-mutex-1.0-cuda

pyyaml pkgs/main/win-64::pyyaml-6.0.2-py310h827c3e9_0

requests pkgs/main/win-64::requests-2.32.3-py310haa95532_1

sympy pkgs/main/win-64::sympy-1.13.2-py310haa95532_0

tbb pkgs/main/win-64::tbb-2021.8.0-h59b6b97_0

torchaudio pytorch/win-64::torchaudio-2.5.1-py310_cu118

torchvision pytorch/win-64::torchvision-0.20.1-py310_cu118

typing_extensions pkgs/main/win-64::typing_extensions-4.11.0-py310haa95532_0

urllib3 pkgs/main/win-64::urllib3-2.2.3-py310haa95532_0

win_inet_pton pkgs/main/win-64::win_inet_pton-1.1.0-py310haa95532_0

yaml pkgs/main/win-64::yaml-0.2.5-he774522_0

zstd pkgs/main/win-64::zstd-1.5.6-h8880b57_0

Proceed ([y]/n)? y

done 怎么办

2

您已经再次确认安装了 pytorch、torchvision、torchaudio 以及与 CUDA 11.8 对应的 pytorch-cuda 包。在最后一步，当您输入 y 时，Conda 已开始进行下载和安装。如果安装过程顺利完成（未出现新的错误信息），说明这些包已正确安装到 new_env 环境中。

接下来您可以进行如下验证步骤：

验证安装是否成功：

在 new_env 环境下执行：
复制代码
```
python -c "import torch; print(torch.version.cuda); print(torch.cuda.is_available())"
```
如果输出中返回了 11.8 或与您预期的 CUDA 版本号接近的数值，并且 True 表示 torch.cuda.is_available() 为可用，则说明 CUDA 加速已经正确启用。
运行您的 YOLOv8 程序：

将工作目录切换到您的项目目录：
复制代码
```
cd /d D:\code\ultralytics-main
```
然后运行您的训练脚本（例如 train.py）或 YOLOv8 命令行（例如 yolo task=detect mode=train ...）：
复制代码
```
python train.py
```
或
复制代码
```
yolo task=detect mode=train data=data.yaml model=yolov8n.pt epochs=100
```

如若上述验证步骤仍有问题，请检查网络稳定性、再次清理并使用 mamba（如果需要）尝试安装，或确保未同时使用 pip 与 conda 混装 PyTorch 相关包。

如果您已经成功安装了带有 CUDA 支持的 PyTorch，并且 torch.cuda.is_available() 返回了 True，那么您的环境就已经能够使用 GPU 进行深度学习训练了。接下来可以进行以下步骤：

验证 GPU 是否可用

在终端中再次确认：
复制代码
```
python -c "import torch; print(torch.cuda.is_available())"
```
输出 True 则说明 PyTorch 已经识别到 GPU。
使用 YOLOv8 训练时自动检测 GPU

YOLOv8（由 ultralytics 提供的工具包）会在默认情况下自动检测 GPU 并在有 GPU 时使用它。如果您使用 yolo 命令行接口进行训练，例如：
复制代码
```
yolo task=detect mode=train model=yolov8n.pt data=coco.yaml epochs=100
```
YOLOv8 会自动选择 GPU（CUDA）作为设备。如果需要强制指定 GPU，可以通过 device 参数：
复制代码
```
yolo task=detect mode=train model=yolov8n.pt data=coco.yaml epochs=100 device=0
```
device=0 表示使用第0号 GPU，如果您有多块GPU，可以指定对应编号。
在 Python 脚本中显式指定 GPU

如果您是通过脚本（例如 train.py）使用 YOLOv8 的 Python 接口，可以在加载 YOLO 类或 ultralytics 库时指定设备：
复制代码
```
from ultralytics import YOLO

# 加载模型
model = YOLO('yolov8n.pt')
# 使用GPU进行训练
results = model.train(data='coco.yaml', epochs=100, device=0)
```
如果不指定 device，模型会自动尝试使用 GPU。如果找不到 CUDA GPU，就会使用 CPU。

总结：

一旦您的 PyTorch CUDA 环境搭建完成，YOLOv8 在训练时会自动检测并使用 GPU。您只需要正常运行 YOLOv8 的训练命令或脚本即可享受 GPU 加速的训练过程。

完成cuda-gpu安装成功(new_env) D:\Miniconda3\envs\new_env＞conda clean --all

Package Plan

To activate this environment, use

$ conda activate new_env

To deactivate an active environment, use

$ conda deactivate

Package Plan

2