【避坑】paddlepaddle-gpu安装报错：The GPU architecture in your current machine is Pascal, which is not-Toy模板网

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版本与报错信息

完整的系统、显卡等环境如下：

系统：win10
显卡：GeForce GTX 1060 6GB
python 3.7.16
cuda：cuda 11.2.0
cudnn：cudnn 8.2.1
paddlepaddle：pip安装版本：gpu==2.5.1.post112

安装指令为：

python -m pip install paddlepaddle-gpu==2.5.1.post112 -f https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html

安装成功后，测试结果如下：

(base) D:\Downloads>python -c "import paddle; paddle.utils.run_check()"
Running verify PaddlePaddle program ...
I0831 10:35:55.205960  7352 interpretercore.cc:237] New Executor is Running.
W0831 10:35:55.205960  7352 gpu_resources.cc:96] The GPU architecture in your current machine is Pascal, which is not compatible with Paddle installation with arch: 70 75 80 86 , it is recommended to install the corresponding wheel package according to the installation information on the official Paddle website.
W0831 10:35:55.206962  7352 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:35:55.221961  7352 gpu_resources.cc:149] device: 0, cuDNN Version: 8.2.
I0831 10:35:56.037954  7352 interpreter_util.cc:518] Standalone Executor is Used.
PaddlePaddle works well on 1 GPU.
PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.

注意这个警告信息：

The GPU architecture in your current machine is Pascal, which is not compatible with Paddle installation with arch: 70 75 80 86

我以为只是一个警告信息，直接忽略了。但是当我具体写代码时，我发现了个很严重的问题！！！

(w) D:\Downloads>python
Python 3.7.16 (default, Jan 17 2023, 16:06:28) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import paddle
>>> paddle.ones([3,3])
W0831 10:13:48.890246 16284 gpu_resources.cc:96] The GPU architecture in your current machine is Pascal, which is not compatible with Paddle installation with arch: 70 75 80 86 , it is recommended to install the corresponding wheel package according to the installation information on the official Paddle website.
W0831 10:13:48.891247 16284 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:13:48.901255 16284 gpu_resources.cc:149] device: 0, cuDNN Version: 8.2.
Tensor(shape=[3, 3], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0., 0., 0.],
        [0., 0., 0.],
        [0., 0., 0.]])
>>> paddle.ones([3,3]) *3
Tensor(shape=[3, 3], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0., 0., 0.],
        [0., 0., 0.],
        [0., 0., 0.]])

paddle.ones([3,3])返回的结果是 0！！！！直接震惊，后续测试其他的代码也是如此，这说明确实是安装失败了！
后续我安装了 CPU 版本的 paddle，发现是正常的，说明确实是 GPU 版本没安装成功！这里我对比了 torch、tensorflow，这两个框架的 GPU 都能用！！所以 paddle 实锤了…

2.4.1.post112 版本安装（×）

继续尝试，我试着安装版本低一些的 paddle，先尝试的是 2.4.1.post112。
我在（https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html）网页下载了 2.4.1.post112 版本的 whl 文件，然后安装：

D:\Downloads>pip install paddlepaddle_gpu-2.4.1.post112-cp37-cp37m-win_amd64.whl -i https://pypi.tuna.tsinghua.edu.cn/simple/

安装完成后，测试结果如下：

(w) D:\Downloads>python -c "import paddle; paddle.utils.run_check()"
Running verify PaddlePaddle program ...
W0831 10:04:52.412166 12988 gpu_resources.cc:61] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:04:52.426165 12988 gpu_resources.cc:91] device: 0, cuDNN Version: 8.2.
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "D:\anaconda3\envs\w\lib\site-packages\paddle\utils\install_check.py", line 270, in run_check
    _run_dygraph_single(use_cuda, use_xpu, use_npu)
  File "D:\anaconda3\envs\w\lib\site-packages\paddle\utils\install_check.py", line 136, in _run_dygraph_single
    linear_out = linear(input_tensor)
  File "D:\anaconda3\envs\w\lib\site-packages\paddle\fluid\dygraph\layers.py", line 948, in __call__
    return self.forward(*inputs, **kwargs)
  File "D:\anaconda3\envs\w\lib\site-packages\paddle\nn\layer\common.py", line 176, in forward
    x=input, weight=self.weight, bias=self.bias, name=self.name
  File "D:\anaconda3\envs\w\lib\site-packages\paddle\nn\functional\common.py", line 1882, in linear
    return _C_ops.linear(x, weight, bias)
OSError: Invalid enum backend type `63`.
  [..\paddle/phi/common/backend.h:140]

报了新的错误：OSError: Invalid enum backend type 63.

develop 版本安装（×）

通过在 github 的 issue （https://github.com/PaddlePaddle/Paddle/issues/49964）上发现了同样的错误，查到有大佬给出解决方法：
【避坑】paddlepaddle-gpu安装报错：The GPU architecture in your current machine is Pascal, which is not,Issue,paddlepaddle,python,paddlepaddle,CUDN,GPU
安装指令依他的，如下

python -m pip install paddlepaddle-gpu==0.0.0.post112 -f https://www.paddlepaddle.org.cn/whl/windows/gpu/develop.html

安装成功后测试结果如下，依然报错（这是最开始的错误）：

(w) D:\Downloads>python -c "import paddle; paddle.utils.run_check()"
Running verify PaddlePaddle program ...
I0831 10:13:26.942690 11972 program_interpreter.cc:175] New Executor is Running.
W0831 10:13:26.943701 11972 gpu_resources.cc:96] The GPU architecture in your current machine is Pascal, which is not compatible with Paddle installation with arch: 70 75 80 86 , it is recommended to install the corresponding wheel package according to the installation information on the official Paddle website.
W0831 10:13:26.943701 11972 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:13:26.956668 11972 gpu_resources.cc:149] device: 0, cuDNN Version: 8.2.
I0831 10:13:27.715677 11972 interpreter_util.cc:602] Standalone Executor is Used.
PaddlePaddle works well on 1 GPU.
PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.

ERROR：The GPU architecture in your current machine is Pascal, which is not compatible with Paddle installation with arch: 70 75 80 86

可以发现，GPU 版本的 paddle，ones 函数的结果都是 0，很明显安装失败！

(w) D:\Downloads>python
Python 3.7.16 (default, Jan 17 2023, 16:06:28) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import paddle
>>> paddle.ones([3,3])
W0831 10:13:48.890246 16284 gpu_resources.cc:96] The GPU architecture in your current machine is Pascal, which is not compatible with Paddle installation with arch: 70 75 80 86 , it is recommended to install the corresponding wheel package according to the installation information on the official Paddle website.
W0831 10:13:48.891247 16284 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:13:48.901255 16284 gpu_resources.cc:149] device: 0, cuDNN Version: 8.2.
Tensor(shape=[3, 3], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0., 0., 0.],
        [0., 0., 0.],
        [0., 0., 0.]])
>>> paddle.ones([3,3]) *3
Tensor(shape=[3, 3], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0., 0., 0.],
        [0., 0., 0.],
        [0., 0., 0.]])

2.3.2.post112 版本安装

继续尝试之前的版本，在（https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html）网页下载了 2.3.2.post112 版本的 whl 文件，然后安装：
安装指令如下：

pip install paddlepaddle_gpu-2.3.2.post112-cp37-cp37m-win_amd64.whl

环境中所有包的版本如下：

(w) D:\Downloads>conda list
# packages in environment at D:\anaconda3\envs\w:
#
# Name                    Version                   Build  Channel
anyio                     3.7.1                    pypi_0    pypi
astor                     0.8.1                    pypi_0    pypi
ca-certificates           2023.05.30           haa95532_0    defaults
certifi                   2022.12.7        py37haa95532_0    defaults
charset-normalizer        3.2.0                    pypi_0    pypi
decorator                 5.1.1                    pypi_0    pypi
exceptiongroup            1.1.3                    pypi_0    pypi
h11                       0.14.0                   pypi_0    pypi
httpcore                  0.17.3                   pypi_0    pypi
httpx                     0.24.1                   pypi_0    pypi
idna                      3.4                      pypi_0    pypi
numpy                     1.21.6                   pypi_0    pypi
openssl                   1.1.1v               h2bbff1b_0    defaults
opt-einsum                3.3.0                    pypi_0    pypi
paddle-bfloat             0.1.7                    pypi_0    pypi
paddlepaddle-gpu          2.3.2.post112            pypi_0    pypi 
pillow                    9.5.0                    pypi_0    pypi
pip                       22.3.1           py37haa95532_0    defaults
protobuf                  3.20.0                   pypi_0    pypi
python                    3.7.16               h6244533_0    defaults
python-version            0.0.2                    pypi_0    pypi
requests                  2.31.0                   pypi_0    pypi
setuptools                65.6.3           py37haa95532_0    defaults
six                       1.16.0                   pypi_0    pypi
sniffio                   1.3.0                    pypi_0    pypi
sqlite                    3.41.2               h2bbff1b_0    defaults
typing-extensions         4.7.1                    pypi_0    pypi
urllib3                   2.0.4                    pypi_0    pypi
vc                        14.2                 h21ff451_1    defaults
vs2015_runtime            14.27.29016          h5e58377_2    defaults
wheel                     0.38.4           py37haa95532_0    defaults
wincertstore              0.2              py37haa95532_2    defaults

测试结果如下：

(w) D:\Downloads>python -c "import paddle; paddle.utils.run_check()"
Running verify PaddlePaddle program ...
W0831 10:32:31.453032 12400 gpu_resources.cc:61] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:32:31.468046 12400 gpu_resources.cc:91] device: 0, cuDNN Version: 8.2.
PaddlePaddle works well on 1 GPU.
PaddlePaddle works well on 1 GPUs.
PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.

(w) D:\Downloads>python -c "import paddle; conv = paddle.nn.Conv1D(3, 1, 1); ts = paddle.to_tensor([[[1.1], [4.5], [1.4]]], dtype='float32'); print(conv(ts))
W0831 10:32:42.271850 13316 gpu_resources.cc:61] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:32:42.285848 13316 gpu_resources.cc:91] device: 0, cuDNN Version: 8.2.
Tensor(shape=[1, 1, 1], dtype=float32, place=Place(gpu:0), stop_gradient=False,
       [[[1.36227489]]])

成功！还是不放心，再写了个脚本测试了一下：

import paddle
from paddle.vision.transforms import Normalize

transform = Normalize(mean=[127.5], std=[127.5], data_format='CHW')
# 下载数据集并初始化 DataSet
train_dataset = paddle.vision.datasets.MNIST(mode='train', transform=transform)
test_dataset = paddle.vision.datasets.MNIST(mode='test', transform=transform)

# 模型组网并初始化网络
lenet = paddle.vision.models.LeNet(num_classes=10)
model = paddle.Model(lenet)

# 模型训练的配置准备，准备损失函数，优化器和评价指标
model.prepare(paddle.optimizer.Adam(parameters=model.parameters()),
              paddle.nn.CrossEntropyLoss(),
              paddle.metric.Accuracy())

# 模型训练
model.fit(train_dataset, epochs=5, batch_size=512, verbose=1)
# 模型评估
model.evaluate(test_dataset, batch_size=128, verbose=1)

运行成功，放心了！！！

D:\anaconda3\envs\w\python.exe E:\Code\paddle_test\p.py 
W0831 10:51:13.105628 15956 gpu_resources.cc:61] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 12.2, Runtime API Version: 11.2
W0831 10:51:13.128626 15956 gpu_resources.cc:91] device: 0, cuDNN Version: 8.2.
The loss value printed in the log is the current step, and the metric is the average value of previous steps.
Epoch 1/5
D:\anaconda3\envs\w\lib\site-packages\paddle\fluid\dygraph\amp\auto_cast.py:303: UserWarning: For float16, amp only support NVIDIA GPU with Compute Capability 7.0 or higher, current GPU is: NVIDIA GeForce GTX 1060 6GB, with Compute Capability: 6.1.
  % (paddle.device.cuda.get_device_name(), prop[0], prop[1]))
step 118/118 [==============================] - loss: 0.1857 - acc: 0.8243 - 90ms/step          
Epoch 2/5
step 118/118 [==============================] - loss: 0.1530 - acc: 0.9593 - 76ms/step          
Epoch 3/5
step 118/118 [==============================] - loss: 0.1555 - acc: 0.9718 - 74ms/step          
Epoch 4/5
step 118/118 [==============================] - loss: 0.0283 - acc: 0.9774 - 73ms/step          
Epoch 5/5
step 118/118 [==============================] - loss: 0.0505 - acc: 0.9806 - 73ms/step          
Eval begin...
step 79/79 [==============================] - loss: 0.0014 - acc: 0.9770 - 24ms/step          
Eval samples: 10000

Process finished with exit code 0

总结 paddlepaddle-gpu 安装方法

paddlepaddle-gpu 安装步骤

安装 Anaconda，这里就不多说了，啥版本都可以
安装 CUDA 和 CUDNN。（划重点：这里必须参照 paddle 官网给的 cuda 和 cudnn 版本来安装！！！）

paddlepaddle官网（https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/windows-pip.html）对cuda和cudnn版本的要求描述如下：

如果您的计算机没有 NVIDIA® GPU，请安装CPU 版的 PaddlePaddle

如果您的计算机有 NVIDIA® GPU，请确保满足以下条件并且安装 GPU 版 PaddlePaddle

CUDA 工具包 10.2 配合 cuDNN v7.6.5，如需使用 PaddleTensorRT 推理，需配合 TensorRT7.0.0.11

CUDA 工具包 11.2 配合 cuDNN v8.2.1，如需使用 PaddleTensorRT 推理，需配合 TensorRT8.2.4.2

CUDA 工具包 11.6 配合 cuDNN v8.4.0，如需使用 PaddleTensorRT 推理，需配合 TensorRT8.4.0.6

CUDA 工具包 11.7 配合 cuDNN v8.4.1，如需使用 PaddleTensorRT 推理，需配合 TensorRT8.4.2.4

CUDA 工具包 11.8 配合 cuDNN v8.6.0，如需使用 PaddleTensorRT 推理，需配合 TensorRT8.5.1.7

CUDA 工具包 12.0 配合 cuDNN v8.9.1, 如需使用 PaddleTensorRT 推理，需配合 TensorRT8.6.1.6

GPU 运算能力超过 3.5 的硬件设备

注：目前官方发布的 windows 安装包仅包含 CUDA 10.2/11.2/11.6/11.7/11.8/12.0，如需使用其他 cuda 版本，请通过源码自行编译。您可参考 NVIDIA 官方文档了解 CUDA、CUDNN 和 TensorRT 的安装流程和配置方法，请见CUDA，cuDNN，TensorRT

PS：按照官网要求我安装的版本为：CUDA11.2，cuDNN8.2.1。此外，CUDA 和 CUDNN 的安装教程可以看这位大佬写的博客：https://blog.csdn.net/Vertira/article/details/125060383，写的很详细。

安装 paddle ，这里尽量选较老一点的版本，比如我最终是选择 2.3.2.post112 版本才安装成功的。安装方法参考官网，不建议安装最新版本的 paddle。建议参考网页（https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html）下载 whl 文件，离线安装，这样可供选择的版本更多些。

写在最后

CUDA 与 CUDNN 版本一定要对应，paddle 对驱动版本限制很死！！！（无力吐槽）
paddle-gpu 版本要多尝试，建议老一点的版本（CPU 版本的 paddle 不影响）
不确定我的版本是否也适合你们，但是只能多尝试版本，感觉这两个错就是paddle版本的问题，多尝试吧。诶…

就这样，希望本文对你有所帮助，感谢阅读。文章来源地址https://www.toymoban.com/news/detail-713850.html

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