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

2024-04-09 1603阅读

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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 "", line 1, in 
  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

    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

    1. 安装 Anaconda，这里就不多说了，啥版本都可以
    2. 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。

        1. 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

        1. CUDA 与 CUDNN 版本一定要对应，paddle 对驱动版本限制很死！！！（无力吐槽）
        2. paddle-gpu 版本要多尝试，建议老一点的版本（CPU 版本的 paddle 不影响）
        3. 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。

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