【发布时间】:2021-11-15 01:02:07
【问题描述】:
我正在研究这个模型:
class Model(torch.nn.Module):
def __init__(self, sizes, config):
super(Model, self).__init__()
self.lstm = []
for i in range(len(sizes) - 2):
self.lstm.append(LSTM(sizes[i], sizes[i+1], num_layers=8))
self.lstm.append(torch.nn.Linear(sizes[-2], sizes[-1]).cuda())
self.lstm = torch.nn.ModuleList(self.lstm)
self.config_mel = config.mel_features
def forward(self, x):
# convert to log-domain
x = x.clip(min=1e-6).log10()
for layer in self.lstm[:-1]:
x, _ = layer(x)
x = torch.relu(x)
#x = torch_unpack_seq(x)[0]
x = self.lstm[-1](x)
mask = torch.sigmoid(x)
return mask
然后:
model = Model(model_width, config)
model.cuda()
但我收到此错误:
File "main.py", line 29, in <module>
Model.train(args)
File ".../src/model.py", line 57, in train
model.cuda()
File ".../.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 637, in cuda
return self._apply(lambda t: t.cuda(device))
File ".../.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in _apply
module._apply(fn)
File "/.../.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in _apply
module._apply(fn)
File ".../.local/lib/python3.8/site-packages/torch/nn/modules/rnn.py", line 189, in _apply
self.flatten_parameters()
File ".../.local/lib/python3.8/site-packages/torch/nn/modules/rnn.py", line 175, in flatten_parameters
torch._cudnn_rnn_flatten_weight(
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
我不知道为什么会这样。我正在尝试在 cuda 中推送模型和输入,并且我了解错误是否是由于 CPU 中的某些模型和 GPU 中的某些模型引起的。但这里不是这样。我在这里找到了一些 pip 安装解决方案:Pytorch CUDA error: no kernel image is available for execution on the device on RTX 3090 with cuda 11.1
但我无法使用它,因为我试图在无法访问 pip install 的远程仓库中完成工作。
有什么办法可以解决这个问题吗?
【问题讨论】:
-
您尝试使用的 PyTorch 安装没有对您尝试使用的 GPU 的内置二进制支持。您将必须找到(或自己制作)具有内置支持的构建。由于 PyTorch 的设计和封装,这里没有工作