我使用numba库中的装饰器@jit优化了一些python代码。但是,我想指示@jit显式地使用我的GPU设备。出发地:,我知道我需要使用@jit(target="cuda")来完成它。我试着这样做:
@jit(target='cuda') # The code runs normally without (target='cuda我希望得到一些帮助,使@jit
我被这个错误This attribute exists on the Python module, but we failed to convert Python type: 'Vocab' to amnt/d/anaconda3/lib/python3.6/site-packages/torch/jit/__init__.py", line 1261, in script
return torch.<em
对装饰器进行更好的动态控制的最佳方法是从numba.cuda.jit、numba.jit和none (纯python)中进行选择。import numba as nb
# global control of this --> @nb.jit or @nb.cuda.jit or none# some functions with @nb.jit or cuda.jit with kwargs like (nopython
normally provide to your model's forward() method.traced_script_module = torch.jit.trace(model, examplealexnet),我的代码失败:
sq = torchvision.models.squeezenet1_0(
我正在尝试使用PyTorch 中的示例代码来转换python模型,以便在PyTorch c++应用编程接口(LibTorch)中使用。to generate a torch.jit.ScriptModule via tracing. File "C:\Python37\lib\site-packages\torch\jit\__init__.py&quo