问题描述
最近我了解到 CuPy 将利用 GPU 来加速深度学习中的计算。但是,在执行以下步骤后,我仍然遇到无法解决的错误:
import h5py
import torch
import numpy as np
import cupy as cp
from torch.utils.data import Dataset,DataLoader
from torchvision import transforms,utils
class cupy_Dataset(Dataset):
def __init__(self,file_dir):
super(cupy_Dataset,self).__init__()
data = h5py.File(file_dir)
self.ms = cp.array(data.get("ms"))
self.lms = cp.array(data.get("lms"))
self.pan = cp.array(data.get("pan"))
self.gt = cp.array(data.get("gt"))
self.ms = (self.ms[0:10,:,:])
self.lms = (self.lms[0:10,:])
self.pan = (self.pan[0:10,:])
self.gt = (self.gt[0:10,:])
self.ms = torch.utils.dlpack.from_dlpack(self.ms.toDLpack()).float()
self.lms = torch.utils.dlpack.from_dlpack(self.lms.toDLpack()).float()
self.pan = torch.utils.dlpack.from_dlpack(self.pan.toDLpack()).float()
self.gt = torch.utils.dlpack.from_dlpack(self.gt.toDLpack()).float()
def __len__(self):
return len(self.gt.shape[0])
def __getitem__(self,idx):
ms = self.ms[idx,:]
lms = self.lms[idx,:]
pan = self.pan[idx,:]
gt = self.gt[idx,:]
return ms,lms,pan,gt
if __name__ == '__main__':
train_dataset = cupy_WorldView3_Dataset(file_dir='./training_data/train.mat')
print(train_dataset.gt.shape)
在文件 B
中:
import torch
import cupy
from {file_A} import cupy_Dataset
train_dataset = cupy_Dataset(file_dir='./training_data/train.mat')
gt = train_dataset.gt
pan = train_dataset.pan
lms = train_dataset.lms
ms = train_dataset.ms
print(type(gt))
Traceback (most recent call last):
File "{file path}",line 94,in <module>
train_dataset = cupy_WorldView3_Dataset(file_dir='./training_data/train.mat')
File "{file path}",line 76,in __init__
self.ms = torch.utils.dlpack.from_dlpack(self.ms.toDLpack()).float()
AttributeError: module 'torch.utils' has no attribute 'dlpack'
Using backend: pytorch
Traceback (most recent call last):
File "/home/office-desktop/.pycharm_helpers/pydev/pydevd.py",line 1477,in _exec
pydev_imports.execfile(file,globals,locals) # execute the script
File "/home/office-desktop/.pycharm_helpers/pydev/_pydev_imps/_pydev_execfile.py",line 18,in execfile
exec(compile(contents+"\n",file,'exec'),glob,loc)
File "{file path}",line 6,in <module>
train_dataset = cupy_Dataset(file_dir='./training_data/train.mat')
File "{file path}",in __init__
self.ms = torch.utils.dlpack.from_dlpack(self.ms.toDLpack()).float()
AttributeError: 'cupy.core.core.ndarray' object has no attribute 'toDLpack'
Process finished with exit code 1
仅供参考,我的基本想法是使用 DLpack
作为 CuPy 和 PyTorch 张量之间的互连。初始用法和语法可以在 https://docs.cupy.dev/en/stable/reference/interoperability.html 和 https://pytorch.org/docs/stable/dlpack.html 中找到。
这是为什么?先感谢您。如果您需要任何其他信息,我愿意提供:)
解决方法
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