【pytorch】数据转换

pytorch中的硬件设备

查看显卡信息

nvidia-smi

在代码中指定设备

import os
os.environ["CUDA_VISIBLE_DEVICES"] = "2"`

cpu->gpu:

if torch.cuda.is_aviliable():
    a=a.cuda()

gpu->cpu:

a=a.cpu()

pytorch中的分布式

分布式并行处理数据在一些代码里面见到过，但是由于现在还没有机会用到，就先简单写一下，后面用到了深入了解吧

torch.distributed.init_process_group(world_size=4, init_method='...')
model = torch.nn.DistributedDataParallel(model)

pytorch中的数据类型

Data type	dtype	CPU tensor	GPU tensor
32-bit floating point	torch.float32 or torch.float	torch.FloatTensor	torch.cuda.FloatTensor
64-bit floating point	torch.float64 or torch.double	torch.DoubleTensor	torch.cuda.DoubleTensor
16-bit floating point	torch.float16 or torch.half	torch.HalfTensor	torch.cuda.HalfTensor
8-bit integer (unsigned)	torch.uint8	torch.ByteTensor	torch.cuda.ByteTensor
8-bit integer (signed)	torch.int8	torch.CharTensor	torch.cuda.CharTensor
16-bit integer (signed)	torch.int16 or torch.short	torch.ShortTensor	torch.cuda.ShortTensor
32-bit integer (signed)	torch.int32 or torch.int	torch.IntTensor	torch.cuda.IntTensor
64-bit integer (signed)	torch.int64 or torch.long	torch.LongTensor	torch.cuda.LongTensor

x,y=torch.from_numpy(x),torch.from_numpy(y)
x,y=x.type(torch.DoubleTensor),y.type(torch.DoubleTensor

z=torch.zeros([2, 4], dtype=torch.int32)