Python ValueError:尚未支持负步骤。如何解决

我使用4个GPU，我使用pytorch DDP加速训练。下面是我的数据集代码

import cv2
import ast
import torch
import numpy as np
import random
from glob import glob
from torch.utils.data import DataLoader, Dataset
from torch.utils.data.distributed import DistributedSampler

cv2.setNumThreads(1)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
class VimeoDataset(Dataset):
    def __init__(self, mode): ##mode = 'train' means train mode or 'val' means val mode
        self.h = 256
        self.w = 448
        self.mode = mode
        self.trainlist = glob('/data/vimeoFlow2/dataset/train/*.npz')
        self.vallist = glob('/data/vimeoFlow2/dataset/val/*.npz')
        xx = np.arange(0, self.w).reshape(1,-1).repeat(self.h,0) #xx shape is(256,448)
        yy = np.arange(0, self.h).reshape(-1,1).repeat(self.w,1) #yy shape is(448,256)
        self.grid = np.stack((xx,yy),2).copy()
        self.npzs = []
        if self.mode == 'train':
            self.npzs = self.trainlist[:80]
        else:
            self.npzs = self.vallist[:20]

    def __len__(self):
        return len(self.npzs)

    def aug(self, img0, gt, img1, flow_gt, h, w):
        ih, iw, _ = img0.shape
        x = np.random.randint(0, ih - h + 1)
        y = np.random.randint(0, iw - w + 1)
        img0 = img0[x:x+h, y:y+w, :] #random generate image slices, img shape is (224,224,:) 
        img1 = img1[x:x+h, y:y+w, :]
        gt = gt[x:x+h, y:y+w, :]
        flow_gt = flow_gt[x:x+h, y:y+w, :]
        return img0, gt, img1, flow_gt

    def getimg(self, index):
        f = np.load(self.npzs[index])
        data = f['i0i1gt']
        if self.mode == 'train':
            flow_data = f['ft0ft1']
        else:
            flow_data = np.zeros((256, 448, 4))
        img0 = data[:,:,0:3]
        img1 = data[:,:,3:6]
        gt = data[:,:,6:9]
        flow_gt = flow_data
        return img0, gt, img1, flow_gt  
        
    def __getitem__(self, index):        
        img0, gt, img1, flow_gt = self.getimg(index)
        if self.mode == 'train':
            img0, gt, img1, flow_gt = self.aug(img0, gt, img1, flow_gt, 224, 224)
            flow_gt = torch.from_numpy(flow_gt.copy()).permute(2, 0, 1)
            img0 = torch.from_numpy(img0.copy()).permute(2, 0, 1)
            img1 = torch.from_numpy(img1.copy()).permute(2, 0, 1)
            gt = torch.from_numpy(gt.copy()).permute(2, 0, 1)             
            if random.uniform(0, 1) < 0.5:
                img0 = img0[:, :, ::-1] 
                img1 = img1[:, :, ::-1]
                gt = gt[:, :, ::-1]
            if random.uniform(0, 1) < 0.5:
                img0 = img0[::-1]
                img1 = img1[::-1]
                gt = gt[::-1]
                flow_gt = flow_gt[::-1]
                flow_gt = np.concatenate((flow_gt[:, :, 0:1], -flow_gt[:, :, 1:2], flow_gt[:, :, 2:3], -flow_gt[:, :, 3:4]), 2)
            if random.uniform(0, 1) < 0.5:
                img0 = img0[:, ::-1]
                img1 = img1[:, ::-1]
                gt = gt[:, ::-1]
                flow_gt = flow_gt[:, ::-1]
                flow_gt = np.concatenate((-flow_gt[:, :, 0:1], flow_gt[:, :, 1:2], -flow_gt[:, :, 2:3], flow_gt[:, :, 3:4]), 2)
            if random.uniform(0, 1) < 0.5:
                tmp = img1
                img1 = img0
                img0 = tmp
                flow_gt = np.concatenate((flow_gt[:, :, 2:4], flow_gt[:, :, 0:2]), 2)
        flow_gt = torch.from_numpy(flow_gt.copy()).permute(2, 0, 1)
        img0 = torch.from_numpy(img0.copy()).permute(2, 0, 1)
        img1 = torch.from_numpy(img1.copy()).permute(2, 0, 1)
        gt = torch.from_numpy(gt.copy()).permute(2, 0, 1)
        return torch.cat((img0, img1, gt), 0), flow_gt

我使用以下启动命令

python -m torch.distributed.launch --nproc_per_node=4 --nnodes=1 --node_rank=0 train.py --epoch=100 --batch_size=16

错误回溯如下。我的数据集分为train和val，它们是npz文件。由于内存大小的限制，基于索引，我一次只能读取一个npz文件

 training...
    Traceback (most recent call last):
      File "train.py", line 173, in <module>
        train(model, args.local_rank)
      File "train.py", line 72, in train
        for i, data in enumerate(train_data):
      File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 346, in __next__
        data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
      File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
        data = [self.dataset[idx] for idx in possibly_batched_index]
      File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
        data = [self.dataset[idx] for idx in possibly_batched_index]
      File "/code/RIFE/dataset.py", line 67, in __getitem__
        img0 = img0[::-1]
    ValueError: negative step not yet supported
    File "/opt/conda/lib/python3.6/site-packages/torch/distributed/launch.py", line 249, in main
        cmd=cmd)
    subprocess.CalledProcessError: Command '['/opt/conda/bin/python', '-u', 'train.py', '--local_rank=3', '--epoch=100', '--batch_size=1']' returned non-zero exit status 1.

培训。。。
回溯（最近一次呼叫最后一次）：
文件“train.py”，第173行，在
列车（型号、参数、本地等级）
列车中第72行的文件“train.py”
对于i，枚举中的数据（列数据）：
文件“/opt/conda/lib/python3.6/site packages/torch/utils/data/dataloader.py”，第346行，下一步__
data=self._dataset_fetcher.fetch（index）#可能引发停止迭代
文件“/opt/conda/lib/python3.6/site packages/torch/utils/data/_utils/fetch.py”，第44行，fetch中
data=[self.dataset[idx]用于可能的批处理索引中的idx]
文件“/opt/conda/lib/python3.6/site packages/torch/utils/data/_utils/fetch.py”，第44行，在
data=[self.dataset[idx]用于可能的批处理索引中的idx]
文件“/code/RIFE/dataset.py”，第67行，在__
img0=img0[：-1]
ValueError:尚不支持负步骤
文件“/opt/conda/lib/python3.6/site packages/torch/distributed/launch.py”，第249行，主目录
cmd=cmd）
subprocess.CalledProcessError:命令'['/opt/conda/bin/python'，'-u'，train.py'，'-local_rank=3'，'-epoch=100'，'-batch_size=1']'返回非零退出状态1。

由于张量的图形关系，不能在张量中后退，请改用翻转函数：

 training...
    Traceback (most recent call last):
      File "train.py", line 173, in <module>
        train(model, args.local_rank)
      File "train.py", line 72, in train
        for i, data in enumerate(train_data):
      File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 346, in __next__
        data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
      File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
        data = [self.dataset[idx] for idx in possibly_batched_index]
      File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
        data = [self.dataset[idx] for idx in possibly_batched_index]
      File "/code/RIFE/dataset.py", line 67, in __getitem__
        img0 = img0[::-1]
    ValueError: negative step not yet supported
    File "/opt/conda/lib/python3.6/site-packages/torch/distributed/launch.py", line 249, in main
        cmd=cmd)
    subprocess.CalledProcessError: Command '['/opt/conda/bin/python', '-u', 'train.py', '--local_rank=3', '--epoch=100', '--batch_size=1']' returned non-zero exit status 1.