CompVis / metric-learning-divide-and-conquer

Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019

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'_SingleProcessDataLoaderIter' object has no attribute 'next'

LUCASDNORONHA opened this issue · comments

can someone explain to me?

import numpy as np
import torch
import torch.nn.functional as F
import matplotlib.pyplot as plt
from time import time
from torchvision import datasets, transforms
from torch import nn, optim

trasnform = transforms.ToTensor()
trainset = datasets.MNIST('./MMIST_data/', download=True, train=True, transform=transforms)
trainloader = torch.utils.data.DataLoader(trainset, batch_size=64, shuffle=True)

valset = datasets.MNIST('./MNIST_data/', download=True, train=False, transform=transforms)
valloader = torch.utils.data.DataLoader(valset, batch_size=64, shuffle=True)

dataiter = iter(trainloader)
imagens, etiquetas = dataiter.next()
plt.imshow(imagens[0].numpy().squeeze(), cmpap='gray_r');

erro:
AttributeError Traceback (most recent call last)
in
1 dataiter = iter(trainloader)
----> 2 imagens, etiquetas = dataiter.next()
3 plt.imshow(imagens[0].numpy().squeeze(), cmpap='gray_r');

AttributeError: '_SingleProcessDataLoaderIter' object has no attribute 'next'