I have been trying to iterate through the items in dataloader for my model, but some reason, an error keeps showing up. After debugging, I realized that the error lies in the iteration of the dataset.
Here’s the error:
Here’s the first part of the code where the dataloader as well as the iteration is included (for debugging purpose):
from __future__ import print_function
import torch.utils
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import torchvision
from PIL import Image
import matplotlib.pyplot as plt
import torchvision.transforms as transforms
import torchvision.models as models
import copy
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# desired size of the output image
imsize = 128 if torch.cuda.is_available() else 128 # use small size if no gpu
#transforms.Grayscale(num_output_channels=1),
transform = transforms.Compose(
[transforms.Resize((128,128)),
transforms.ToTensor(),
transforms.Normalize((0.5,), (0.5,))])
target_transform = transforms.Compose(
#transforms.ToPILImage(),
[transforms.Resize((128,128)),
transforms.ToTensor(),
transforms.Normalize((0.5,), (0.5,))])
#training stuff
training_set_style = torchvision.datasets.ImageFolder('./style', transform=transform, target_transform=target_transform)
training_set_content = torchvision.datasets.ImageFolder('./content', transform=transform, target_transform=target_transform)
training_loader_style = torch.utils.data.DataLoader(training_set_style, batch_size=4, shuffle=True,num_workers=2)
training_loader_content = torch.utils.data.DataLoader(training_set_content, batch_size=4, shuffle=True,num_workers=2)
for b in enumerate(training_loader_content):
print(b)
Mainly, I wish to iterate through the dataloader in this loop:
if name in content_layers:
for batch in training_loader_content:
# add content loss:
content_image = batch[0].to(device)
print(content_image.shape)
target = model(content_image).detach()
content_loss = ContentLoss(target)
model.add_module("content_loss_{}".format(i), content_loss)
content_losses.append(content_loss)
Can somebody help me out?