Object 如何在spyder中看到内部对象张量?
我正努力在spyder中看到一个物体的内部。当我运行这个代码段时,在变量资源管理器中,我只能看到附加的fig,但是,我需要看到probs和其他对象张量,还需要访问probs的值?如有任何评论,将不胜感激Object 如何在spyder中看到内部对象张量?,object,ide,spyder,pytorch,Object,Ide,Spyder,Pytorch,我正努力在spyder中看到一个物体的内部。当我运行这个代码段时,在变量资源管理器中,我只能看到附加的fig,但是,我需要看到probs和其他对象张量,还需要访问probs的值?如有任何评论,将不胜感激 import torch from U_Net_demo import device from dataset import test_loader import matplotlib.pyplot as plt from torchvision.utils import make_grid i
import torch
from U_Net_demo import device
from dataset import test_loader
import matplotlib.pyplot as plt
from torchvision.utils import make_grid
import torch.nn as nn
import numpy
criterion = nn.NLLLoss()
def test():
model_load = torch.load('model.pth')
#test model
model_load.eval()
total = 0
test_loss = 0
correct = 0
count = 0
#iterate through test dataset
for ii, data in enumerate(test_loader):
t_image, mask = data
t_image, mask = t_image.to(device), mask.to(device)
with torch.no_grad():
outputs = model_load(t_image)
#print(outputs.shape) # torch.Size([1, 2, 240, 320])
test_loss += criterion(outputs, mask).item() / len(test_loader)
probs = torch.exp(outputs)
_, predicted = torch.max(outputs.data, 1)
total += mask.nelement()
correct += predicted.eq(mask.data).sum().item()
accuracy = 100 * correct / total
count +=1
print(count, "Test Loss: {:.3f}".format(test_loss), "Test Accuracy: %d %%" % (accuracy))
if __name__=='__main__':
test = test()
(此处为Spyder maintainer)自2019/01年起,Spyder的变量资源管理器不支持Pytorch张量。有任何支持计划吗?可能在2019年下半年发布Spyder 4.1之后,但我们无法确定。