PyTorch data to device
what is the best practice to move data to gpu? Shall I move it before model training or move it while model training like the code you provided
ResNet bottleneck structure
for this resnet, what does buttleneck class do and why it is named bottleneck ``` def resnet50nodown(device, filename, num_classes=1): “"”Constructs a ResNet-50 nodown model. “”” model = ResNet(Bottleneck, [3, 4, 6, 3], num_classes=num_classes, stride0=1) model.load_state_dict(torch.load(filename, map_location=torch.device(‘cpu’))[‘model’]) model = model.to(device).eval() return model class Bottleneck(nn.Module): expansion = 4
Python sample files from folder
for a CNN model doing binary classification task. I have one class in folder 1 and another class in folder 2. How to randomly sample equal number of data from both classes and mix them and save sampled files from folder1 and folder2 to directory sampled_folder1 and sampled_folder2
Understanding DAO
what is DAO in crypto world? How is DAO formed and how does DAO work. Can you explain with example
Steps to build a github site like this
full guide by github: https://docs.github.com/en/pages/quickstart (quite tedious)