32 questions from Information Theory, Logistic Regression & Softmax, Neural Network Basics, Training Deep Networks, Deep Learning Frameworks, Convolutional Neural Networks, Recurrent Neural Networks, Attention & Transformers, Transfer Learning, Autoencoders & VAEs, Diffusion Models, Fine-tuning & PEFT, Alignment & Reasoning, PyTorch
20 questions · 20 min · score and explanations at the end
This is the d2l entropy function. What does the last line return?
import torch
def nansum(x):
return x[~torch.isnan(x)].sum()
def entropy(p):
return nansum(-p * torch.log2(p))
entropy(torch.tensor([0.5, 0.25, 0.25, 0.0]))