apaszke

import torch                                                                                          
                                                                                                      
def jacobian(y, x, create_graph=False):                                                               
    jac = []                                                                                          
    flat_y = y.reshape(-1)                                                                            
    grad_y = torch.zeros_like(flat_y)                                                                 
    for i in range(len(flat_y)):                                                                      
        grad_y[i] = 1.                                                                                
        grad_x, = torch.autograd.grad(flat_y, x, grad_y, retain_graph=True, create_graph=create_graph)
        jac.append(grad_x.reshape(x.shape))                                                      

songron

Codes for Machine Learning Foundations(NTU)
台湾国立大学《机器学习基石》（Coursera版）相关的代码、编程作业等。

课程地址：https://class.coursera.org/ntumlone-001/

pksunkara

[user]
	name = Pavan Kumar Sunkara
	email = pavan.sss1991@gmail.com
	username = pksunkara
[init]
	defaultBranch = master
[core]
	editor = nvim
	whitespace = fix,-indent-with-non-tab,trailing-space,cr-at-eol
	pager = delta