pytorch backward機制了解

m=Variable( torch.FloatTensor( [ [2,3] ] ),requires_grad=True )
# j=torch.zeros(2,2)
# k=Variable( torch.zeros( 1,2 ) )
#
# k[0,0]=m[0,0]**2+3*m[0,1]
# k[0,1]=m[0,1]**2+2*m[0,0]
#
# k.backward( torch.FloatTensor( [ [1,1] ] ) )
# print k
# print m.grad
# print m.grad.data

j=torch.zeros( 2,2 )
k=Variable( torch.zeros(1,2) )
# m.grad.data.zero_()
k[0,0]=m[0,0]**2+3*m[0,1]
k[0,1]=m[0,1]**2+2*m[0,0]

k.backward( torch.FloatTensor( [[1,0]] ),retain_graph=True )
j[:,0]=m.grad.data
m.grad.data.zero_()
k.backward( torch.FloatTensor( [[0,1]] ) )
j[:,1]=m.grad.data
print j