def hessian_diag1(f, v):
g = gradient1(f, v)
idx = tt.arange(g.shape[0], dtype='int32')
def hess_ii(i):
return gradient1(g[i], v)[i]
return theano.map(hess_ii, idx)[0]
def jacobian1(f, v):
"""jacobian of f wrt v"""
f = tt.flatten(f)
idx = tt.arange(f.shape[0])
def grad_i(i):
return gradient1(f[i], v)
return theano.map(grad_i, idx)[0]
def hessian_diag1(f, v):
g = gradient1(f, v)
idx = t.arange(g.shape[0])
def hess_ii(i):
return gradient1(g[i], v)[i]
return theano.map(hess_ii, idx)[0]
def jacobian1(f, v):
"""jacobian of f wrt v"""
f = t.flatten(f)
idx = t.arange(f.shape[0])
def grad_i(i):
return gradient1(f[i], v)
return theano.map(grad_i, idx)[0]