def compute_hessian(y, params):
grads = chainer.grad([y], params, enable_double_backprop=True)
flat_grads = trpo._flatten_and_concat_variables(grads)
hessian_rows = []
for i in range(len(flat_grads)):
ggrads = chainer.grad([flat_grads[i]], params)
assert all(ggrad is not None for ggrad in ggrads)
ggrads_data = [ggrad.data for ggrad in ggrads]
flat_ggrads_data = trpo._flatten_and_concat_ndarrays(ggrads_data)
hessian_rows.append(flat_ggrads_data)
return np.asarray(hessian_rows)
def compute_hessian_vector_product(y, params, vec):
grads = chainer.grad(
[y], params, enable_double_backprop=True)
flat_grads = trpo._flatten_and_concat_variables(grads)
return trpo._hessian_vector_product(flat_grads, params, vec)