def svd(self, a):
if not isinstance(a, self.tensor):
raise TypeError('the input should be {}'.format(self.tensor.__qualname__))
if a.ndim != 2:
raise TypeError('the input tensor should be a matrix')
u, s, vh = ctf.svd(a.unwrap())
return self.tensor(u), self.tensor(ctf.real(s)), self.tensor(vh)
def _einsvd_reduced(self, expr, a, rank):
u, s, vh = a.tsr.i(expr.inputs[0].indices_string).svd(
expr.outputs[0].indices_string,
expr.outputs[1].indices_string,
rank=rank,
)
u_newshape = expr.outputs[0].newshape(u.shape)
vh_newshape = expr.outputs[1].newshape(vh.shape)
if u_newshape != u.shape: u = u.reshape(*u_newshape)
if vh_newshape != vh.shape: vh = vh.reshape(*vh_newshape)
return self.tensor(u), self.tensor(ctf.real(s)), self.tensor(vh)
def _einsvd_reduced(self, expr, a, rank, absorb_s):
u_str, vh_str = expr.outputs[0].indices_string, expr.outputs[
1].indices_string
u, s, vh = a.tsr.i(expr.inputs[0].indices_string).svd(u_str,
vh_str,
rank=rank)
u, s, vh = self.tensor(u), self.tensor(ctf.real(s)), self.tensor(vh)
u, s, vh = svd_absorb_s_ctf(u, s, vh, absorb_s, u_str, vh_str)
u_newshape = expr.outputs[0].newshape(u.shape)
vh_newshape = expr.outputs[1].newshape(vh.shape)
if u_newshape != u.shape: u = u.reshape(*u_newshape)
if vh_newshape != vh.shape: vh = vh.reshape(*vh_newshape)
return u, s, vh
def real(val):
try:
val = ctf.real(val)
except:
val = npreal(val)
return val