def _eval_operand(op, args, env):
if is_constants(args):
pyfunc = _typerules.get_pyfunc(type(op))
return Constant(pyfunc(*[x.obj for x in args]))
ufunc = _typerules.get_ufunc(env.mode, type(op))
return _call_ufunc(ufunc, args, None, env)
def _eval_operand(op, args, env, dtype=None):
ufunc = _typerules.get_ufunc(env.mode, type(op))
assert ufunc.nin == len(args)
assert ufunc.nout == 1
for x in args:
if not isinstance(x.ctype, _types.Scalar):
raise NotImplementedError
in_types = tuple([x.ctype.dtype for x in args])
if dtype is None:
op = ufunc._ops._guess_routine_from_in_types(in_types)
else:
op = ufunc._ops._guess_routine_from_dtype(dtype)
if op is None:
raise TypeError(
f'"{ufunc.name}" does not support for the input types: {in_types}')
if op.routine is None:
op.error_func()
assert op.routine.startswith('out0 = ')
out_type = _types.Scalar(op.out_types[0])
expr = op.routine[7:]
for i, x in enumerate(args):
x = astype_scalar(x, _types.Scalar(op.in_types[i]))
expr = expr.replace(f'in{i}', x.code)
expr = expr.replace('out0_type', str(out_type))
env.preambles.add(ufunc._preamble)
return CudaObject('(' + expr + ')', out_type)