def _record_function_with_param(self):
u = torch.randn(3, 4, 5, requires_grad=True)
with _profile(with_stack=True, use_kineto=kineto_available(), record_shapes=True) as prof:
with record_function("## TEST 1 ##", "1, 2, 3"):
rf_handle = _record_function_with_args_enter("## TEST 2 ##", 1, False, 2.5, [u, u], "hello", u)
_record_function_with_args_exit(rf_handle)
with record_function("## TEST 3 ##"):
rf_handle = _record_function_with_args_enter("## TEST 4 ##")
_record_function_with_args_exit(rf_handle)
return prof
def payload(self, use_cuda=False):
u = torch.randn(3, 4, 5, requires_grad=True)
with record_function("## TEST 1 ##", "1, 2, 3"):
rf_handle = _record_function_with_args_enter("## TEST 2 ##", 1, False, 2.5, [u, u], (u, u), "hello", u)
x = torch.randn(10, 10, requires_grad=True)
if use_cuda:
x = x.cuda()
y = torch.randn(10, 10, requires_grad=True)
if use_cuda:
y = y.cuda()
z = x + y + x * y + x * y
z.backward(z)
if use_cuda:
z = z.cpu()
_record_function_with_args_exit(rf_handle)
