Fix SplitSigmasDenoise returning empty high_sigmas at low denoise

When round(steps * denoise) is 0 (e.g. a small denoise), sigmas[:-(total_steps)]
becomes sigmas[:0] because -0 == 0, collapsing high_sigmas to an empty tensor
instead of the full schedule. Slice with len(sigmas) - total_steps so the
zero case keeps the whole schedule; the behavior is identical for total_steps > 0.

comfy_extras/nodes_custom_sampler.py

@@ -245,7 +245,7 @@ class SplitSigmasDenoise(io.ComfyNode):
     def execute(cls, sigmas, denoise) -> io.NodeOutput:
         steps = max(sigmas.shape[-1] - 1, 0)
         total_steps = round(steps * denoise)
-        sigmas1 = sigmas[:-(total_steps)]
+        sigmas1 = sigmas[:len(sigmas) - total_steps]
         sigmas2 = sigmas[-(total_steps + 1):]
         return io.NodeOutput(sigmas1, sigmas2)
 

tests-unit/comfy_extras_test/split_sigmas_denoise_test.py

@@ -0,0 +1,23 @@
+import torch
+from comfy.cli_args import args as cli_args
+
+if not torch.cuda.is_available():
+    cli_args.cpu = True
+
+from comfy_extras.nodes_custom_sampler import SplitSigmasDenoise
+
+
+class TestSplitSigmasDenoise:
+    def test_low_denoise_keeps_full_high_sigmas(self):
+        # denoise small enough that round(steps * denoise) == 0. sigmas[:-0] == sigmas[:0]
+        # collapsed high_sigmas to empty; it should stay the full schedule.
+        sigmas = torch.linspace(10, 0, 21)  # 20 steps
+        high, low = SplitSigmasDenoise.execute(sigmas, 0.02)
+        assert high.shape[-1] == 21
+        assert low.shape[-1] == 1
+
+    def test_normal_denoise_split(self):
+        sigmas = torch.linspace(10, 0, 21)
+        high, low = SplitSigmasDenoise.execute(sigmas, 0.5)  # total_steps = 10
+        assert high.shape[-1] == 11
+        assert low.shape[-1] == 11