[diffusion] refactor: validate and document spectrum controls (#33851)

python/sglang/multimodal_gen/configs/sample/spectrum.py

@@ -1,6 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 from __future__ import annotations
 
+import math
 from dataclasses import dataclass
 
 from sglang.multimodal_gen.configs.sample.sampling_params import CacheParams
@@ -67,6 +68,45 @@ class SpectrumParams(CacheParams):
     tau_num_steps: int = 50
     taylor_order: int = 1
 
+    def __post_init__(self) -> None:
+        finite_numbers = {
+            "window_size": self.window_size,
+            "flex_window": self.flex_window,
+            "w": self.w,
+            "lam": self.lam,
+        }
+        for name, value in finite_numbers.items():
+            if (
+                isinstance(value, bool)
+                or not isinstance(value, (int, float))
+                or not math.isfinite(value)
+            ):
+                raise ValueError(f"Spectrum {name} must be a finite number.")
+
+        if self.window_size <= 0:
+            raise ValueError("Spectrum window_size must be greater than zero.")
+        if self.flex_window < 0:
+            raise ValueError("Spectrum flex_window must be non-negative.")
+        if not 0 <= self.w <= 1:
+            raise ValueError("Spectrum w must be between zero and one.")
+        if self.lam < 0:
+            raise ValueError("Spectrum lam must be non-negative.")
+
+        non_negative_ints = {"warmup_steps": self.warmup_steps}
+        positive_ints = {
+            "m": self.m,
+            "history_size": self.history_size,
+            "tau_num_steps": self.tau_num_steps,
+        }
+        for name, value in non_negative_ints.items():
+            if isinstance(value, bool) or not isinstance(value, int) or value < 0:
+                raise ValueError(f"Spectrum {name} must be a non-negative integer.")
+        for name, value in positive_ints.items():
+            if isinstance(value, bool) or not isinstance(value, int) or value <= 0:
+                raise ValueError(f"Spectrum {name} must be a positive integer.")
+        if self.taylor_order not in (1, 2, 3):
+            raise ValueError("Spectrum taylor_order must be one of 1, 2, or 3.")
+
     def get_total_forward_steps(
         self, num_inference_steps: int, do_cfg: bool, separate_cfg_branches: bool
     ) -> int:

python/sglang/multimodal_gen/test/unit/test_sampling_params.py

@@ -29,6 +29,7 @@ from sglang.multimodal_gen.configs.sample.sampling_params import (
     SamplingParams,
     _json_safe,
 )
+from sglang.multimodal_gen.configs.sample.spectrum import SpectrumParams
 from sglang.multimodal_gen.configs.sample.teacache import TeaCacheParams
 from sglang.multimodal_gen.configs.sample.wan import (
     FastWanT2V480PConfig,
@@ -105,6 +106,29 @@ class TestSamplingParamsValidate(unittest.TestCase):
         ):
             SamplingParams(enable_teacache=True, enable_spectrum=True)
 
+    def test_spectrum_params_reject_invalid_controls(self):
+        invalid_controls = (
+            {"window_size": 0},
+            {"flex_window": -0.1},
+            {"w": 1.1},
+            {"lam": -0.1},
+            {"warmup_steps": -1},
+            {"m": 0},
+            {"history_size": 0},
+            {"tau_num_steps": 0},
+            {"taylor_order": 4},
+        )
+        for kwargs in invalid_controls:
+            with self.assertRaises(ValueError):
+                SpectrumParams(**kwargs)
+
+    def test_spectrum_dict_is_validated_when_sampling_params_constructs_it(self):
+        with self.assertRaisesRegex(ValueError, "history_size"):
+            SamplingParams(
+                enable_spectrum=True,
+                spectrum_params={"history_size": 0},
+            )
+
 
 class TestSamplingParamsSubclass(unittest.TestCase):
     def test_glm_image_rounds_resolution_up_to_multiple_of_32(self):