[diffusion] chore: validate sampling params (#16677)
Co-authored-by: root <root@huchong2-0.huchong2.podvm.svc.cluster.local>
This commit is contained in:
@@ -213,11 +213,85 @@ class SamplingParams:
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check if the sampling params is correct by itself
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"""
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if self.prompt_path and not self.prompt_path.endswith(".txt"):
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raise ValueError("prompt_path must be a txt file")
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raise ValueError(
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f"prompt_path must be a txt file, got {self.prompt_path!r}"
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)
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# These are always required to be sane regardless of pipeline.
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if (
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not isinstance(self.num_outputs_per_prompt, int)
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or self.num_outputs_per_prompt <= 0
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):
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raise ValueError(
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f"num_outputs_per_prompt must be a positive int, got {self.num_outputs_per_prompt!r}"
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)
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# Used by seconds() and video writer; fps <= 0 is always invalid.
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if not isinstance(self.fps, int) or self.fps <= 0:
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raise ValueError(f"fps must be a positive int, got {self.fps!r}")
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# num_frames is already asserted in __post_init__, but keep a friendly error here too
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# (e.g., when validation is triggered from other code paths).
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if not isinstance(self.num_frames, int) or self.num_frames <= 0:
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raise ValueError(
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f"num_frames must be a positive int, got {self.num_frames!r}"
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)
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if self.num_inference_steps is not None:
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if (
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not isinstance(self.num_inference_steps, int)
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or self.num_inference_steps <= 0
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):
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raise ValueError(
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f"num_inference_steps must be a positive int, got {self.num_inference_steps!r}"
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)
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# Numeric hyperparams should not be NaN/Inf and should be within basic ranges.
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# Note: bool is a subclass of int; reject it explicitly to avoid silent surprises.
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def _finite_non_negative_float(
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name: str, value: Any, allow_none: bool = True
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) -> None:
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if value is None and allow_none:
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return
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if isinstance(value, bool) or not isinstance(value, (int, float)):
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raise ValueError(f"{name} must be a number, got {value!r}")
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if not math.isfinite(float(value)):
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raise ValueError(f"{name} must be finite, got {value!r}")
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if float(value) < 0.0:
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raise ValueError(f"{name} must be non-negative, got {value!r}")
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_finite_non_negative_float(
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"guidance_scale", self.guidance_scale, allow_none=True
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)
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_finite_non_negative_float(
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"guidance_scale_2", self.guidance_scale_2, allow_none=True
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)
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_finite_non_negative_float(
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"true_cfg_scale", self.true_cfg_scale, allow_none=True
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)
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_finite_non_negative_float(
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"guidance_rescale", self.guidance_rescale, allow_none=False
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)
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if self.boundary_ratio is not None:
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if isinstance(self.boundary_ratio, bool) or not isinstance(
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self.boundary_ratio, (int, float)
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):
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raise ValueError(
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f"boundary_ratio must be a number, got {self.boundary_ratio!r}"
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)
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if not math.isfinite(float(self.boundary_ratio)):
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raise ValueError(
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f"boundary_ratio must be finite, got {self.boundary_ratio!r}"
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)
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if not (0.0 <= float(self.boundary_ratio) <= 1.0):
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raise ValueError(
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f"boundary_ratio must be within [0, 1], got {self.boundary_ratio!r}"
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)
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def check_sampling_param(self):
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if self.prompt_path and not self.prompt_path.endswith(".txt"):
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raise ValueError("prompt_path must be a txt file")
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# Keep backward-compatibility for old call sites.
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self._validate()
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def _validate_with_pipeline_config(self, pipeline_config):
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"""
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@@ -27,6 +27,8 @@ SUITES = {
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"test_lora_format_adapter.py",
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# cli test
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"../cli/test_generate_t2i_perf.py",
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# unit tests (no server needed)
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"../test_sampling_params_validate.py",
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# add new 1-gpu test files here
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],
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"2-gpu": [
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@@ -0,0 +1,49 @@
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import math
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import unittest
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from sglang.multimodal_gen.configs.sample.sampling_params import SamplingParams
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class TestSamplingParamsValidate(unittest.TestCase):
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def test_prompt_path_suffix(self):
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with self.assertRaisesRegex(ValueError, r"prompt_path"):
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SamplingParams(prompt_path="bad.png")
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def test_num_outputs_per_prompt_must_be_positive(self):
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with self.assertRaisesRegex(ValueError, r"num_outputs_per_prompt"):
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SamplingParams(num_outputs_per_prompt=0)
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def test_fps_must_be_positive_int(self):
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with self.assertRaisesRegex(ValueError, r"\bfps\b"):
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SamplingParams(fps=0)
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with self.assertRaisesRegex(ValueError, r"\bfps\b"):
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SamplingParams(fps=None) # type: ignore[arg-type]
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def test_num_inference_steps_optional_but_if_set_must_be_positive(self):
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SamplingParams(num_inference_steps=None)
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with self.assertRaisesRegex(ValueError, r"num_inference_steps"):
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SamplingParams(num_inference_steps=-1)
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def test_guidance_scale_must_be_finite_non_negative_if_set(self):
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SamplingParams(guidance_scale=None)
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with self.assertRaisesRegex(ValueError, r"guidance_scale"):
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SamplingParams(guidance_scale=math.nan)
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with self.assertRaisesRegex(ValueError, r"guidance_scale"):
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SamplingParams(guidance_scale=-0.1)
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def test_guidance_rescale_must_be_finite_non_negative(self):
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with self.assertRaisesRegex(ValueError, r"guidance_rescale"):
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SamplingParams(guidance_rescale=-1.0)
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with self.assertRaisesRegex(ValueError, r"guidance_rescale"):
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SamplingParams(guidance_rescale=math.inf)
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def test_boundary_ratio_range(self):
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SamplingParams(boundary_ratio=None)
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with self.assertRaisesRegex(ValueError, r"boundary_ratio"):
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SamplingParams(boundary_ratio=1.5)
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with self.assertRaisesRegex(ValueError, r"boundary_ratio"):
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SamplingParams(boundary_ratio=math.nan)
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if __name__ == "__main__":
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unittest.main()
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