chore: import upstream snapshot with attribution

vllm/config/diffusion.py

@@ -0,0 +1,26 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Configuration for discrete diffusion (dLLM) models."""
+
+from pydantic import Field
+
+from vllm.config.utils import config
+
+
+@config
+class DiffusionConfig:
+    """Configuration for discrete diffusion language models (dLLMs).
+
+    dLLMs generate tokens via iterative denoising over a fixed-length canvas
+    rather than left-to-right autoregressive decoding. They reuse the
+    speculative-decoding data path (draft token ids, scheduled spec decode
+    tokens) with overloaded semantics for block-based generation.
+    """
+
+    canvas_length: int = Field(default=None, gt=0)  # type: ignore[assignment]
+    """Length of the denoising canvas (block).  Also determines the number of
+    speculative tokens scheduled per step."""
+
+    max_denoising_steps: int | None = None
+    """Maximum number of denoising iterations per canvas block.
+    If not set, read from the model's generation_config.json."""