from __future__ import annotations import logging from typing import TYPE_CHECKING import torch from sglang.jit_kernel.utils import ( cache_once, is_arch_support_pdl, load_jit, make_cpp_args, ) from sglang.srt.utils.custom_op import register_custom_op if TYPE_CHECKING: from tvm_ffi.module import Module logger = logging.getLogger(__name__) @cache_once def _jit_qknorm_rope_module( head_dim: int, rope_dim: int, is_neox: bool, dtype: torch.dtype, ) -> Module: args = make_cpp_args(head_dim, rope_dim, is_neox, is_arch_support_pdl(), dtype) return load_jit( "qknorm_rope", *args, cuda_files=["diffusion/qknorm_rope.cuh"], cuda_wrappers=[("qknorm_rope", f"QKNormRopeKernel<{args}>::run")], ) @torch.compiler.assume_constant_result @cache_once def can_use_fused_inplace_qknorm_rope( head_dim: int, rope_dim: int, is_neox: bool, dtype: torch.dtype, ) -> bool: if head_dim not in (64, 128, 256): logger.warning(f"Unsupported head_dim={head_dim} for JIT fused QKNorm+RoPE") return False if rope_dim <= 0 or rope_dim > head_dim: logger.warning( f"Unsupported rope_dim={rope_dim} for head_dim={head_dim} in fused QKNorm+RoPE" ) return False elems_per_thread = head_dim // 32 if rope_dim % elems_per_thread != 0: logger.warning( "rope_dim=%s must be divisible by per-thread width=%s for fused QKNorm+RoPE", rope_dim, elems_per_thread, ) return False if is_neox: rotary_lanes = rope_dim // elems_per_thread if rotary_lanes < 2 or rotary_lanes & (rotary_lanes - 1): logger.warning( "rope_dim=%s yields invalid rotary_lanes=%s for neox fused QKNorm+RoPE; rotary lane count must be a power of 2", rope_dim, rotary_lanes, ) return False try: _jit_qknorm_rope_module(head_dim, rope_dim, is_neox, dtype) return True except Exception as e: logger.warning(f"Failed to load JIT fused QKNorm+RoPE kernel: {e}") return False @register_custom_op(mutates_args=["q", "k"]) def fused_inplace_qknorm_rope( q: torch.Tensor, k: torch.Tensor, q_weight: torch.Tensor, k_weight: torch.Tensor, cos_sin_cache: torch.Tensor, positions: torch.Tensor, *, is_neox: bool, eps: float = 1e-6, head_dim: int = 0, rope_dim: int = 0, ) -> None: head_dim = head_dim or q.size(-1) rope_dim = rope_dim or cos_sin_cache.size(-1) module = _jit_qknorm_rope_module(head_dim, rope_dim, is_neox, q.dtype) module.qknorm_rope(q, k, q_weight, k_weight, cos_sin_cache, positions, eps)