vllm/vllm/v1/worker/gpu/structured_outputs.py
Woosuk Kwon 30b44a1598
GPU Model Runner V2 (#25266)
Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
2025-11-21 08:20:55 -08:00

77 lines
2.5 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import numpy as np
import torch
from vllm.triton_utils import tl, triton
from vllm.v1.worker.gpu.input_batch import InputBuffers
def apply_grammar_bitmask(
logits: torch.Tensor,
req_ids: list[str],
grammar_req_ids: list[str],
grammar_bitmask: np.ndarray,
input_buffers: InputBuffers,
) -> None:
input_buffers.grammar_bitmask.np[: grammar_bitmask.shape[0]] = grammar_bitmask
input_buffers.grammar_bitmask.copy_to_gpu(grammar_bitmask.shape[0])
batch_size = logits.shape[0]
grammar_req_id_to_idx = {req_id: i for i, req_id in enumerate(grammar_req_ids)}
# logits -> bitmask mapping
mapping = [grammar_req_id_to_idx.get(req_id, -1) for req_id in req_ids]
input_buffers.bitmask_indices.np[:batch_size] = mapping
input_buffers.bitmask_indices.copy_to_gpu(batch_size)
vocab_size = logits.shape[-1]
BLOCK_SIZE = 8192
grid = (batch_size, triton.cdiv(vocab_size, BLOCK_SIZE))
_apply_grammar_bitmask_kernel[grid](
logits,
logits.stride(0),
input_buffers.grammar_bitmask.gpu,
input_buffers.grammar_bitmask.gpu.stride(0),
input_buffers.bitmask_indices.gpu,
vocab_size,
BLOCK_SIZE=BLOCK_SIZE,
)
# Adapted from
# https://github.com/mlc-ai/xgrammar/blob/main/python/xgrammar/kernels/apply_token_bitmask_inplace_triton.py
@triton.jit
def _apply_grammar_bitmask_kernel(
logits_ptr,
logits_stride,
bitmask_ptr,
bitmask_stride,
bitmask_indices_ptr,
vocab_size,
BLOCK_SIZE: tl.constexpr,
):
logits_idx = tl.program_id(0)
bitmask_idx = tl.load(bitmask_indices_ptr + logits_idx)
if bitmask_idx == -1:
# No bitmask to apply.
return
# Load the bitmask.
block_id = tl.program_id(1)
bitmask_offset = (block_id * BLOCK_SIZE) // 32 + tl.arange(0, BLOCK_SIZE // 32)
packed_bitmask = tl.load(
bitmask_ptr + bitmask_idx * bitmask_stride + bitmask_offset,
mask=bitmask_offset < bitmask_stride,
)
# Unpack the bitmask.
bitmask = ((packed_bitmask[:, None] >> (tl.arange(0, 32)[None, :])) & 1) == 0
bitmask = bitmask.reshape(BLOCK_SIZE)
# Apply the bitmask to the logits.
block_offset = block_id * BLOCK_SIZE + tl.arange(0, BLOCK_SIZE)
tl.store(
logits_ptr + logits_idx * logits_stride + block_offset,
-float("inf"),
mask=bitmask & (block_offset < vocab_size),
)