init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

vllm_ascend/worker/v2/structured_outputs.py

@@ -0,0 +1,68 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# This file is a part of the vllm-ascend project.
+#
+# NPU-compatible structured output bitmask kernel.
+#
+# Upstream cannot be used directly on Ascend NPU: `BLOCK_SIZE=8192` overflows
+# UB, while a smaller `BLOCK_SIZE` makes the grid unstable. We therefore keep
+# `BLOCK_SIZE=8192` and split each block with `BLOCK_SIZE_SUB=1024`.
+#
+#
+
+from vllm.triton_utils import tl, triton
+
+
+# Adapted from
+# https://github.com/mlc-ai/xgrammar/blob/main/python/xgrammar/kernels/apply_token_bitmask_inplace_triton.py
+# Ascend NPU bitmask kernel (BLOCK_SIZE_SUB tiling)
+# TODO: Optimize the kernel performance with NPU profiling data.
+@triton.jit
+def _apply_grammar_bitmask_kernel(
+    logits_ptr,
+    logits_stride,
+    logits_indices_ptr,
+    bitmask_ptr,
+    bitmask_stride,
+    vocab_size,
+    BLOCK_SIZE: tl.constexpr,
+):
+    BLOCK_SIZE_SUB: tl.constexpr = 1024
+    bitmask_idx = tl.program_id(0)
+    block_id = tl.program_id(1)
+    logits_idx = tl.load(logits_indices_ptr + bitmask_idx)
+
+    # Sub-block tiling loop: process BLOCK_SIZE_SUB tokens per iteration
+    for sub_offset in tl.range(0, BLOCK_SIZE, BLOCK_SIZE_SUB):
+        global_token_offset = block_id * BLOCK_SIZE + sub_offset
+        bitmask_word_start = global_token_offset // 32
+        bitmask_offset = bitmask_word_start + tl.arange(0, BLOCK_SIZE_SUB // 32)
+        packed_bitmask = tl.load(
+            bitmask_ptr + bitmask_idx * bitmask_stride + bitmask_offset,
+            mask=bitmask_offset < bitmask_stride,
+            other=0,
+        )
+        bitmask = ((packed_bitmask[:, None] >> (tl.arange(0, 32)[None, :])) & 1) == 0
+        bitmask = bitmask.reshape(BLOCK_SIZE_SUB)
+
+        # Apply: set blocked positions to -inf
+        block_offset = global_token_offset + tl.arange(0, BLOCK_SIZE_SUB)
+        tl.store(
+            logits_ptr + logits_idx * logits_stride + block_offset,
+            -float("inf"),
+            mask=bitmask & (block_offset < vocab_size),
+        )