[releases/v0.18.0][Triton][Sampler] Add penalty-related Triton kernel for better performance of penalties (#7794)

### What this PR does / why we need it?
Implement get_token_bin_counts_and_mask and apply_penalties with
Triton-Ascend kernels. This significantly reduces latency of the
sampling process when repetition/frequency/presence penalties are
enabled.

Cherry-pick from main PR #7569 
### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
CI passed.

Signed-off-by: linfeng-yuan <1102311262@qq.com>
Co-authored-by: realliujiaxu <realliujiaxu@163.com>

vllm_ascend/sample/penalties.py

@@ -0,0 +1,45 @@
+# SPDX-License-Identifier: Apache-2.0
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+#
+# apply_all_penalties for AscendSampler - uses Triton-Ascend kernels.
+
+import torch
+from vllm.utils.platform_utils import is_pin_memory_available
+from vllm.utils.torch_utils import make_tensor_with_pad
+
+from vllm_ascend.ops.triton.penalty import apply_penalties_triton
+
+
+def _convert_to_tensors(output_token_ids: list[list[int]], vocab_size: int, device: torch.device) -> torch.Tensor:
+    """Convert output_token_ids (list of lists) to padded tensor."""
+    output_tokens_tensor = make_tensor_with_pad(
+        output_token_ids,
+        pad=vocab_size,
+        device="cpu",
+        dtype=torch.int64,
+        pin_memory=is_pin_memory_available(),
+    )
+    return output_tokens_tensor.to(device, non_blocking=True)
+
+
+def apply_all_penalties(
+    logits: torch.Tensor,
+    prompt_token_ids: torch.Tensor,
+    presence_penalties: torch.Tensor,
+    frequency_penalties: torch.Tensor,
+    repetition_penalties: torch.Tensor,
+    output_token_ids: list[list[int]],
+) -> torch.Tensor:
+    """Apply penalties to logits via Triton-Ascend."""
+    _, vocab_size = logits.shape
+    output_tokens_t = _convert_to_tensors(output_token_ids, vocab_size, logits.device)
+    output_tokens_t.masked_fill_(output_tokens_t == -1, vocab_size)
+
+    return apply_penalties_triton(
+        logits,
+        prompt_token_ids,
+        output_tokens_t,
+        presence_penalties,
+        frequency_penalties,
+        repetition_penalties,
+    )