Fix grammar abort & Minor style fixes (#7204)

python/sglang/srt/layers/attention/flashinfer_mla_backend.py

@@ -15,7 +15,6 @@ from functools import partial
 from typing import TYPE_CHECKING, Callable, Optional, Union
 
 import torch
-import triton
 
 if os.environ["SGLANG_ENABLE_TORCH_COMPILE"] == "1":
     import logging
@@ -33,7 +32,7 @@ from sglang.srt.layers.utils import is_sm100_supported
 from sglang.srt.managers.schedule_batch import global_server_args_dict
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch, ForwardMode
 from sglang.srt.speculative.eagle_utils import EagleDraftInput, EagleVerifyInput
-from sglang.srt.utils import is_flashinfer_available
+from sglang.srt.utils import is_flashinfer_available, next_power_of_2
 
 if TYPE_CHECKING:
     from sglang.srt.layers.radix_attention import RadixAttention
@@ -756,7 +755,7 @@ class FlashInferMLAMultiStepDraftBackend:
 
         if topk > 1:
             raise ValueError(
-                f"Currently Flashinfer MLA only supports topk=1 for speculative decoding"
+                "Currently Flashinfer MLA only supports topk=1 for speculative decoding"
             )
         self.topk = topk
         self.speculative_num_steps = speculative_num_steps
@@ -815,9 +814,9 @@ class FlashInferMLAMultiStepDraftBackend:
             self.pool_len,
             kv_indices_buffer.shape[1],
             self.kv_indptr.shape[1],
-            triton.next_power_of_2(num_seqs),
-            triton.next_power_of_2(self.speculative_num_steps),
-            triton.next_power_of_2(bs),
+            next_power_of_2(num_seqs),
+            next_power_of_2(self.speculative_num_steps),
+            next_power_of_2(bs),
         )
 
         assert forward_batch.spec_info is not None

python/sglang/srt/layers/attention/flashmla_backend.py

@@ -464,11 +464,9 @@ class FlashMLAMultiStepDraftBackend:
         topk: int,
         speculative_num_steps: int,
     ):
-        from sglang.srt.speculative.eagle_utils import generate_draft_decode_kv_indices
-
         if topk > 1:
             raise ValueError(
-                f"Currently FlashMLA only supports topk=1 for speculative decoding"
+                "Currently FlashMLA only supports topk=1 for speculative decoding"
             )
         self.topk = topk
         self.speculative_num_steps = speculative_num_steps

python/sglang/srt/layers/attention/triton_backend.py

@@ -12,7 +12,7 @@ from sglang.srt.layers.attention.utils import create_flashinfer_kv_indices_trito
 from sglang.srt.layers.dp_attention import get_attention_tp_size
 from sglang.srt.layers.radix_attention import AttentionType
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch, ForwardMode
-from sglang.srt.utils import get_bool_env_var, get_device_core_count
+from sglang.srt.utils import get_bool_env_var, get_device_core_count, next_power_of_2
 
 if TYPE_CHECKING:
     from sglang.srt.layers.radix_attention import RadixAttention
@@ -766,6 +766,7 @@ class TritonMultiStepDraftBackend:
         self.device = model_runner.device
         # Cached variables for generate_draft_decode_kv_indices
         self.pool_len = model_runner.req_to_token_pool.req_to_token.shape[1]
+        self.page_size = model_runner.server_args.page_size
 
     def common_template(
         self, forward_batch: ForwardBatch, kv_indices_buffer: torch.Tensor, call_fn: int
@@ -788,9 +789,9 @@ class TritonMultiStepDraftBackend:
             self.pool_len,
             kv_indices_buffer.shape[1],
             self.kv_indptr.shape[1],
-            triton.next_power_of_2(num_seqs),
-            triton.next_power_of_2(self.speculative_num_steps),
-            triton.next_power_of_2(bs),
+            next_power_of_2(num_seqs),
+            next_power_of_2(self.speculative_num_steps),
+            next_power_of_2(bs),
         )
 
         for i in range(self.speculative_num_steps):

python/sglang/srt/layers/attention/triton_ops/decode_attention.py

@@ -708,7 +708,7 @@ def decode_attention_fwd(
             num_kv_splits,
             max_kv_splits,
             sm_scale,
-            logit_cap,
+            logit_cap=logit_cap,
         )
     else:
         # GQA/MQA/MLA
@@ -724,5 +724,5 @@ def decode_attention_fwd(
             num_kv_splits,
             max_kv_splits,
             sm_scale,
-            logit_cap,
+            logit_cap=logit_cap,
         )

python/sglang/srt/layers/radix_attention.py

@@ -18,7 +18,6 @@ from typing import Optional
 
 from torch import nn
 
-from sglang.srt.layers.linear import UnquantizedLinearMethod
 from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 
@@ -52,9 +51,9 @@ class RadixAttention(nn.Module):
         sliding_window_size: int = -1,
         is_cross_attention: bool = False,
         quant_config: Optional[QuantizationConfig] = None,
-        attn_type=AttentionType.DECODER,
-        prefix: str = "",
+        attn_type: AttentionType = AttentionType.DECODER,
         use_irope: bool = False,
+        prefix: str = "",
     ):
         super().__init__()
         self.tp_q_head_num = num_heads

python/sglang/srt/managers/scheduler.py

@@ -2108,6 +2108,7 @@ class Scheduler(
             # In this case, we change the input_ids to be only one token to make this prefill cheap.
             if req.rid.startswith(recv_req.rid):
                 logger.debug(f"Abort grammar queue request. {req.rid=}")
+                if req.grammar:
                     req.grammar.cancel()
                 req.set_finish_with_abort("Aborted by AbortReq.")
 

python/sglang/srt/mem_cache/memory_pool.py

@@ -141,15 +141,12 @@ class KVCache(abc.ABC):
     ) -> None:
         raise NotImplementedError()
 
-    @abc.abstractmethod
     def get_flat_data(self, indices):
         raise NotImplementedError()
 
-    @abc.abstractmethod
     def transfer(self, indices, flat_data):
         raise NotImplementedError()
 
-    @abc.abstractmethod
     def transfer_per_layer(self, indices, flat_data, layer_id):
         raise NotImplementedError()
 

python/sglang/srt/speculative/eagle_draft_extend_cuda_graph_runner.py

@@ -86,8 +86,8 @@ class EAGLEDraftExtendCudaGraphRunner:
 
             self.seq_lens = torch.ones((self.max_bs,), dtype=torch.int32)
             self.extend_seq_lens = torch.ones((self.max_bs,), dtype=torch.int32)
-            self.accept_length = (
-                torch.ones((self.max_bs,), dtype=torch.int32) * self.num_tokens_per_bs
+            self.accept_length = torch.full(
+                (self.max_bs,), self.num_tokens_per_bs, dtype=torch.int32
             )
 
         # Capture