Remove deprecated configs (#1431)

python/sglang/bench_latency.py

@@ -63,7 +63,7 @@ from sglang.srt.managers.schedule_batch import Req, ScheduleBatch
 from sglang.srt.model_executor.model_runner import ModelRunner
 from sglang.srt.sampling.sampling_params import SamplingParams
 from sglang.srt.server_args import ServerArgs
-from sglang.srt.utils import suppress_other_loggers
+from sglang.srt.utils import kill_child_process, suppress_other_loggers
 
 
 @dataclasses.dataclass
@@ -502,4 +502,9 @@ if __name__ == "__main__":
         format="%(message)s",
     )
 
-    main(server_args, bench_args)
+    try:
+        main(server_args, bench_args)
+    except Exception as e:
+        raise e
+    finally:
+        kill_child_process(os.getpid(), including_parent=False)

python/sglang/global_config.py

 """Global configurations"""
 
+import os
+
 
 class GlobalConfig:
     def __init__(self):
@@ -16,30 +18,20 @@ class GlobalConfig:
         self.base_min_new_token_ratio = 0.1
         self.new_token_ratio_decay = 0.001
 
-        # Runtime constants: The threshold (number of tokens) to trigger layer-wise cuda sync.
-        # This can improve the speed for large batch sizes during prefill.
-        self.layer_sync_threshold = 8192
-
         # Runtime constants: others
         self.num_continue_decode_steps = 10
         self.retract_decode_steps = 20
-        self.flashinfer_workspace_size = 384 * 1024 * 1024
+        self.flashinfer_workspace_size = os.environ.get(
+            "FLASHINFER_WORKSPACE_SIZE", 384 * 1024 * 1024
+        )
 
         # Output tokenization configs
         self.skip_special_tokens_in_output = True
         self.spaces_between_special_tokens_in_out = True
 
         # Interpreter optimization configs
-        self.eager_fill_image = False
         self.enable_precache_with_tracing = True
         self.enable_parallel_encoding = True
-        self.enable_parallel_decoding = True
-
-        # Deprecated
-        # Choices: ["no_adjust", "adjust_cache"]
-        # no_adjust: Do not adjust the position embedding of KV cache.
-        # adjust_cache: Adjust the position embedding of KV cache.
-        self.concate_and_append_mode = "no_adjust"
 
 
 global_config = GlobalConfig()

python/sglang/lang/interpreter.py

@@ -434,9 +434,6 @@ class StreamExecutor:
         self.cur_images.append((path, base64_data))
         self.text_ += self.chat_template.image_token
 
-        # if global_config.eager_fill_image:
-        #     self.backend.fill_image(self)
-
     def _spec_gen(self, sampling_params):
         stop = sampling_params.stop
         max_new_tokens = sampling_params.max_new_tokens

python/sglang/srt/layers/attention_backend.py

@@ -150,7 +150,7 @@ class FlashInferAttnBackend(AttentionBackend):
             # Some heuristics to check whether to use ragged forward
             use_ragged = False
             if (
-                int(torch.sum(input_metadata.seq_lens)) > 4096
+                torch.sum(input_metadata.seq_lens).item() >= 4096
                 and self.model_runner.sliding_window_size is None
             ):
                 use_ragged = True
@@ -301,10 +301,6 @@ class FlashInferAttnBackend(AttentionBackend):
                 layer.layer_id, input_metadata.out_cache_loc, k, v
             )
 
-            if total_num_tokens >= global_config.layer_sync_threshold:
-                # TODO: Revisit this. Why is this synchronize needed?
-                torch.cuda.synchronize()
-
         return o.view(-1, layer.tp_q_head_num * layer.head_dim)
 
     def forward_decode(self, q, k, v, layer: nn.Module, input_metadata: InputMetadata):

python/sglang/test/test_utils.py

@@ -304,7 +304,6 @@ def add_common_sglang_args_and_parse(parser: argparse.ArgumentParser):
 def select_sglang_backend(args: argparse.Namespace):
     if args.backend.startswith("srt"):
         if args.backend == "srt-no-parallel":
-            global_config.enable_parallel_decoding = False
             global_config.enable_parallel_encoding = False
         backend = RuntimeEndpoint(f"{args.host}:{args.port}")
     elif args.backend.startswith("gpt-"):