Remove deprecated configs (#1431)
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@@ -63,7 +63,7 @@ from sglang.srt.managers.schedule_batch import Req, ScheduleBatch
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from sglang.srt.model_executor.model_runner import ModelRunner
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from sglang.srt.sampling.sampling_params import SamplingParams
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from sglang.srt.server_args import ServerArgs
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from sglang.srt.utils import suppress_other_loggers
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from sglang.srt.utils import kill_child_process, suppress_other_loggers
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@dataclasses.dataclass
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@@ -502,4 +502,9 @@ if __name__ == "__main__":
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format="%(message)s",
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)
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main(server_args, bench_args)
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try:
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main(server_args, bench_args)
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except Exception as e:
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raise e
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finally:
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kill_child_process(os.getpid(), including_parent=False)
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@@ -1,5 +1,7 @@
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"""Global configurations"""
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import os
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class GlobalConfig:
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def __init__(self):
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@@ -16,30 +18,20 @@ class GlobalConfig:
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self.base_min_new_token_ratio = 0.1
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self.new_token_ratio_decay = 0.001
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# Runtime constants: The threshold (number of tokens) to trigger layer-wise cuda sync.
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# This can improve the speed for large batch sizes during prefill.
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self.layer_sync_threshold = 8192
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# Runtime constants: others
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self.num_continue_decode_steps = 10
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self.retract_decode_steps = 20
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self.flashinfer_workspace_size = 384 * 1024 * 1024
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self.flashinfer_workspace_size = os.environ.get(
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"FLASHINFER_WORKSPACE_SIZE", 384 * 1024 * 1024
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)
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# Output tokenization configs
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self.skip_special_tokens_in_output = True
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self.spaces_between_special_tokens_in_out = True
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# Interpreter optimization configs
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self.eager_fill_image = False
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self.enable_precache_with_tracing = True
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self.enable_parallel_encoding = True
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self.enable_parallel_decoding = True
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# Deprecated
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# Choices: ["no_adjust", "adjust_cache"]
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# no_adjust: Do not adjust the position embedding of KV cache.
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# adjust_cache: Adjust the position embedding of KV cache.
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self.concate_and_append_mode = "no_adjust"
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global_config = GlobalConfig()
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@@ -434,9 +434,6 @@ class StreamExecutor:
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self.cur_images.append((path, base64_data))
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self.text_ += self.chat_template.image_token
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# if global_config.eager_fill_image:
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# self.backend.fill_image(self)
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def _spec_gen(self, sampling_params):
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stop = sampling_params.stop
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max_new_tokens = sampling_params.max_new_tokens
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@@ -150,7 +150,7 @@ class FlashInferAttnBackend(AttentionBackend):
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# Some heuristics to check whether to use ragged forward
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use_ragged = False
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if (
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int(torch.sum(input_metadata.seq_lens)) > 4096
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torch.sum(input_metadata.seq_lens).item() >= 4096
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and self.model_runner.sliding_window_size is None
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):
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use_ragged = True
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@@ -301,10 +301,6 @@ class FlashInferAttnBackend(AttentionBackend):
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layer.layer_id, input_metadata.out_cache_loc, k, v
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)
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if total_num_tokens >= global_config.layer_sync_threshold:
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# TODO: Revisit this. Why is this synchronize needed?
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torch.cuda.synchronize()
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return o.view(-1, layer.tp_q_head_num * layer.head_dim)
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def forward_decode(self, q, k, v, layer: nn.Module, input_metadata: InputMetadata):
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@@ -304,7 +304,6 @@ def add_common_sglang_args_and_parse(parser: argparse.ArgumentParser):
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def select_sglang_backend(args: argparse.Namespace):
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if args.backend.startswith("srt"):
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if args.backend == "srt-no-parallel":
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global_config.enable_parallel_decoding = False
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global_config.enable_parallel_encoding = False
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backend = RuntimeEndpoint(f"{args.host}:{args.port}")
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elif args.backend.startswith("gpt-"):
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