Disable swa memory for trtllm-mha backend (#17429)
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@@ -101,6 +101,7 @@ class ModelConfig:
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is_multi_layer_eagle: bool = False,
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encoder_only: bool = False,
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language_only: bool = False,
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disable_hybrid_swa_memory: bool = False,
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) -> None:
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# Parse args
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self.model_path = model_path
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@@ -111,6 +112,7 @@ class ModelConfig:
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self.sampling_defaults = sampling_defaults
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self.quantize_and_serve = quantize_and_serve
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self.is_multi_layer_eagle = is_multi_layer_eagle
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self.disable_hybrid_swa_memory = disable_hybrid_swa_memory
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# Validate quantize_and_serve configuration
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self._validate_quantize_and_serve_config()
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@@ -257,6 +259,7 @@ class ModelConfig:
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language_only=server_args.language_only,
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encoder_only=server_args.encoder_only,
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is_draft_model=is_draft_model,
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disable_hybrid_swa_memory=server_args.disable_hybrid_swa_memory,
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**kwargs,
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)
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@@ -310,7 +313,10 @@ class ModelConfig:
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def _derive_hybrid_model(self):
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# Use self.context_len after it has been initialized to prevent using context_len which may be None.
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self.is_hybrid_swa = is_hybrid_swa_model(self.hf_config.architectures)
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self.is_hybrid_swa = (
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is_hybrid_swa_model(self.hf_config.architectures)
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and not self.disable_hybrid_swa_memory
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)
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if self.is_hybrid_swa:
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self.swa_attention_layer_ids, self.full_attention_layer_ids = (
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@@ -1280,9 +1280,9 @@ class ServerArgs:
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or decode_attn_backend == "trtllm_mha"
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):
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# TODO: support swa kv indices translation for trtllm_mha attention backend
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self.swa_full_tokens_ratio = 1.0
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self.disable_hybrid_swa_memory = True
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logger.warning(
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"Set swa_full_tokens_ratio to 1.0 for GPT-OSS model with trtllm_mha attention backend."
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"Disable hybrid SWA memory for GPT-OSS model with trtllm_mha attention backend."
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)
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quant_method = get_quantization_config(hf_config)
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