Optimize qwen2_vl and qwen2_5_vl (#701)
### What this PR does / why we need it? Optimize qwen2_vl and qwen2_5_vl. ### Does this PR introduce _any_ user-facing change? no ### How was this patch tested? Testing this PR on 1080p picture with tp=1, bs=1 on Qwen2-VL and Qwen2.5-VL, every fa op's during time lasting from 11ms to 9ms, got roughly 22% perf boost. --------- Signed-off-by: zouyida2052 <zouyida@huawei.com> Signed-off-by: zouyida2052 <zouyida2002@gmail.com> Co-authored-by: zouyida2052 <zouyida@huawei.com>
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@@ -5,7 +5,9 @@ def register_model():
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from .deepseek_mtp import CustomDeepSeekMTP # noqa: F401
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from .deepseek_v2 import CustomDeepseekV2ForCausalLM # noqa: F401
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from .deepseek_v2 import CustomDeepseekV3ForCausalLM # noqa: F401
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from .qwen2_vl import CustomQwen2VLForConditionalGeneration # noqa: F401
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from .qwen2_5_vl import \
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AscendQwen2_5_VLForConditionalGeneration # noqa: F401
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from .qwen2_vl import AscendQwen2VLForConditionalGeneration # noqa: F401
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ModelRegistry.register_model(
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"DeepSeekMTPModel",
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@@ -13,7 +15,12 @@ def register_model():
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ModelRegistry.register_model(
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"Qwen2VLForConditionalGeneration",
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"vllm_ascend.models.qwen2_vl:CustomQwen2VLForConditionalGeneration")
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"vllm_ascend.models.qwen2_vl:AscendQwen2VLForConditionalGeneration")
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ModelRegistry.register_model(
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"Qwen2_5_VLForConditionalGeneration",
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"vllm_ascend.models.qwen2_5_vl:AscendQwen2_5_VLForConditionalGeneration"
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)
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ModelRegistry.register_model(
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"DeepseekV2ForCausalLM",
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