Optimize first token of C++ NPU by adding npu_dpu_groups (#12443)
* add npu_dpu_groups * add check for env * fix style
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2 changed files with 11 additions and 2 deletions
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@ -23,7 +23,8 @@ from intel_npu_acceleration_library.backend.factory import NNFactory
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import numpy as np
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def update_names_of_IR_and_export_blob(model, model_name, dir, compile_blob=True, keep_ir=True):
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def update_names_of_IR_and_export_blob(model, model_name, dir, compile_blob=True, keep_ir=True,
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npu_dpu_groups=None):
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xml_path = os.path.join(dir, model_name + ".xml")
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bin_path = os.path.join(dir, model_name + ".bin")
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model.save(xml_path)
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@ -35,6 +36,11 @@ def update_names_of_IR_and_export_blob(model, model_name, dir, compile_blob=True
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core.set_property("NPU", {"NPU_COMPILATION_MODE_PARAMS":
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"compute-layers-with-higher-precision=Sqrt,Power,ReduceMean,Add"})
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core.set_property("NPU", {"PERFORMANCE_HINT": "LATENCY"})
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if (
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npu_dpu_groups is not None
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and os.environ.get("IPEX_LLM_NPU_DISABLE_COMPILE_OPT", "0") != "1"
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):
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core.set_property("NPU", {"NPU_DPU_GROUPS": str(npu_dpu_groups)})
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model = core.read_model(xml_path)
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inputs = model.inputs
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@ -272,11 +272,13 @@ def convert_llama_layer(model, layer_idx, n_splits_linear, n_splits_down_proj,
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input_len = 1
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decoder_name = f"decoder_layer_{layer_idx}"
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keep_position_ids = True
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npu_dpu_groups = None
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else:
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input_len = kv_len
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decoder_name = "decoder_layer_prefill"
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layernorm_const = False
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keep_position_ids = False
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npu_dpu_groups = 6
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single_decoder = LowBitLlamaMultiDecoderlayer(
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[1, input_len, num_heads * head_dim],
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@ -303,7 +305,8 @@ def convert_llama_layer(model, layer_idx, n_splits_linear, n_splits_down_proj,
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rest_blob_path = update_names_of_IR_and_export_blob(single_decoder,
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decoder_name,
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temp_dir,
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True, False)
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True, False,
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npu_dpu_groups=npu_dpu_groups)
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if mode == "decode":
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if hasattr(curr_layer.self_attn.rotary_emb, "cos_cached"):
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