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59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
import os
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# os.environ["CUDA_VISIBLE_DEVICES"]="1,2"
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# add path
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import sys
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current_path = os.path.abspath(os.path.dirname(__file__))
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sys.path.append(current_path+"/../..")
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import numpy as np
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# from ktransformers.operators.linear import KTransformersLinear, KLinearMarlin
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# from ktransformers.operators.experts import KTransformersExperts, KExpertsTorch
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from ktransformers.util.custom_gguf import GGUFLoader
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import torch
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import KTransformersOps
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torch.set_default_dtype(torch.bfloat16)
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import time
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from transformers import (
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AutoConfig,
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)
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import os
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# CUDA_LAUNCH_BLOCKING=1
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os.environ["CUDA_LAUNCH_BLOCKING"]="1"
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gguf_config = GGUFLoader("/data/Qwen2-57B-A14B-Instruct-GGUF/q4_k_m")
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model_name = "/data/Qwen2-57B-A14B-Instruct"
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# Q4k
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key = "blk.1."
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target = "attn_q.weight"
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t1 = time.time()
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q_weight_cpu = gguf_config.load_gguf_tensor(key+target, "cpu")
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# q_weight_cpu = torch.from_numpy(q_weight_cpu)
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t2 = time.time()
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q_weight_gpu = gguf_config.load_gguf_tensor(key+target, "cuda:0")
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t3 = time.time()
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print()
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allclose = torch.allclose(q_weight_cpu, q_weight_gpu.cpu(), atol=1e-6)
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print(f"Q4k {key+target}")
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print("load gguf tensor from cpu cost: ", t2-t1)
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print("load gguf tensor from gpu cost: ", t3-t2)
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print("allclose: ", allclose)
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# Q6k
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key = "blk.0."
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target = "ffn_down_exps.weight"
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t1 = time.time()
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q_weight_cpu = gguf_config.load_gguf_tensor(key+target, "cpu")
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t2 = time.time()
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q_weight_gpu = gguf_config.load_gguf_tensor(key+target, "cuda:0")
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t3 = time.time()
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print()
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allclose = torch.allclose(q_weight_cpu, q_weight_gpu.cpu().to(torch.float32), atol=1e-6)
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print(f"Q6k {key+target}")
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print("load gguf tensor from cpu cost: ", t2-t1)
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print("load gguf tensor from gpu cost: ", t3-t2)
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print("allclose: ", allclose)
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