[Inference] update fakequant support (PaddlePaddle#9047)

* 1. add a8w8(fp8) a8w8c8(int8) quant_type support
2. add llama3.1 and qwen2 ptq config
3. update quantization.md

* fix load_quant_model bug

* fix load quant bug

* update ll/README.md

* remove useless code

* update quant observer config

* resolve wrong modify

* fix prepare_qconfig

* remove unuse files

Author: lixcli

llm/README.md

@@ -224,13 +224,13 @@ python -u  -m paddle.distributed.launch --gpus "0,1,2,3,4,5,6,7" ./alignment/dpo
 
 ```shell
 # PTQ 量化启动命令参考
-python  run_finetune.py ./config/llama/ptq_argument.json
+python run_finetune.py ./config/llama/ptq_argument.json
 
 # GPTQ 量化启动命令参考
-python  run_finetune.py ./config/llama/ptq_argument.json
+python run_finetune.py ./config/llama/ptq_argument.json
 
 # W8A8C8(INT)量化启动命令参考
-python  run_finetune.py ./config/llama/ptq_c8_argument.json
+python run_finetune.py ./config/llama/ptq_c8_argument.json
 
 # W8A8(FP8)量化启动命令参考
 python run_finetune.py ./config/llama/fp8_ptq_argument.json

llm/docs/quantization.md

@@ -1,4 +1,4 @@
-# 大模型量化教程
+p# 大模型量化教程
 
 ## 1.算法介绍
 
@@ -111,8 +111,8 @@ python run_finetune.py ./config/llama/ceval_quant_argument.json
 - `use_fp8`: 是否使用 FP8 量化，默认为空字符串。输入`"WA"`(不区分大小写)则将权重和激活的8位量化转换为 FP8量化。
 - `fp8_type`: FP8量化类型，长度应与`use_fp8`相同。默认为`["e4m3","e4m3"]`。
 - `do_ptq`: 是否进行 PTQ 量化，默认为 False。
-- `weight_quant_method`: 权重量化方式，现可选 groupwise 或者 abs_max_channel_wise。
-- `act_quant_method`: 激活量化方式，现可选 avg 或者 abs_max。
+- `weight_quant_method`: 权重量化方式，INT8量化可选 groupwise 或者 abs_max_channel_wise，FP8量化可选 abs_max 或 avg。
+- `act_quant_method`: 激活量化方式，INT8可选 avg 或者 abs_max，FP8量化可选 abs_max 或 avg。
 - `cachekv_quant_method`: kvcache 量化方式，现可选 abs_max_headwise, avg_headwise。
 - `ptq_step`: PTQ 量化步数，也即模型前向次数，默认为32。
 - `shift`: 是否在 PTQ 量化前进行[Shift 策略](https://arxiv.org/abs/2304.09145)，默认为 False。使用 Shift 策略需要设`do_ptq`为 True。

llm/experimental/ceval/default/eval.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -36,25 +36,20 @@ def run_eval_one_time(args, evaluator, take):
     subject_list = [val_file.replace("_val.csv", "") for val_file in filenames]
     accuracy, summary = {}, {}
 
-    # run_date = time.strftime("%Y-%m-%d_%H-%M-%S", time.localtime(time.time()))
     output_dir = args.output_dir
     save_result_dir = os.path.join(output_dir, f"take{take}")
     if not os.path.exists(save_result_dir):
         os.makedirs(save_result_dir, exist_ok=True)
 
     all_answers = {}
     for index, subject_name in enumerate(subject_list):
-        # print(
-        #     f"{index/len(subject_list)} Inference starts at {run_date} on {args.model_name_or_path} with subject of {subject_name}!"
-        # )
         val_file_path = os.path.join(val_path, f"{subject_name}_val.csv")
         dev_file_path = os.path.join(dev_path, f"{subject_name}_dev.csv")
         test_file_path = os.path.join(test_path, f"{subject_name}_test.csv")
 
         val_df = pd.read_csv(val_file_path) if args.do_test is False else pd.read_csv(test_file_path)
         dev_df = pd.read_csv(dev_file_path) if args.few_shot else None
 
-        # import pdb;pdb.set_trace()
         correct_ratio, answers = evaluator.eval_subject(
             subject_name,
             val_df,

llm/experimental/ceval/default/evaluator.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

llm/experimental/ceval/default/model_evaluator.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

llm/experimental/layers/cache_kv.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -166,13 +166,7 @@ def forward(
 
     def _smooth(self, x, y, use_smooth_x):
         # For ShiftSmooth
-        # smooth_shape = y.shape[2:]
         self.dtype = y.dtype
-        # if not hasattr(self, "smooth_weight"):
-        #     self.smooth_weight = self.create_parameter(
-        #         shape=smooth_shape,
-        #         attr=ParamAttr(initializer=Constant(value=1.)),
-        #         dtype=self.dtype)
         smooth_y = y
         smooth_y = paddle.divide(smooth_y, self.smooth_weight)
 

llm/experimental/layers/custom_attention.py

@@ -58,7 +58,6 @@ def forward(
         **kwargs
     ):
         """forward"""
-        # import pdb;pdb.set_trace()
         if self.enable_fake_quant:
             self.collect_kv_quant_policy(q, k, v, **kwargs)
         perm = [0, 2, 1, 3]  # [1, 2, 0, 3] if self.sequence_parallel else [0, 2, 1, 3]

llm/experimental/observer/abs_max_headwise.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -14,8 +14,6 @@
 
 import numpy as np
 import paddle
-
-# from paddleslim.quant.observers.channel_wise import ChannelWiseObserver
 from experimental.observer.channel_wise import ChannelWiseObserver
 from paddle.quantization.factory import ObserverFactory
 

llm/experimental/observer/avg_headwise.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

llm/experimental/observer/channel_wise.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -14,13 +14,8 @@
 
 from typing import Dict
 
-# import numpy as np
 import paddle
-
-# from paddle.quantization.factory import ObserverFactory
 from experimental.layers.cache_kv import CacheKVMatMul
-
-# from paddleslim.quant.observers.mse import MSEObserverLayer
 from paddleslim.quant.observers.uniform import UniformObserver
 
 CHANNEL_AXIS: Dict[type, int] = {