Merge pull request #2114 from PaddlePaddle/develop

Merge develop to release/2.4

deploy/slim/quant_post_static.py

@@ -41,6 +41,8 @@ def main():
                      'inference.pdmodel')) and os.path.exists(
                          os.path.join(config["Global"]["save_inference_dir"],
                                       'inference.pdiparams'))
+    if "Query" in config["DataLoader"]["Eval"]:
+        config["DataLoader"]["Eval"] = config["DataLoader"]["Eval"]["Query"]
     config["DataLoader"]["Eval"]["sampler"]["batch_size"] = 1
     config["DataLoader"]["Eval"]["loader"]["num_workers"] = 0
 

docs/en/algorithm_introduction/ImageNet_models_en.md

@@ -541,9 +541,9 @@ The accuracy and speed indicators of MobileViT series models are shown in the fo
 
 | Model       | Top-1 Acc | Top-5 Acc | time(ms)<br>bs=1 | time(ms)<br>bs=4 | time(ms)<br/>bs=8 | FLOPs(M) | Params(M) | Pretrained Model Download Address                                               | Inference Model Download Address                                      |
 | ---------- | --------- | --------- | ---------------- | ---------------- | -------- | --------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
-|  MobileViT_XXS    | 0.6867 | 0.8878 | - | - | - | 1849.35  |  5.59   | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_XXS_pretrained.pdparams) | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_XXS_infer.tar) |
+|  MobileViT_XXS    | 0.6867 | 0.8878 | - | - | - | 337.24  |  1.28   | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_XXS_pretrained.pdparams) | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_XXS_infer.tar) |
 |  MobileViT_XS    | 0.7454 | 0.9227 | - | - | - | 930.75  |  2.33   | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_XS_pretrained.pdparams) | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_XS_infer.tar) |
-|  MobileViT_S    | 0.7814 | 0.9413 | - | - | - | 337.24  |   1.28   | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_S_pretrained.pdparams) | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_S_infer.tar) |
+|  MobileViT_S    | 0.7814 | 0.9413 | - | - | - | 1849.35  |   5.59   | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_S_pretrained.pdparams) | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_S_infer.tar) |
 
 <a name="26"></a>
 

docs/en/models/MobileViT_en.md

@@ -18,6 +18,6 @@ MobileViT is a lightweight visual Transformer network that can be used as a gene
 
 | Models           | Top1 | Top5 | Reference<br>top1 | Reference<br>top5 | FLOPs<br>(M) | Params<br>(M) |
 |:--:|:--:|:--:|:--:|:--:|:--:|:--:|
-| MobileViT_XXS    | 0.6867 | 0.8878 | 0.690 | - | 1849.35  | 5.59   |
+| MobileViT_XXS    | 0.6867 | 0.8878 | 0.690 | - | 337.24  | 1.28   |
 | MobileViT_XS    | 0.7454 | 0.9227 | 0.747 | - | 930.75  | 2.33   |
-| MobileViT_S    | 0.7814 | 0.9413 | 0.783 | - | 337.24  | 1.28   |
+| MobileViT_S    | 0.7814 | 0.9413 | 0.783 | - | 1849.35  | 5.59   |

docs/zh_CN/PULC/PULC_vehicle_attribute.md

@@ -58,7 +58,7 @@
 从表中可以看出，backbone 为 Res2Net200_vd_26w_4s 时精度较高，但是推理速度较慢。将 backbone 替换为轻量级模型 MobileNetV3_small_x0_35 后，速度可以大幅提升，但是精度下降明显。将 backbone 替换为 PPLCNet_x1_0 时，精度提升 2 个百分点，同时速度也提升 23% 左右。在此基础上，使用 SSLD 预训练模型后，在不改变推理速度的前提下，精度可以提升约 0.5 个百分点，进一步地，当融合EDA策略后，精度可以再提升 0.52 个百分点，最后，在使用 SKL-UGI 知识蒸馏后，精度可以继续提升 0.23 个百分点。此时，PPLCNet_x1_0 的精度与 Res2Net200_vd_26w_4s 仅相差 0.55 个百分点，但是速度快 32 倍。关于 PULC 的训练方法和推理部署方法将在下面详细介绍。
 
 **备注：**
-    
+
 * 延时是基于 Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz 测试得到，开启 MKLDNN 加速策略，线程数为10。
 * 关于PP-LCNet的介绍可以参考[PP-LCNet介绍](../models/PP-LCNet.md)，相关论文可以查阅[PP-LCNet paper](https://arxiv.org/abs/2109.15099)。
 
@@ -178,7 +178,7 @@ from xml.dom.minidom import parse
 
 vehicleids = []
 
-def convert_annotation(input_fp, output_fp):
+def convert_annotation(input_fp, output_fp, subdir):
     in_file = open(input_fp)
     list_file = open(output_fp, 'w')
     tree = parse(in_file)
@@ -201,12 +201,12 @@ def convert_annotation(input_fp, output_fp):
             typeid = int (item.getAttribute("typeID"))
             label[typeid+9] = '1'
         label = ','.join(label)
-        list_file.write(os.path.join('image_train', name)  + "\t" + label + "\n")
+        list_file.write(os.path.join(subdir, name)  + "\t" + label + "\n")
 
     list_file.close()
 
-convert_annotation('train_label.xml', 'train_list.txt')  #imagename vehiclenum colorid typeid
-convert_annotation('test_label.xml', 'test_list.txt')
+convert_annotation('train_label.xml', 'train_list.txt', 'image_train')  #imagename vehiclenum colorid typeid
+convert_annotation('test_label.xml', 'test_list.txt', 'image_test')
 ```
 
 执行上述命令后，`VeRi`目录中具有以下数据：

docs/zh_CN/algorithm_introduction/ImageNet_models.md

@@ -568,9 +568,9 @@ ViT(Vision Transformer) 与 DeiT（Data-efficient Image Transformers）系列模
 
 | 模型       | Top-1 Acc | Top-5 Acc | time(ms)<br>bs=1 | time(ms)<br>bs=4 | time(ms)<br/>bs=8 | FLOPs(M) | Params(M) | 预训练模型下载地址                                               | inference模型下载地址                                      |
 | ---------- | --------- | --------- | ---------------- | ---------------- | -------- | --------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
-|  MobileViT_XXS    | 0.6867 | 0.8878 | - | - | - | 1849.35  |  5.59   | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_XXS_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_XXS_infer.tar) |
+|  MobileViT_XXS    | 0.6867 | 0.8878 | - | - | - | 337.24  |  1.28   | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_XXS_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_XXS_infer.tar) |
 |  MobileViT_XS    | 0.7454 | 0.9227 | - | - | - | 930.75  |  2.33   | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_XS_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_XS_infer.tar) |
-|  MobileViT_S    | 0.7814 | 0.9413 | - | - | - | 337.24  |   1.28   | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_S_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_S_infer.tar) |
+|  MobileViT_S    | 0.7814 | 0.9413 | - | - | - | 1849.35  |   5.59   | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileViT_S_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileViT_S_infer.tar) |
 
 <a name="Others"></a>
 

docs/zh_CN/models/MobileViT.md

@@ -17,6 +17,6 @@ MobileViT 是一个轻量级的视觉 Transformer 网络，可以用作计算机
 
 | Models           | Top1 | Top5 | Reference<br>top1 | Reference<br>top5 | FLOPs<br>(M) | Params<br>(M) |
 |:--:|:--:|:--:|:--:|:--:|:--:|:--:|
-| MobileViT_XXS    | 0.6867 | 0.8878 | 0.690 | - | 1849.35  | 5.59   |
+| MobileViT_XXS    | 0.6867 | 0.8878 | 0.690 | - | 337.24  | 1.28   |
 | MobileViT_XS    | 0.7454 | 0.9227 | 0.747 | - | 930.75  | 2.33   |
-| MobileViT_S    | 0.7814 | 0.9413 | 0.783 | - | 337.24  | 1.28   |
+| MobileViT_S    | 0.7814 | 0.9413 | 0.783 | - | 1849.35  | 5.59   |

docs/zh_CN/models/PP-HGNet.md

@@ -5,8 +5,9 @@
     - [1.2 模型细节](#1.2)
     - [1.3 实验结果](#1.3)
 - [2. 模型快速体验](#2)
-   - [2.1 安装 paddleclas](#2.1)
-   - [2.2 预测](#2.2)
+    - [2.1 安装 paddlepaddle](#2.1)
+    - [2.2 安装 paddleclas](#2.2)
+    - [2.3 预测](#2.3)
 - [3. 模型训练、评估和预测](#3)
     - [3.1 环境配置](#3.1)
     - [3.2 数据准备](#3.2)
@@ -88,24 +89,43 @@ PP-HGNet 与其他模型的比较如下，其中测试机器为 NVIDIA® Tesla®
 | ResNeXt101_32x48d_wsl    | 85.37      | 97.69       | 55.07       |
 | SwinTransformer_base     | 85.2       | 97.5        | 13.53       |  
 | <b>PPHGNet_base_ssld<b> | <b>85.00<b>| <b>97.35<b> | <b>5.97<b>   |
-
- 
-<a name="2"></a>   
     
+    
+<a name="2"></a>
+
 ## 2. 模型快速体验
 
-<a name="2.1"></a>   
-    
-### 2.1 安装 paddleclas
-    
-使用如下命令快速安装 paddlepaddle, paddleclas
-    
-```    
-pip3 install paddlepaddle paddleclas
+<a name="2.1"></a>  
+
+### 2.1 安装 paddlepaddle
+
+- 您的机器安装的是 CUDA9 或 CUDA10，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
+```
+
+- 您的机器是CPU，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
 ```
-<a name="2.2"></a> 
+
+更多的版本需求，请参照[飞桨官网安装文档](https://www.paddlepaddle.org.cn/install/quick)中的说明进行操作。
+
+<a name="2.2"></a>  
+
+### 2.2 安装 paddleclas
+
+使用如下命令快速安装 paddleclas
+
+```  
+pip3 install paddleclas
+```
+
+<a name="2.3"></a> 
     
-### 2.2 预测
+### 2.3 预测
 
 * 在命令行中使用 PPHGNet_small 的权重快速预测
     

docs/zh_CN/models/PP-LCNet.md

@@ -16,8 +16,9 @@
       - [1.4.2 基于 V100 GPU 的预测速度](#1.4.2)
       - [1.4.3 基于 SD855 的预测速度](#1.4.3)
 - [2. 模型快速体验](#2)
-   - [2.1 安装 paddleclas](#2.1)
-   - [2.2 预测](#2.2)
+    - [2.1 安装 paddlepaddle](#2.1)
+    - [2.2 安装 paddleclas](#2.2)
+    - [2.3 预测](#2.3)
 - [3. 模型训练、评估和预测](#3)
     - [3.1 环境配置](#3.1)
     - [3.2 数据准备](#3.2)
@@ -240,16 +241,35 @@ MobileNetV3_large_x0_75 | 64.53 | 151 |
 
 <a name="2.1"></a>   
     
-### 2.1 安装 paddleclas
-    
-使用如下命令快速安装 paddlepaddle, paddleclas
-    
-```    
-pip3 install paddlepaddle paddleclas
+### 2.1 安装 paddlepaddle
+
+- 您的机器安装的是 CUDA9 或 CUDA10，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
+```
+
+- 您的机器是CPU，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
+```
+
+更多的版本需求，请参照[飞桨官网安装文档](https://www.paddlepaddle.org.cn/install/quick)中的说明进行操作。
+
+<a name="2.2"></a>  
+
+### 2.2 安装 paddleclas
+
+使用如下命令快速安装 paddleclas
+
+```  
+pip3 install paddleclas
 ```
-<a name="2.2"></a> 
     
-### 2.2 预测
+<a name="2.3"></a> 
+    
+### 2.3 预测
 
 * 在命令行中使用 PPLCNet_x1_0 的权重快速预测
     

docs/zh_CN/models/PP-LCNetV2.md

@@ -14,8 +14,9 @@
       - [1.2.5 SE 模块](#1.2.5)     
     - [1.3 实验结果](#1.3)
 - [2. 模型快速体验](#2)
-   - [2.1 安装 paddleclas](#2.1)
-   - [2.2 预测](#2.2)
+    - [2.1 安装 paddlepaddle](#2.1)
+    - [2.2 安装 paddleclas](#2.2)
+    - [2.3 预测](#2.3)
 - [3. 模型训练、评估和预测](#3)
     - [3.1 环境配置](#3.1)
     - [3.2 数据准备](#3.2)
@@ -114,22 +115,41 @@ PPLCNetV2 目前提供的模型的精度、速度指标及预训练权重链接
 | <b>PPLCNetV2_base_ssld<b>  | <b>6.6<b> | <b>604<b>  | <b>80.07<b> | <b>94.87<b> | <b>4.32<b> |
 
 
-<a name="2"></a>   
+<a name="2"></a>    
     
 ## 2. 模型快速体验
 
 <a name="2.1"></a>   
     
-### 2.1 安装 paddleclas
-    
-使用如下命令快速安装 paddlepaddle, paddleclas
-    
-```    
-pip3 install paddlepaddle paddleclas
+### 2.1 安装 paddlepaddle
+
+- 您的机器安装的是 CUDA9 或 CUDA10，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
+```
+
+- 您的机器是CPU，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
+```
+
+更多的版本需求，请参照[飞桨官网安装文档](https://www.paddlepaddle.org.cn/install/quick)中的说明进行操作。
+
+<a name="2.2"></a>  
+
+### 2.2 安装 paddleclas
+
+使用如下命令快速安装 paddleclas
+
+```  
+pip3 install paddleclas
 ```
-<a name="2.2"></a> 
     
-### 2.2 预测
+<a name="2.3"></a> 
+    
+### 2.3 预测
 
 * 在命令行中使用 PPLCNetV2_base 的权重快速预测
     

docs/zh_CN/models/ResNet.md

@@ -9,8 +9,9 @@
       - [1.3.1 基于 V100 GPU 的预测速度](#1.3.1)
       - [1.3.2 基于 T4 GPU 的预测速度](#1.3.2)
 - [2. 模型快速体验](#2)
-   - [2.1 安装 paddleclas](#2.1)
-   - [2.2 预测](#2.2)
+    - [2.1 安装 paddlepaddle](#2.1)
+    - [2.2 安装 paddleclas](#2.2)
+    - [2.3 预测](#2.3)
 - [3. 模型训练、评估和预测](#3)
     - [3.1 环境配置](#3.1)
     - [3.2 数据准备](#3.2)
@@ -131,16 +132,34 @@ PaddleClas 提供的 ResNet 系列的模型包括 ResNet50，ResNet50_vd，ResNe
 
 <a name="2.1"></a>   
     
-### 2.1 安装 paddleclas
-    
-使用如下命令快速安装 paddlepaddle, paddleclas
-    
-```    
-pip3 install paddlepaddle paddleclas
+### 2.1 安装 paddlepaddle
+
+- 您的机器安装的是 CUDA9 或 CUDA10，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
+```
+
+- 您的机器是CPU，请运行以下命令安装
+
+```bash
+python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
+```
+
+更多的版本需求，请参照[飞桨官网安装文档](https://www.paddlepaddle.org.cn/install/quick)中的说明进行操作。
+
+<a name="2.2"></a>  
+
+### 2.2 安装 paddleclas
+
+使用如下命令快速安装 paddleclas
+
+```  
+pip3 install paddleclas
 ```
-<a name="2.2"></a> 
+<a name="2.3"></a> 
     
-### 2.2 预测
+### 2.3 预测
 
 * 在命令行中使用 ResNet50 的权重快速预测
     

paddleclas.py

@@ -340,6 +340,7 @@ def print_info():
         first_width = 30
         second_width = total_width - first_width if total_width > 50 else 10
     except OSError:
+        total_width = 100
         second_width = 100
     for series in IMN_MODEL_SERIES:
         names = textwrap.fill(
@@ -452,7 +453,9 @@ class PaddleClas(object):
     """PaddleClas.
     """
 
-    print_info()
+    if not os.environ.get('ppcls', False):
+        os.environ.setdefault('ppcls', 'True')
+        print_info()
 
     def __init__(self,
                  model_name: str=None,

ppcls/arch/backbone/model_zoo/vision_transformer.py

@@ -62,7 +62,7 @@ def drop_path(x, drop_prob=0., training=False):
         return x
     keep_prob = paddle.to_tensor(1 - drop_prob)
     shape = (paddle.shape(x)[0], ) + (1, ) * (x.ndim - 1)
-    random_tensor = keep_prob + paddle.rand(shape, dtype=x.dtype)
+    random_tensor = keep_prob + paddle.rand(shape).astype(x.dtype)
     random_tensor = paddle.floor(random_tensor)  # binarize
     output = x.divide(keep_prob) * random_tensor
     return output

ppcls/arch/slim/quant.py

@@ -48,6 +48,12 @@ def quantize_model(config, model, mode="train"):
         QUANT_CONFIG["activation_preprocess_type"] = "PACT"
         if mode in ["infer", "export"]:
             QUANT_CONFIG['activation_preprocess_type'] = None
+
+        # for rep nets, convert to reparameterized model first
+        for layer in model.sublayers():
+            if hasattr(layer, "rep"):
+                layer.rep()
+
         model.quanter = QAT(config=QUANT_CONFIG)
         model.quanter.quantize(model)
         logger.info("QAT model summary:")

ppcls/data/preprocess/ops/operators.py

@@ -430,7 +430,7 @@ class RandCropImageV2(object):
 
     def __call__(self, img):
         if isinstance(img, np.ndarray):
-            img_h, img_w = img.shap[0], img.shap[1]
+            img_h, img_w = img.shape[0], img.shape[1]
         else:
             img_w, img_h = img.size
         tw, th = self.size

ppcls/engine/engine.py

@@ -466,7 +466,7 @@ class Engine(object):
 
         # for rep nets
         for layer in self.model.sublayers():
-            if hasattr(layer, "rep"):
+            if hasattr(layer, "rep") and not getattr(layer, "is_repped"):
                 layer.rep()
 
         save_path = os.path.join(self.config["Global"]["save_inference_dir"],

ppcls/engine/evaluation/retrieval.py

@@ -159,7 +159,15 @@ def cal_feature(engine, name='gallery'):
         if len(batch) == 3:
             has_unique_id = True
             batch[2] = batch[2].reshape([-1, 1]).astype("int64")
-        out = engine.model(batch[0], batch[1])
+        if engine.amp and engine.amp_eval:
+            with paddle.amp.auto_cast(
+                    custom_black_list={
+                        "flatten_contiguous_range", "greater_than"
+                    },
+                    level=engine.amp_level):
+                out = engine.model(batch[0], batch[1])
+        else:
+            out = engine.model(batch[0], batch[1])
         if "Student" in out:
             out = out["Student"]
 

ppcls/loss/distillationloss.py

@@ -236,8 +236,13 @@ class DistillationDKDLoss(DKDLoss):
                  temperature=1.0,
                  alpha=1.0,
                  beta=1.0,
+                 use_target_as_gt=False,
                  name="loss_dkd"):
-        super().__init__(temperature=temperature, alpha=alpha, beta=beta)
+        super().__init__(
+            temperature=temperature,
+            alpha=alpha,
+            beta=beta,
+            use_target_as_gt=use_target_as_gt)
         self.key = key
         self.model_name_pairs = model_name_pairs
         self.name = name

ppcls/loss/dkdloss.py

@@ -10,13 +10,20 @@ class DKDLoss(nn.Layer):
     Code was heavily based on https://github.com/megvii-research/mdistiller
     """
 
-    def __init__(self, temperature=1.0, alpha=1.0, beta=1.0):
+    def __init__(self,
+                 temperature=1.0,
+                 alpha=1.0,
+                 beta=1.0,
+                 use_target_as_gt=False):
         super().__init__()
         self.temperature = temperature
         self.alpha = alpha
         self.beta = beta
+        self.use_target_as_gt = use_target_as_gt
 
-    def forward(self, logits_student, logits_teacher, target):
+    def forward(self, logits_student, logits_teacher, target=None):
+        if target is None or self.use_target_as_gt:
+            target = logits_teacher.argmax(axis=-1)
         gt_mask = _get_gt_mask(logits_student, target)
         other_mask = 1 - gt_mask
         pred_student = F.softmax(logits_student / self.temperature, axis=1)

ppcls/optimizer/optimizer.py

@@ -16,9 +16,9 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from paddle import optimizer as optim
-import paddle
+import inspect
 
+from paddle import optimizer as optim
 from ppcls.utils import logger
 
 
@@ -49,21 +49,32 @@ class SGD(object):
                  learning_rate=0.001,
                  weight_decay=None,
                  grad_clip=None,
+                 multi_precision=False,
                  name=None):
         self.learning_rate = learning_rate
         self.weight_decay = weight_decay
         self.grad_clip = grad_clip
+        self.multi_precision = multi_precision
         self.name = name
 
     def __call__(self, model_list):
         # model_list is None in static graph
         parameters = sum([m.parameters() for m in model_list],
                          []) if model_list else None
-        opt = optim.SGD(learning_rate=self.learning_rate,
-                        parameters=parameters,
-                        weight_decay=self.weight_decay,
-                        grad_clip=self.grad_clip,
-                        name=self.name)
+        argspec = inspect.getargspec(optim.SGD.__init__).args
+        if 'multi_precision' in argspec:
+            opt = optim.SGD(learning_rate=self.learning_rate,
+                            parameters=parameters,
+                            weight_decay=self.weight_decay,
+                            grad_clip=self.grad_clip,
+                            multi_precision=self.multi_precision,
+                            name=self.name)
+        else:
+            opt = optim.SGD(learning_rate=self.learning_rate,
+                            parameters=parameters,
+                            weight_decay=self.weight_decay,
+                            grad_clip=self.grad_clip,
+                            name=self.name)
         return opt
 
 
@@ -242,8 +253,9 @@ class AdamW(object):
 
         if self.one_dim_param_no_weight_decay:
             self.no_weight_decay_param_name_list += [
-                p.name for model in model_list
-                for n, p in model.named_parameters() if len(p.shape) == 1
+                p.name
+                for model in model_list for n, p in model.named_parameters()
+                if len(p.shape) == 1
             ] if model_list else []
 
         opt = optim.AdamW(

ppcls/utils/logger.py

@@ -12,11 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import datetime
+import logging
 import os
 import sys
 
-import logging
-import datetime
 import paddle.distributed as dist
 
 _logger = None
@@ -39,8 +39,12 @@ def init_logger(name='ppcls', log_file=None, log_level=logging.INFO):
         logging.Logger: The expected logger.
     """
     global _logger
-    assert _logger is None, "logger should not be initialized twice or more."
-    _logger = logging.getLogger(name)
+
+    #  solve mutiple init issue when using paddleclas.py and engin.engin
+    init_flag = False
+    if _logger is None:
+        _logger = logging.getLogger(name)
+        init_flag = True
 
     formatter = logging.Formatter(
         '[%(asctime)s] %(name)s %(levelname)s: %(message)s',
@@ -48,13 +52,32 @@ def init_logger(name='ppcls', log_file=None, log_level=logging.INFO):
 
     stream_handler = logging.StreamHandler(stream=sys.stdout)
     stream_handler.setFormatter(formatter)
-    _logger.addHandler(stream_handler)
+    stream_handler._name = 'stream_handler'
+
+    # add stream_handler when _logger dose not contain stream_handler
+    for i, h in enumerate(_logger.handlers):
+        if h.get_name() == stream_handler.get_name():
+            break
+        if i == len(_logger.handlers) - 1:
+            _logger.addHandler(stream_handler)
+    if init_flag:
+        _logger.addHandler(stream_handler)
+
     if log_file is not None and dist.get_rank() == 0:
         log_file_folder = os.path.split(log_file)[0]
         os.makedirs(log_file_folder, exist_ok=True)
         file_handler = logging.FileHandler(log_file, 'a')
         file_handler.setFormatter(formatter)
-        _logger.addHandler(file_handler)
+        file_handler._name = 'file_handler'
+
+        # add file_handler when _logger dose not contain same file_handler
+        for i, h in enumerate(_logger.handlers):
+            if h.get_name() == file_handler.get_name() and \
+                    h.baseFilename == file_handler.baseFilename:
+                break
+            if i == len(_logger.handlers) - 1:
+                _logger.addHandler(file_handler)
+
     if dist.get_rank() == 0:
         _logger.setLevel(log_level)
     else:

test_tipc/README.md

@@ -107,6 +107,7 @@ bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/MobileNetV3/Mo
 各功能测试中涉及混合精度、裁剪、量化等训练相关，及mkldnn、Tensorrt等多种预测相关参数配置，请点击下方相应链接了解更多细节和使用教程：
 
 - [test_train_inference_python 使用](docs/test_train_inference_python.md)：测试基于Python的模型训练、评估、推理等基本功能，包括裁剪、量化、蒸馏。
+- [test_train_pact_inference_python 使用](docs/test_train_pact_inference_python.md)：测试基于Python的模型PACT在线量化等基本功能。
 - [test_inference_cpp 使用](docs/test_inference_cpp.md) ：测试基于C++的模型推理。
 - [test_serving 使用](docs/test_serving.md) ：测试基于Paddle Serving的服务化部署功能。
 - [test_lite_arm_cpu_cpp 使用](docs/test_lite_arm_cpu_cpp.md): 测试基于Paddle-Lite的ARM CPU端c++预测部署功能.

test_tipc/config/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_amp_infer_python.txt → test_tipc/config/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,14 +39,14 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_rec.py -c configs/inference_rec.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.rec_inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/Aliproduct/demo_test/
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null
 null:null

test_tipc/config/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=100
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.004 -o Global.pretrained_model="pretrained_model/general_PPLCNet_x2_5_pretrained_v1.0"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/general_PPLCNet_x2_5_pretrained_v1.0.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_rec.py -c configs/inference_rec.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.rec_inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/Aliproduct/demo_test/
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=100
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Global.save_inference_dir=./general_PPLCNet_x2_5_lite_v1.0_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/inference/general_PPLCNet_x2_5_lite_v1.0_infer.tar
+infer_model:./general_PPLCNet_x2_5_lite_v1.0_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_rec.py -c configs/inference_rec.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.rec_inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/Aliproduct/demo_test/
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:MobileNetV3_large_x1_0_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./MobileNetV3_large_x1_0_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/MobileNetV3_large_x1_0_pact_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:MobileNetV3_large_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/MobileNetV3_large_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:MobileNetV3_large_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/MobileNetV3_large_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -3,7 +3,7 @@ model_name:MobileNetV3_large_x1_0
 python:python3.7
 gpu_list:0|0,1
 -o Global.device:gpu
--o Global.auto_cast:amp
+-o Global.auto_cast:null
 -o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
 -o Global.output_dir:./output/
 -o DataLoader.Train.sampler.batch_size:8
@@ -12,16 +12,16 @@ train_model_name:latest
 train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
-trainer:norm_train|pact_train|fpgm_train
-norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
-pact_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
-fpgm_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+trainer:amp_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
+pact_train:null
+fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -33,20 +33,20 @@ fpgm_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_p
 distill_export:null
 kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.save_inference_dir=./inference
 export2:null
-inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/MobileNetV3_large_x1_0_inference.tar
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x1_0_pretrained.pdparams
 infer_model:../inference/
-infer_export:null
+infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null
 null:null

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:MobileNetV3_large_x1_0
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/MobileNetV3_large_x1_0_pretrained"
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x1_0_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:256|640
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:MobileNetV3_large_x1_0
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+fpgm_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml
+quant_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml
+fpgm_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.save_inference_dir=./MobileNetV3_large_x1_0_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileNetV3_large_x1_0_infer.tar
+infer_model:./MobileNetV3_large_x1_0_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:256|640
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./general_PPLCNet_x2_5_lite_v1.0_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_pact_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPHGNet_small_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./PPHGNet_small_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPHGNet/PPHGNet_small_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPHGNet_small_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./PPHGNet_small_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_pact_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPHGNet/PPHGNet_small_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_pact_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPHGNet/PPHGNet_small_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_pact_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPHGNet/PPHGNet_small_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

+===========================train_params===========================
+model_name:PPHGNet_small
+python:python3.7
+gpu_list:0|0,1
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:amp_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_small_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null

test_tipc/config/PPHGNet/PPHGNet_small_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPHGNet_small
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/PPHGNet_small_pretrained" -o AMP=None
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_small_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml -o PreProcess.transform_ops.0.ResizeImage.resize_short=236
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPHGNet/PPHGNet_small_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPHGNet_small
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Global.save_inference_dir=./PPHGNet_small_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_small_infer.tar
+infer_model:./PPHGNet_small_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml -o PreProcess.transform_ops.0.ResizeImage.resize_short=236
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPHGNet/PPHGNet_tiny_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

+===========================train_params===========================
+model_name:PPHGNet_tiny
+python:python3.7
+gpu_list:0|0,1
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:amp_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_tiny_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null

test_tipc/config/PPHGNet/PPHGNet_tiny_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPHGNet_tiny
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/PPHGNet_tiny_pretrained" -o AMP=None
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_tiny_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml -o PreProcess.transform_ops.0.ResizeImage.resize_short=236
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPHGNet/PPHGNet_tiny_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPHGNet_tiny
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Global.save_inference_dir=./PPHGNet_tiny_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_tiny_infer.tar
+infer_model:./PPHGNet_tiny_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml -o PreProcess.transform_ops.0.ResizeImage.resize_short=236
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPLCNet/PPLCNet_x0_25_train_amp_infer_python.txt → test_tipc/config/PPLCNet/PPLCNet_x0_25_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x0_25_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_25
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_25_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_25_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_25_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_25
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Global.save_inference_dir=./PPLCNet_x0_25_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_25_infer.tar
+infer_model:./PPLCNet_x0_25_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_35_train_amp_infer_python.txt → test_tipc/config/PPLCNet/PPLCNet_x0_35_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x0_35_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_35
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_35_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_35_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_35_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_35
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Global.save_inference_dir=./PPLCNet_x0_35_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_35_infer.tar
+infer_model:./PPLCNet_x0_35_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_5_train_amp_infer_python.txt → test_tipc/config/PPLCNet/PPLCNet_x0_5_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x0_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_5_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_5_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_5_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Global.save_inference_dir=./PPLCNet_x0_5_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_5_infer.tar
+infer_model:./PPLCNet_x0_5_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_75_train_amp_infer_python.txt → test_tipc/config/PPLCNet/PPLCNet_x0_75_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x0_75_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_75
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_75_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_75_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_75_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_75
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Global.save_inference_dir=./PPLCNet_x0_75_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_75_infer.tar
+infer_model:./PPLCNet_x0_75_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNet_x1_0_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNet_x1_0_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNet_x1_0_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNet_x1_0_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_pact_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_train_amp_infer_python.txt → test_tipc/config/PPLCNet/PPLCNet_x1_0_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x1_0_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x1_0
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x1_0_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x1_0_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x1_0_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x1_0
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Global.save_inference_dir=./PPLCNet_x1_0_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x1_0_infer.tar
+infer_model:./PPLCNet_x1_0_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x1_5_train_amp_infer_python.txt → test_tipc/config/PPLCNet/PPLCNet_x1_5_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x1_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x1_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x1_5_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x1_5_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x1_5_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x1_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Global.save_inference_dir=./PPLCNet_x1_5_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x1_5_infer.tar
+infer_model:./PPLCNet_x1_5_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x2_0_train_amp_infer_python.txt → test_tipc/config/PPLCNet/PPLCNet_x2_0_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x2_0_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_0
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x2_0_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_0_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x2_0_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_0
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Global.save_inference_dir=./PPLCNet_x2_0_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x2_0_infer.tar
+infer_model:./PPLCNet_x2_0_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x2_5_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -3,7 +3,7 @@ model_name:PPLCNet_x2_5
 python:python3.7
 gpu_list:0|0,1
 -o Global.device:gpu
--o Global.auto_cast:amp
+-o Global.auto_cast:null
 -o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
 -o Global.output_dir:./output/
 -o DataLoader.Train.sampler.batch_size:8
@@ -12,16 +12,16 @@ train_model_name:latest
 train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
-trainer:norm_train
-norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+trainer:amp_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,13 +39,13 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null

test_tipc/config/PPLCNet/PPLCNet_x2_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x2_5_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_5_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x2_5_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Global.save_inference_dir=./PPLCNet_x2_5_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x2_5_infer.tar
+infer_model:./PPLCNet_x2_5_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNetV2_base_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNetV2_base_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNetV2_base_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNetV2_base_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_pact_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

+===========================train_params===========================
+model_name:PPLCNetV2_base
+python:python3.7
+gpu_list:0|0,1
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:null
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:amp_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Global.seed=1234 -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNetV2_base_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null

test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNetV2_base
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.first_bs:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Global.seed=1234 -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNetV2_base_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNetV2_base_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNetV2_base
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.first_bs:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Global.seed=1234 -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Global.save_inference_dir=./PPLCNetV2_base_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNetV2_base_infer.tar
+infer_model:./PPLCNetV2_base_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/ResNet/ResNet50_train_purefp16_infer_python.txt → test_tipc/config/ResNet/ResNet50_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,15 +13,15 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50_amp_O1.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Optimizer.multi_precision=True
 pact_train:null
 fpgm_train:null
 distill_train:null
 to_static_train:-o Global.to_static=True
 null:null
 ##
-===========================eval_params=========================== 
-eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 null:null
 ##
 ===========================infer_params==========================
@@ -39,15 +39,15 @@ infer_export:True
 infer_quant:Fasle
 inference:python/predict_cls.py -c configs/inference_cls.yaml
 -o Global.use_gpu:True|False
--o Global.enable_mkldnn:True|False
--o Global.cpu_num_threads:1|6
--o Global.batch_size:1|16
--o Global.use_tensorrt:True|False
--o Global.use_fp16:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:6
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
 -o Global.inference_model_dir:../inference
 -o Global.infer_imgs:../dataset/ILSVRC2012/val
 -o Global.save_log_path:null
--o Global.benchmark:True
+-o Global.benchmark:False
 null:null
 null:null
 ===========================train_benchmark_params==========================

test_tipc/config/ResNet/ResNet50_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:ResNet50
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/ResNet50_pretrained"
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet50_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../dataset/ILSVRC2012/val
+-o Global.save_log_path:null
+-o Global.benchmark:True
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:128
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/ResNet/ResNet50_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:ResNet50
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=200
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
+pact_train:null
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Global.save_inference_dir=./ResNet50_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/ResNet50_infer.tar
+infer_model:./ResNet50_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-o Global.use_gpu:True|False
+-o Global.enable_mkldnn:False
+-o Global.cpu_num_threads:1
+-o Global.batch_size:1
+-o Global.use_tensorrt:False
+-o Global.use_fp16:False
+-o Global.inference_model_dir:../inference
+-o Global.infer_imgs:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:128
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/ResNet/ResNet50_vd_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:ResNet50_vd_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./ResNet50_vd_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/ResNet50_vd_pact_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/ResNet/ResNet50_vd_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:ResNet50_vd_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/ResNet50_vd_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/ResNet50_vd_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/ResNet50_vd_pact_serving/
+--serving_client:./deploy/paddleserving/ResNet50_vd_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/ResNet/ResNet50_vd_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:ResNet50_vd_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/ResNet50_vd_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/ResNet50_vd_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/ResNet50_vd_pact_serving/
+--serving_client:./deploy/paddleserving/ResNet50_vd_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py