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未验证 提交 e8b99c75 编写于 作者: C cuicheng01 提交者： GitHub
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Merge pull request #2114 from PaddlePaddle/develop 

Merge develop to release/2.4
上级 24de8fc1 f3f0605c
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Showing with 3439 addition and 397 deletion
deploy/slim/quant_post_static.py
浏览文件 @ e8b99c75
...@@ -41,6 +41,8 @@ def main(): ...@@ -41,6 +41,8 @@ def main():
'inference.pdmodel')) and os.path.exists( 'inference.pdmodel')) and os.path.exists(
os.path.join(config["Global"]["save_inference_dir"], os.path.join(config["Global"]["save_inference_dir"],
'inference.pdiparams')) '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"]["sampler"]["batch_size"] = 1
config["DataLoader"]["Eval"]["loader"]["num_workers"] = 0 config["DataLoader"]["Eval"]["loader"]["num_workers"] = 0
......
docs/en/algorithm_introduction/ImageNet_models_en.md
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...@@ -541,9 +541,9 @@ The accuracy and speed indicators of MobileViT series models are shown in the fo ...@@ -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 | | 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_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> <a name="26"></a>
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docs/en/models/MobileViT_en.md
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...@@ -18,6 +18,6 @@ MobileViT is a lightweight visual Transformer network that can be used as a gene ...@@ -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) | | 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_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/images/PP-HGNet/PP-HGNet-block.png
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docs/images/PP-HGNet/PP-HGNet-block.png
  • 2-up
  • Swipe
  • Onion skin
docs/zh_CN/PULC/PULC_vehicle_attribute.md
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...@@ -178,7 +178,7 @@ from xml.dom.minidom import parse ...@@ -178,7 +178,7 @@ from xml.dom.minidom import parse
vehicleids = [] vehicleids = []
def convert_annotation(input_fp, output_fp): def convert_annotation(input_fp, output_fp, subdir):
in_file = open(input_fp) in_file = open(input_fp)
list_file = open(output_fp, 'w') list_file = open(output_fp, 'w')
tree = parse(in_file) tree = parse(in_file)
...@@ -201,12 +201,12 @@ def convert_annotation(input_fp, output_fp): ...@@ -201,12 +201,12 @@ def convert_annotation(input_fp, output_fp):
typeid = int (item.getAttribute("typeID")) typeid = int (item.getAttribute("typeID"))
label[typeid+9] = '1' label[typeid+9] = '1'
label = ','.join(label) 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() list_file.close()
convert_annotation('train_label.xml', 'train_list.txt') #imagename vehiclenum colorid typeid convert_annotation('train_label.xml', 'train_list.txt', 'image_train') #imagename vehiclenum colorid typeid
convert_annotation('test_label.xml', 'test_list.txt') 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： 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
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...@@ -568,9 +568,9 @@ ViT(Vision Transformer) 与 DeiT（Data-efficient Image Transformers）系列模 ...@@ -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 | | 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_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> <a name="Others"></a>
......
docs/zh_CN/models/MobileViT.md
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...@@ -17,6 +17,6 @@ MobileViT 是一个轻量级的视觉 Transformer 网络，可以用作计算机 ...@@ -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) | | 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_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
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...@@ -5,8 +5,9 @@ ...@@ -5,8 +5,9 @@
- [1.2 模型细节](#1.2) - [1.2 模型细节](#1.2)
- [1.3 实验结果](#1.3) - [1.3 实验结果](#1.3)
- [2. 模型快速体验](#2) - [2. 模型快速体验](#2)
- [2.1 安装 paddleclas](#2.1) - [2.1 安装 paddlepaddle](#2.1)
- [2.2 预测](#2.2) - [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. 模型训练、评估和预测](#3)
- [3.1 环境配置](#3.1) - [3.1 环境配置](#3.1)
- [3.2 数据准备](#3.2) - [3.2 数据准备](#3.2)
...@@ -96,16 +97,35 @@ PP-HGNet 与其他模型的比较如下，其中测试机器为 NVIDIA® Tesla® ...@@ -96,16 +97,35 @@ PP-HGNet 与其他模型的比较如下，其中测试机器为 NVIDIA® Tesla®
<a name="2.1"></a> <a name="2.1"></a>
### 2.1 安装 paddleclas ### 2.1 安装 paddlepaddle
使用如下命令快速安装 paddlepaddle, paddleclas - 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
``` ```
pip3 install paddlepaddle paddleclas
- 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> <a name="2.2"></a>
### 2.2 预测 ### 2.2 安装 paddleclas
使用如下命令快速安装 paddleclas
```
pip3 install paddleclas
```
<a name="2.3"></a>
### 2.3 预测
* 在命令行中使用 PPHGNet_small 的权重快速预测 * 在命令行中使用 PPHGNet_small 的权重快速预测
......
docs/zh_CN/models/PP-LCNet.md
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...@@ -16,8 +16,9 @@ ...@@ -16,8 +16,9 @@
- [1.4.2 基于 V100 GPU 的预测速度](#1.4.2) - [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) - [1.4.3 基于 SD855 的预测速度](#1.4.3)
- [2. 模型快速体验](#2) - [2. 模型快速体验](#2)
- [2.1 安装 paddleclas](#2.1) - [2.1 安装 paddlepaddle](#2.1)
- [2.2 预测](#2.2) - [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. 模型训练、评估和预测](#3)
- [3.1 环境配置](#3.1) - [3.1 环境配置](#3.1)
- [3.2 数据准备](#3.2) - [3.2 数据准备](#3.2)
...@@ -240,16 +241,35 @@ MobileNetV3_large_x0_75 | 64.53 | 151 | ...@@ -240,16 +241,35 @@ MobileNetV3_large_x0_75 | 64.53 | 151 |
<a name="2.1"></a> <a name="2.1"></a>
### 2.1 安装 paddleclas ### 2.1 安装 paddlepaddle
使用如下命令快速安装 paddlepaddle, paddleclas - 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
``` ```
pip3 install paddlepaddle paddleclas
- 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> <a name="2.2"></a>
### 2.2 预测 ### 2.2 安装 paddleclas
使用如下命令快速安装 paddleclas
```
pip3 install paddleclas
```
<a name="2.3"></a>
### 2.3 预测
* 在命令行中使用 PPLCNet_x1_0 的权重快速预测 * 在命令行中使用 PPLCNet_x1_0 的权重快速预测
......
docs/zh_CN/models/PP-LCNetV2.md
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...@@ -14,8 +14,9 @@ ...@@ -14,8 +14,9 @@
- [1.2.5 SE 模块](#1.2.5) - [1.2.5 SE 模块](#1.2.5)
- [1.3 实验结果](#1.3) - [1.3 实验结果](#1.3)
- [2. 模型快速体验](#2) - [2. 模型快速体验](#2)
- [2.1 安装 paddleclas](#2.1) - [2.1 安装 paddlepaddle](#2.1)
- [2.2 预测](#2.2) - [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. 模型训练、评估和预测](#3)
- [3.1 环境配置](#3.1) - [3.1 环境配置](#3.1)
- [3.2 数据准备](#3.2) - [3.2 数据准备](#3.2)
...@@ -120,16 +121,35 @@ PPLCNetV2 目前提供的模型的精度、速度指标及预训练权重链接 ...@@ -120,16 +121,35 @@ PPLCNetV2 目前提供的模型的精度、速度指标及预训练权重链接
<a name="2.1"></a> <a name="2.1"></a>
### 2.1 安装 paddleclas ### 2.1 安装 paddlepaddle
使用如下命令快速安装 paddlepaddle, paddleclas - 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
``` ```
pip3 install paddlepaddle paddleclas
- 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> <a name="2.2"></a>
### 2.2 预测 ### 2.2 安装 paddleclas
使用如下命令快速安装 paddleclas
```
pip3 install paddleclas
```
<a name="2.3"></a>
### 2.3 预测
* 在命令行中使用 PPLCNetV2_base 的权重快速预测 * 在命令行中使用 PPLCNetV2_base 的权重快速预测
......
docs/zh_CN/models/ResNet.md
浏览文件 @ e8b99c75
...@@ -9,8 +9,9 @@ ...@@ -9,8 +9,9 @@
- [1.3.1 基于 V100 GPU 的预测速度](#1.3.1) - [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) - [1.3.2 基于 T4 GPU 的预测速度](#1.3.2)
- [2. 模型快速体验](#2) - [2. 模型快速体验](#2)
- [2.1 安装 paddleclas](#2.1) - [2.1 安装 paddlepaddle](#2.1)
- [2.2 预测](#2.2) - [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. 模型训练、评估和预测](#3)
- [3.1 环境配置](#3.1) - [3.1 环境配置](#3.1)
- [3.2 数据准备](#3.2) - [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 ...@@ -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> <a name="2.1"></a>
### 2.1 安装 paddleclas ### 2.1 安装 paddlepaddle
使用如下命令快速安装 paddlepaddle, paddleclas - 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
``` ```
pip3 install paddlepaddle paddleclas
- 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> <a name="2.2"></a>
### 2.2 预测 ### 2.2 安装 paddleclas
使用如下命令快速安装 paddleclas
```
pip3 install paddleclas
```
<a name="2.3"></a>
### 2.3 预测
* 在命令行中使用 ResNet50 的权重快速预测 * 在命令行中使用 ResNet50 的权重快速预测
......
paddleclas.py
浏览文件 @ e8b99c75
...@@ -340,6 +340,7 @@ def print_info(): ...@@ -340,6 +340,7 @@ def print_info():
first_width = 30 first_width = 30
second_width = total_width - first_width if total_width > 50 else 10 second_width = total_width - first_width if total_width > 50 else 10
except OSError: except OSError:
total_width = 100
second_width = 100 second_width = 100
for series in IMN_MODEL_SERIES: for series in IMN_MODEL_SERIES:
names = textwrap.fill( names = textwrap.fill(
...@@ -452,6 +453,8 @@ class PaddleClas(object): ...@@ -452,6 +453,8 @@ class PaddleClas(object):
"""PaddleClas. """PaddleClas.
""" """
if not os.environ.get('ppcls', False):
os.environ.setdefault('ppcls', 'True')
print_info() print_info()
def __init__(self, def __init__(self,
......
ppcls/arch/backbone/model_zoo/vision_transformer.py
浏览文件 @ e8b99c75
...@@ -62,7 +62,7 @@ def drop_path(x, drop_prob=0., training=False): ...@@ -62,7 +62,7 @@ def drop_path(x, drop_prob=0., training=False):
return x return x
keep_prob = paddle.to_tensor(1 - drop_prob) keep_prob = paddle.to_tensor(1 - drop_prob)
shape = (paddle.shape(x)[0], ) + (1, ) * (x.ndim - 1) 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 random_tensor = paddle.floor(random_tensor) # binarize
output = x.divide(keep_prob) * random_tensor output = x.divide(keep_prob) * random_tensor
return output return output
......
ppcls/arch/slim/quant.py
浏览文件 @ e8b99c75
...@@ -48,6 +48,12 @@ def quantize_model(config, model, mode="train"): ...@@ -48,6 +48,12 @@ def quantize_model(config, model, mode="train"):
QUANT_CONFIG["activation_preprocess_type"] = "PACT" QUANT_CONFIG["activation_preprocess_type"] = "PACT"
if mode in ["infer", "export"]: if mode in ["infer", "export"]:
QUANT_CONFIG['activation_preprocess_type'] = None 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 = QAT(config=QUANT_CONFIG)
model.quanter.quantize(model) model.quanter.quantize(model)
logger.info("QAT model summary:") logger.info("QAT model summary:")
......
ppcls/data/preprocess/ops/operators.py
浏览文件 @ e8b99c75
...@@ -430,7 +430,7 @@ class RandCropImageV2(object): ...@@ -430,7 +430,7 @@ class RandCropImageV2(object):
def __call__(self, img): def __call__(self, img):
if isinstance(img, np.ndarray): 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: else:
img_w, img_h = img.size img_w, img_h = img.size
tw, th = self.size tw, th = self.size
......
ppcls/engine/engine.py
浏览文件 @ e8b99c75
...@@ -466,7 +466,7 @@ class Engine(object): ...@@ -466,7 +466,7 @@ class Engine(object):
# for rep nets # for rep nets
for layer in self.model.sublayers(): for layer in self.model.sublayers():
if hasattr(layer, "rep"): if hasattr(layer, "rep") and not getattr(layer, "is_repped"):
layer.rep() layer.rep()
save_path = os.path.join(self.config["Global"]["save_inference_dir"], save_path = os.path.join(self.config["Global"]["save_inference_dir"],
......
ppcls/engine/evaluation/retrieval.py
浏览文件 @ e8b99c75
...@@ -159,6 +159,14 @@ def cal_feature(engine, name='gallery'): ...@@ -159,6 +159,14 @@ def cal_feature(engine, name='gallery'):
if len(batch) == 3: if len(batch) == 3:
has_unique_id = True has_unique_id = True
batch[2] = batch[2].reshape([-1, 1]).astype("int64") batch[2] = batch[2].reshape([-1, 1]).astype("int64")
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]) out = engine.model(batch[0], batch[1])
if "Student" in out: if "Student" in out:
out = out["Student"] out = out["Student"]
......
ppcls/loss/distillationloss.py
浏览文件 @ e8b99c75
...@@ -236,8 +236,13 @@ class DistillationDKDLoss(DKDLoss): ...@@ -236,8 +236,13 @@ class DistillationDKDLoss(DKDLoss):
temperature=1.0, temperature=1.0,
alpha=1.0, alpha=1.0,
beta=1.0, beta=1.0,
use_target_as_gt=False,
name="loss_dkd"): 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.key = key
self.model_name_pairs = model_name_pairs self.model_name_pairs = model_name_pairs
self.name = name self.name = name
......
ppcls/loss/dkdloss.py
浏览文件 @ e8b99c75
...@@ -10,13 +10,20 @@ class DKDLoss(nn.Layer): ...@@ -10,13 +10,20 @@ class DKDLoss(nn.Layer):
Code was heavily based on https://github.com/megvii-research/mdistiller 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__() super().__init__()
self.temperature = temperature self.temperature = temperature
self.alpha = alpha self.alpha = alpha
self.beta = beta 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) gt_mask = _get_gt_mask(logits_student, target)
other_mask = 1 - gt_mask other_mask = 1 - gt_mask
pred_student = F.softmax(logits_student / self.temperature, axis=1) pred_student = F.softmax(logits_student / self.temperature, axis=1)
......
ppcls/optimizer/optimizer.py
浏览文件 @ e8b99c75
...@@ -16,9 +16,9 @@ from __future__ import absolute_import ...@@ -16,9 +16,9 @@ from __future__ import absolute_import
from __future__ import division from __future__ import division
from __future__ import print_function from __future__ import print_function
from paddle import optimizer as optim import inspect
import paddle
from paddle import optimizer as optim
from ppcls.utils import logger from ppcls.utils import logger
...@@ -49,16 +49,27 @@ class SGD(object): ...@@ -49,16 +49,27 @@ class SGD(object):
learning_rate=0.001, learning_rate=0.001,
weight_decay=None, weight_decay=None,
grad_clip=None, grad_clip=None,
multi_precision=False,
name=None): name=None):
self.learning_rate = learning_rate self.learning_rate = learning_rate
self.weight_decay = weight_decay self.weight_decay = weight_decay
self.grad_clip = grad_clip self.grad_clip = grad_clip
self.multi_precision = multi_precision
self.name = name self.name = name
def __call__(self, model_list): def __call__(self, model_list):
# model_list is None in static graph # model_list is None in static graph
parameters = sum([m.parameters() for m in model_list], parameters = sum([m.parameters() for m in model_list],
[]) if model_list else None []) if model_list else None
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, opt = optim.SGD(learning_rate=self.learning_rate,
parameters=parameters, parameters=parameters,
weight_decay=self.weight_decay, weight_decay=self.weight_decay,
...@@ -242,8 +253,9 @@ class AdamW(object): ...@@ -242,8 +253,9 @@ class AdamW(object):
if self.one_dim_param_no_weight_decay: if self.one_dim_param_no_weight_decay:
self.no_weight_decay_param_name_list += [ self.no_weight_decay_param_name_list += [
p.name for model in model_list p.name
for n, p in model.named_parameters() if len(p.shape) == 1 for model in model_list for n, p in model.named_parameters()
if len(p.shape) == 1
] if model_list else [] ] if model_list else []
opt = optim.AdamW( opt = optim.AdamW(
......
ppcls/utils/logger.py
浏览文件 @ e8b99c75
...@@ -12,11 +12,11 @@ ...@@ -12,11 +12,11 @@
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
import datetime
import logging
import os import os
import sys import sys
import logging
import datetime
import paddle.distributed as dist import paddle.distributed as dist
_logger = None _logger = None
...@@ -39,8 +39,12 @@ def init_logger(name='ppcls', log_file=None, log_level=logging.INFO): ...@@ -39,8 +39,12 @@ def init_logger(name='ppcls', log_file=None, log_level=logging.INFO):
logging.Logger: The expected logger. logging.Logger: The expected logger.
""" """
global _logger global _logger
assert _logger is None, "logger should not be initialized twice or more."
# solve mutiple init issue when using paddleclas.py and engin.engin
init_flag = False
if _logger is None:
_logger = logging.getLogger(name) _logger = logging.getLogger(name)
init_flag = True
formatter = logging.Formatter( formatter = logging.Formatter(
'[%(asctime)s] %(name)s %(levelname)s: %(message)s', '[%(asctime)s] %(name)s %(levelname)s: %(message)s',
...@@ -48,13 +52,32 @@ def init_logger(name='ppcls', log_file=None, log_level=logging.INFO): ...@@ -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 = logging.StreamHandler(stream=sys.stdout)
stream_handler.setFormatter(formatter) stream_handler.setFormatter(formatter)
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) _logger.addHandler(stream_handler)
if log_file is not None and dist.get_rank() == 0: if log_file is not None and dist.get_rank() == 0:
log_file_folder = os.path.split(log_file)[0] log_file_folder = os.path.split(log_file)[0]
os.makedirs(log_file_folder, exist_ok=True) os.makedirs(log_file_folder, exist_ok=True)
file_handler = logging.FileHandler(log_file, 'a') file_handler = logging.FileHandler(log_file, 'a')
file_handler.setFormatter(formatter) file_handler.setFormatter(formatter)
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) _logger.addHandler(file_handler)
if dist.get_rank() == 0: if dist.get_rank() == 0:
_logger.setLevel(log_level) _logger.setLevel(log_level)
else: else:
......
test_tipc/README.md
浏览文件 @ e8b99c75
...@@ -107,6 +107,7 @@ bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/MobileNetV3/Mo ...@@ -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： 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_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_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_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_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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,14 +39,14 @@ infer_export:True ...@@ -39,14 +39,14 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_rec.py -c configs/inference_rec.yaml inference:python/predict_rec.py -c configs/inference_rec.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.rec_inference_model_dir:../inference -o Global.rec_inference_model_dir:../inference
-o Global.infer_imgs:../dataset/Aliproduct/demo_test/ -o Global.infer_imgs:../dataset/Aliproduct/demo_test/
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
null:null null:null
test_tipc/config/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -3,7 +3,7 @@ model_name:MobileNetV3_large_x1_0 ...@@ -3,7 +3,7 @@ model_name:MobileNetV3_large_x1_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
-o Global.device:gpu -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.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/ -o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8 -o DataLoader.Train.sampler.batch_size:8
...@@ -12,16 +12,16 @@ train_model_name:latest ...@@ -12,16 +12,16 @@ train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:norm_train|pact_train|fpgm_train trainer:amp_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 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: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 pact_train:null
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 fpgm_train:null
distill_train:null distill_train:null
null:null null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -33,20 +33,20 @@ fpgm_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_p ...@@ -33,20 +33,20 @@ fpgm_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_p
distill_export:null 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 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 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_model:../inference/
infer_export:null infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
null:null null:null
test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_train_pact_infer_python.txt 0 → 100644
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===========================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
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===========================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
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===========================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
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x0_25_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x0_35_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x0_5_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x0_75_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x1_0_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x1_5_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x2_0_train_pact_infer_python.txt 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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
浏览文件 @ e8b99c75
...@@ -3,7 +3,7 @@ model_name:PPLCNet_x2_5 ...@@ -3,7 +3,7 @@ model_name:PPLCNet_x2_5
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
-o Global.device:gpu -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.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/ -o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8 -o DataLoader.Train.sampler.batch_size:8
...@@ -12,8 +12,8 @@ train_model_name:latest ...@@ -12,8 +12,8 @@ train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:norm_train trainer:amp_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 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ null:null ...@@ -21,7 +21,7 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,13 +39,13 @@ infer_export:True ...@@ -39,13 +39,13 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
test_tipc/config/PPLCNet/PPLCNet_x2_5_train_pact_infer_python.txt 0 → 100644
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===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
浏览文件 @ e8b99c75
===========================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 0 → 100644
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===========================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
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...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val ...@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
null:null null:null
## ##
trainer:amp_train 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 pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,7 +21,7 @@ to_static_train:-o Global.to_static=True ...@@ -21,7 +21,7 @@ to_static_train:-o Global.to_static=True
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml 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 null:null
## ##
===========================infer_params========================== ===========================infer_params==========================
...@@ -39,15 +39,15 @@ infer_export:True ...@@ -39,15 +39,15 @@ infer_export:True
infer_quant:Fasle infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu:True|False -o Global.use_gpu:True|False
-o Global.enable_mkldnn:True|False -o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1|6 -o Global.cpu_num_threads:6
-o Global.batch_size:1|16 -o Global.batch_size:1
-o Global.use_tensorrt:True|False -o Global.use_tensorrt:False
-o Global.use_fp16:True|False -o Global.use_fp16:False
-o Global.inference_model_dir:../inference -o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val -o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.save_log_path:null -o Global.save_log_path:null
-o Global.benchmark:True -o Global.benchmark:False
null:null null:null
null:null null:null
===========================train_benchmark_params========================== ===========================train_benchmark_params==========================
......
test_tipc/config/ResNet/ResNet50_train_pact_infer_python.txt 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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 0 → 100644
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===========================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
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test_tipc/prepare.sh
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test_tipc/test_inference_cpp.sh
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