diff --git a/deploy/python/preprocess.py b/deploy/python/preprocess.py index 5d7fc929675267100f324d014c1e3a4c630b975f..1da32ad6e38028daf1a6708904c4fcdb6089a2f9 100644 --- a/deploy/python/preprocess.py +++ b/deploy/python/preprocess.py @@ -79,7 +79,7 @@ class UnifiedResize(object): if isinstance(interpolation, str): interpolation = _cv2_interp_from_str[interpolation.lower()] # compatible with opencv < version 4.4.0 - elif not interpolation: + elif interpolation is None: interpolation = cv2.INTER_LINEAR self.resize_func = partial(cv2.resize, interpolation=interpolation) elif backend.lower() == "pil": diff --git a/docs/zh_CN/tutorials/getting_started_retrieval.md b/docs/zh_CN/tutorials/getting_started_retrieval.md index a0695d88c1cd2f9a1ef1bc93cabb17276eddf5a9..12c54cd87771e0136ee59d71154cfb212f80a14d 100644 --- a/docs/zh_CN/tutorials/getting_started_retrieval.md +++ b/docs/zh_CN/tutorials/getting_started_retrieval.md @@ -214,7 +214,7 @@ python3 tools/export_model.py \ 其中，`Global.pretrained_model`用于指定模型文件路径，该路径仍无需包含模型文件后缀名（如[2.2 模型恢复训练](#模型恢复训练)）。当执行后，会在当前目录下生成`./inference`目录，目录下包含`inference.pdiparams`、`inference.pdiparams.info`、`inference.pdmodel`文件。`Global.save_inference_dir`可以指定导出inference模型的路径。此处保存的inference模型在embedding特征层做了截断，即模型最终的输出为n维embedding特征。 -上述命令将生成模型结构文件（`inference.pdmodel`）和模型权重文件（`inference.pdiparams`），然后可以使用预测引擎进行推理。使用inference模型推理的流程可以参考[基于Python预测引擎预测推理](@shengyu)。 +上述命令将生成模型结构文件（`inference.pdmodel`）和模型权重文件（`inference.pdiparams`），然后可以使用预测引擎进行推理。使用inference模型推理的流程可以参考[基于Python预测引擎预测推理](https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/inference.md)。 ## 基础知识 diff --git a/docs/zh_CN_tmp/image_recognition_pipeline/mainbody_detection.md b/docs/zh_CN_tmp/image_recognition_pipeline/mainbody_detection.md new file mode 100644 index 0000000000000000000000000000000000000000..8431edb144c51c3891e914550dbaa70b2ba1c8ee --- /dev/null +++ b/docs/zh_CN_tmp/image_recognition_pipeline/mainbody_detection.md @@ -0,0 +1,218 @@ +# 主体检测 + + +主体检测技术是目前应用非常广泛的一种检测技术，它指的是检测出图片中一个或者多个主体的坐标位置，然后将图像中的对应区域裁剪下来，进行识别，从而完成整个识别过程。主体检测是识别任务的前序步骤，可以有效提升识别精度。 + +本部分主要从数据集、模型选择和模型训练 3 个方面对该部分内容进行介绍。 + +## 1. 数据集 + +在 PaddleClas 的识别任务中，训练主体检测模型时主要用到了以下几个数据集。 + +| 数据集 | 数据量 | 主体检测任务中使用的数据量 | 场景 | 数据集地址 | +| :------------: | :-------------: | :-------: | :-------: | :--------: | +| Objects365 | 170W | 6k | 通用场景 | [地址](https://www.objects365.org/overview.html) | +| COCO2017 | 12W | 5k | 通用场景 | [地址](https://cocodataset.org/) | +| iCartoonFace | 2k | 2k | 动漫人脸检测 | [地址](https://github.com/luxiangju-PersonAI/iCartoonFace) | +| LogoDet-3k | 3k | 2k | Logo检测 | [地址](https://github.com/Wangjing1551/LogoDet-3K-Dataset) | +| RPC | 3k | 3k | 商品检测 | [地址](https://rpc-dataset.github.io/) | + +在实际训练的过程中，将所有数据集混合在一起。由于是主体检测，这里将所有标注出的检测框对应的类别都修改为 `前景` 的类别，最终融合的数据集中只包含 1 个类别，即前景。 + + +## 2. 模型选择 + +目标检测方法种类繁多，比较常用的有两阶段检测器（如FasterRCNN系列等）；单阶段检测器（如YOLO、SSD等）；anchor-free检测器（如PicoDet、FCOS等）。PaddleDetection中针对服务端使用场景，自研了 PP-YOLO 系列模型；针对端侧（CPU和移动端等）使用场景，自研了 PicoDet 系列模型，在服务端和端侧均处于业界较为领先的水平。 + +基于上述研究，PaddleClas 中提供了 2 个通用主体检测模型，为轻量级与服务端主体检测模型，分别适用于端侧场景以及服务端场景。下面的表格中给出了在上述 5 个数据集上的平均 mAP 以及它们的模型大小、预测速度对比信息。 + +| 模型 | 模型结构 | 预训练模型下载地址 | inference模型下载地址 | mAP | inference模型大小(MB) | 单张图片预测耗时(不包含预处理)(ms) | +| :------------: | :-------------: | :------: | :-------: | :--------: | :-------: | :--------: | +| 轻量级主体检测模型 | PicoDet | [地址](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_pretrained.pdparams) | [地址](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/inference/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_infer.tar) | 40.1% | 30.1 | 29.8 | +| 服务端主体检测模型 | PP-YOLOv2 | [地址](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/ppyolov2_r50vd_dcn_mainbody_v1.0_pretrained.pdparams) | [地址](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/inference/ppyolov2_r50vd_dcn_mainbody_v1.0_infer.tar) | 42.5% | 210.5 | 466.6 | + + +* 注意 + * 速度评测机器的CPU具体信息为：`Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz`，速度指标为开启 mkldnn ，线程数设置为 10 测试得到。 + * 主体检测的预处理过程较为耗时，平均每张图在上述机器上的时间在 40~55 ms 左右，没有包含在上述的预测耗时统计中。 + + +### 2.1 轻量级主体检测模型 + +PicoDet 由 [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection) 提出，是一个适用于CPU或者移动端场景的目标检测算法。具体地，它融合了下面一系列优化算法。 + +- [ATSS](https://arxiv.org/abs/1912.02424) +- [Generalized Focal Loss](https://arxiv.org/abs/2006.04388) +- 余弦学习率策略 +- Cycle-EMA +- 轻量级检测 head + + +更多关于 PicoDet 的优化细节与 benchmark 可以参考 [PicoDet 系列模型介绍](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/picodet/README.md)。 + +在轻量级主体检测任务中，为了更好地兼顾检测速度与效果，我们使用 PPLCNet_x2_5 作为主体检测模型的骨干网络，同时将训练与预测的图像尺度修改为了 640x640，其余配置与 [picodet_m_shufflenetv2_416_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/picodet/picodet_m_shufflenetv2_416_coco.yml)完全一致。将数据集更换为自定义的主体检测数据集，进行训练，最终得到检测模型。 + + +### 2.2 服务端主体检测模型 + +PP-YOLO 由 [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection) 提出，从骨干网络、数据增广、正则化策略、损失函数、后处理等多个角度对 yolov3 模型进行深度优化，最终在"速度-精度"方面达到了业界领先的水平。具体地，优化的策略如下。 + +- 更优的骨干网络: ResNet50vd-DCN +- 更大的训练batch size: 8 GPUs，每GPU batch_size=24，对应调整学习率和迭代轮数 +- [Drop Block](https://arxiv.org/abs/1810.12890) +- [Exponential Moving Average](https://www.investopedia.com/terms/e/ema.asp) +- [IoU Loss](https://arxiv.org/pdf/1902.09630.pdf) +- [Grid Sensitive](https://arxiv.org/abs/2004.10934) +- [Matrix NMS](https://arxiv.org/pdf/2003.10152.pdf) +- [CoordConv](https://arxiv.org/abs/1807.03247) +- [Spatial Pyramid Pooling](https://arxiv.org/abs/1406.4729) +- 更优的预训练模型 + +更多关于 PP-YOLO 的详细介绍可以参考：[PP-YOLO 模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release%2F2.1/configs/ppyolo/README_cn.md)。 + +在服务端主体检测任务中，为了保证检测效果，我们使用 ResNet50vd-DCN 作为检测模型的骨干网络，使用配置文件 [ppyolov2_r50vd_dcn_365e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) ，更换为自定义的主体检测数据集，进行训练，最终得到检测模型。 + + +## 3. 模型训练 + +本节主要介绍怎样基于PaddleDetection，基于自己的数据集，训练主体检测模型。 + +### 3.1 环境准备 + +下载PaddleDetection代码，安装requirements。 + +```shell +cd +git clone https://github.com/PaddlePaddle/PaddleDetection.git + +cd PaddleDetection +# 安装其他依赖 +pip install -r requirements.txt +``` + +更多安装教程，请参考: [安装文档](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/docs/tutorials/INSTALL_cn.md) + +### 3.2 数据准备 + +对于自定义数据集，首先需要将自己的数据集修改为COCO格式，可以参考[自定义检测数据集教程](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/tutorials/Custom_DataSet.md)制作COCO格式的数据集。 + +主体检测任务中，所有的检测框均属于前景，在这里需要将标注文件中，检测框的`category_id`修改为1，同时将整个标注文件中的`categories`映射表修改为下面的格式，即整个类别映射表中只包含`前景`类别。 + +```json +[{u'id': 1, u'name': u'foreground', u'supercategory': u'foreground'}] +``` + +### 3.3 配置文件改动和说明 + +我们使用 `configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml` 配置进行训练，配置文件摘要如下： + +
+ +
+ +从上图看到 `ppyolov2_r50vd_dcn_365e_coco.yml` 配置需要依赖其他的配置文件，这些配置文件的含义如下: + +``` +coco_detection.yml：主要说明了训练数据和验证数据的路径 + +runtime.yml：主要说明了公共的运行参数，比如是否使用GPU、每多少个epoch存储checkpoint等 + +optimizer_365e.yml：主要说明了学习率和优化器的配置 + +ppyolov2_r50vd_dcn.yml：主要说明模型和主干网络的情况 + +ppyolov2_reader.yml：主要说明数据读取器配置，如 batch size，并发加载子进程数等，同时包含读取后预处理操作，如resize、数据增强等等 +``` + +在主体检测任务中，需要将 `datasets/coco_detection.yml` 中的 `num_classes` 参数修改为 1 （只有 1 个前景类别），同时将训练集和测试集的路径修改为自定义数据集的路径。 + +此外，也可以根据实际情况，修改上述文件，比如，如果显存溢出，可以将 batch size 和学习率等比缩小等。 + + +### 3.4 启动训练 + +PaddleDetection 提供了单卡/多卡训练模式，满足用户多种训练需求。 + +* GPU 单卡训练 + +```bash +# windows和Mac下不需要执行该命令 +export CUDA_VISIBLE_DEVICES=0 +python tools/train.py -c configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml +``` + +* GPU多卡训练 + +```bash +export CUDA_VISIBLE_DEVICES=0,1,2,3 +python -m paddle.distributed.launch --gpus 0,1,2,3 tools/train.py -c configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml --eval +``` + +--eval：表示边训练边验证。 + + +* (**推荐**)模型微调 +如果希望加载 PaddleClas 中已经训练好的主体检测模型，在自己的数据集上进行模型微调，可以使用下面的命令进行训练。 + +```bash +export CUDA_VISIBLE_DEVICES=0 +# 指定pretrain_weights参数，加载通用的主体检测预训练模型 +python tools/train.py -c configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml -o pretrain_weights=https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/ppyolov2_r50vd_dcn_mainbody_v1.0_pretrained.pdparams +``` + +* 模型恢复训练 + +在日常训练过程中，有的用户由于一些原因导致训练中断，可以使用 `-r` 的命令恢复训练: + +```bash +export CUDA_VISIBLE_DEVICES=0,1,2,3 +python -m paddle.distributed.launch --gpus 0,1,2,3 tools/train.py -c configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml --eval -r output/ppyolov2_r50vd_dcn_365e_coco/10000 +``` + +注意：如果遇到 "`Out of memory error`" 问题, 尝试在 `ppyolov2_reader.yml` 文件中调小`batch_size`，同时等比例调小学习率。 + + +### 3.5 模型预测与调试 + +使用下面的命令完成 PaddleDetection 的预测过程。 + +```bash +export CUDA_VISIBLE_DEVICES=0 +python tools/infer.py -c configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml --infer_img=your_image_path.jpg --output_dir=infer_output/ --draw_threshold=0.5 -o weights=output/ppyolov2_r50vd_dcn_365e_coco/model_final +``` + +`--draw_threshold` 是个可选参数. 根据 [NMS](https://ieeexplore.ieee.org/document/1699659) 的计算，不同阈值会产生不同的结果 `keep_top_k` 表示设置输出目标的最大数量，默认值为 100 ，用户可以根据自己的实际情况进行设定。 + +### 3.6 模型导出与预测部署。 + +执行导出模型脚本： + +```bash +python tools/export_model.py -c configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml --output_dir=./inference -o weights=output/ppyolov2_r50vd_dcn_365e_coco/model_final.pdparams +``` + +预测模型会导出到 `inference/ppyolov2_r50vd_dcn_365e_coco` 目录下，分别为 `infer_cfg.yml` (预测不需要), `model.pdiparams`, `model.pdiparams.info`, `model.pdmodel` 。 + +注意： `PaddleDetection` 导出的inference模型的文件格式为 `model.xxx`，这里如果希望与PaddleClas的inference模型文件格式保持一致，需要将其 `model.xxx` 文件修改为 `inference.xxx` 文件，用于后续主体检测的预测部署。 + +更多模型导出教程，请参考： [EXPORT_MODEL](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/deploy/EXPORT_MODEL.md) + +最终，目录 `inference/ppyolov2_r50vd_dcn_365e_coco` 中包含 `inference.pdiparams`, `inference.pdiparams.info` 以及 `inference.pdmodel` 文件，其中 `inference.pdiparams` 为保存的 inference 模型权重文件， `inference.pdmodel` 为保存的 inference 模型结构文件。 + + +导出模型之后，在主体检测与识别任务中，就可以将检测模型的路径更改为该 inference 模型路径，完成预测。 + +以商品识别为例，其配置文件为 [inference_product.yaml](../../../deploy/configs/inference_product.yaml) ，修改其中的 `Global.det_inference_model_dir` 字段为导出的主体检测 inference 模型目录，参考[图像识别快速开始教程](../tutorials/quick_start_recognition.md) ，即可完成商品检测与识别过程。 + + +### FAQ + +#### Q：可以使用其他的主体检测模型结构吗？ + +* A：可以的，但是目前的检测预处理过程仅适配了 PicoDet 以及 YOLO 系列的预处理，因此在使用的时候，建议优先使用这两个系列的模型进行训练，如果希望使用 Faster RCNN 等其他系列的模型，需要按照 PaddleDetection 的数据预处理，修改下预处理逻辑，这块如果您有需求或者有问题的话，欢迎提 issue 或者在微信群里反馈。 + +#### Q：可以修改主体检测的预测尺度吗？ + +* A：可以的，但是需要注意 2 个地方 + * PaddleClas 中提供的主体检测模型是基于 `640x640` 的分辨率去训练的，因此预测的时候也是默认使用 `640x640` 的分辨率进行预测，使用其他分辨率预测的话，精度会有所降低。 + * 在模型导出的时候，建议也修改下模型导出的分辨率，保持模型导出、模型预测的分辨率一致。 diff --git a/ppcls/arch/backbone/__init__.py b/ppcls/arch/backbone/__init__.py index d2efcdc073a91a1571d528d7cb414d14fb251f6b..9dd929bf8872694624b511fce8fce01548760970 100644 --- a/ppcls/arch/backbone/__init__.py +++ b/ppcls/arch/backbone/__init__.py @@ -58,6 +58,7 @@ from ppcls.arch.backbone.model_zoo.dla import DLA34, DLA46_c, DLA46x_c, DLA60, D from ppcls.arch.backbone.model_zoo.rednet import RedNet26, RedNet38, RedNet50, RedNet101, RedNet152 from ppcls.arch.backbone.model_zoo.tnt import TNT_small from ppcls.arch.backbone.model_zoo.hardnet import HarDNet68, HarDNet85, HarDNet39_ds, HarDNet68_ds +from ppcls.arch.backbone.model_zoo.cspnet import CSPDarkNet53 from ppcls.arch.backbone.variant_models.resnet_variant import ResNet50_last_stage_stride1 from ppcls.arch.backbone.variant_models.vgg_variant import VGG19Sigmoid diff --git a/ppcls/arch/backbone/model_zoo/cspnet.py b/ppcls/arch/backbone/model_zoo/cspnet.py new file mode 100644 index 0000000000000000000000000000000000000000..30528214fc4fcfb4c37e9c5dbb3c439bf391ded8 --- /dev/null +++ b/ppcls/arch/backbone/model_zoo/cspnet.py @@ -0,0 +1,374 @@ +# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import paddle +import paddle.nn as nn +import paddle.nn.functional as F +from paddle import ParamAttr + +from ppcls.utils.save_load import load_dygraph_pretrain, load_dygraph_pretrain_from_url + +MODEL_URLS = { + "CSPDarkNet53": + "https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/CSPDarkNet53_pretrained.pdparams" +} + +MODEL_CFGS = { + "CSPDarkNet53": dict( + stem=dict( + out_chs=32, kernel_size=3, stride=1, pool=''), + stage=dict( + out_chs=(64, 128, 256, 512, 1024), + depth=(1, 2, 8, 8, 4), + stride=(2, ) * 5, + exp_ratio=(2., ) + (1., ) * 4, + bottle_ratio=(0.5, ) + (1.0, ) * 4, + block_ratio=(1., ) + (0.5, ) * 4, + down_growth=True, )) +} + +__all__ = ['CSPDarkNet53' + ] # model_registry will add each entrypoint fn to this + + +class ConvBnAct(nn.Layer): + def __init__(self, + input_channels, + output_channels, + kernel_size=1, + stride=1, + padding=None, + dilation=1, + groups=1, + act_layer=nn.LeakyReLU, + norm_layer=nn.BatchNorm2D): + super().__init__() + if padding is None: + padding = (kernel_size - 1) // 2 + self.conv = nn.Conv2D( + in_channels=input_channels, + out_channels=output_channels, + kernel_size=kernel_size, + stride=stride, + padding=padding, + dilation=dilation, + groups=groups, + weight_attr=ParamAttr(), + bias_attr=False) + + self.bn = norm_layer(num_features=output_channels) + self.act = act_layer() + + def forward(self, inputs): + x = self.conv(inputs) + x = self.bn(x) + if self.act is not None: + x = self.act(x) + return x + + +def create_stem(in_chans=3, + out_chs=32, + kernel_size=3, + stride=2, + pool='', + act_layer=None, + norm_layer=None): + stem = nn.Sequential() + if not isinstance(out_chs, (tuple, list)): + out_chs = [out_chs] + assert len(out_chs) + in_c = in_chans + for i, out_c in enumerate(out_chs): + conv_name = f'conv{i + 1}' + stem.add_sublayer( + conv_name, + ConvBnAct( + in_c, + out_c, + kernel_size, + stride=stride if i == 0 else 1, + act_layer=act_layer, + norm_layer=norm_layer)) + in_c = out_c + last_conv = conv_name + if pool: + stem.add_sublayer( + 'pool', nn.MaxPool2D( + kernel_size=3, stride=2, padding=1)) + return stem, dict( + num_chs=in_c, reduction=stride, module='.'.join(['stem', last_conv])) + + +class DarkBlock(nn.Layer): + def __init__(self, + in_chs, + out_chs, + dilation=1, + bottle_ratio=0.5, + groups=1, + act_layer=nn.ReLU, + norm_layer=nn.BatchNorm2D, + attn_layer=None, + drop_block=None): + super(DarkBlock, self).__init__() + mid_chs = int(round(out_chs * bottle_ratio)) + ckwargs = dict(act_layer=act_layer, norm_layer=norm_layer) + self.conv1 = ConvBnAct(in_chs, mid_chs, kernel_size=1, **ckwargs) + self.conv2 = ConvBnAct( + mid_chs, + out_chs, + kernel_size=3, + dilation=dilation, + groups=groups, + **ckwargs) + + def forward(self, x): + shortcut = x + x = self.conv1(x) + x = self.conv2(x) + x = x + shortcut + return x + + +class CrossStage(nn.Layer): + def __init__(self, + in_chs, + out_chs, + stride, + dilation, + depth, + block_ratio=1., + bottle_ratio=1., + exp_ratio=1., + groups=1, + first_dilation=None, + down_growth=False, + cross_linear=False, + block_dpr=None, + block_fn=DarkBlock, + **block_kwargs): + super(CrossStage, self).__init__() + first_dilation = first_dilation or dilation + down_chs = out_chs if down_growth else in_chs + exp_chs = int(round(out_chs * exp_ratio)) + block_out_chs = int(round(out_chs * block_ratio)) + conv_kwargs = dict( + act_layer=block_kwargs.get('act_layer'), + norm_layer=block_kwargs.get('norm_layer')) + + if stride != 1 or first_dilation != dilation: + self.conv_down = ConvBnAct( + in_chs, + down_chs, + kernel_size=3, + stride=stride, + dilation=first_dilation, + groups=groups, + **conv_kwargs) + prev_chs = down_chs + else: + self.conv_down = None + prev_chs = in_chs + + self.conv_exp = ConvBnAct( + prev_chs, exp_chs, kernel_size=1, **conv_kwargs) + prev_chs = exp_chs // 2 # output of conv_exp is always split in two + + self.blocks = nn.Sequential() + for i in range(depth): + self.blocks.add_sublayer( + str(i), + block_fn(prev_chs, block_out_chs, dilation, bottle_ratio, + groups, **block_kwargs)) + prev_chs = block_out_chs + + # transition convs + self.conv_transition_b = ConvBnAct( + prev_chs, exp_chs // 2, kernel_size=1, **conv_kwargs) + self.conv_transition = ConvBnAct( + exp_chs, out_chs, kernel_size=1, **conv_kwargs) + + def forward(self, x): + if self.conv_down is not None: + x = self.conv_down(x) + x = self.conv_exp(x) + split = x.shape[1] // 2 + xs, xb = x[:, :split], x[:, split:] + xb = self.blocks(xb) + xb = self.conv_transition_b(xb) + out = self.conv_transition(paddle.concat([xs, xb], axis=1)) + return out + + +class DarkStage(nn.Layer): + def __init__(self, + in_chs, + out_chs, + stride, + dilation, + depth, + block_ratio=1., + bottle_ratio=1., + groups=1, + first_dilation=None, + block_fn=DarkBlock, + block_dpr=None, + **block_kwargs): + super().__init__() + first_dilation = first_dilation or dilation + + self.conv_down = ConvBnAct( + in_chs, + out_chs, + kernel_size=3, + stride=stride, + dilation=first_dilation, + groups=groups, + act_layer=block_kwargs.get('act_layer'), + norm_layer=block_kwargs.get('norm_layer')) + + prev_chs = out_chs + block_out_chs = int(round(out_chs * block_ratio)) + self.blocks = nn.Sequential() + for i in range(depth): + self.blocks.add_sublayer( + str(i), + block_fn(prev_chs, block_out_chs, dilation, bottle_ratio, + groups, **block_kwargs)) + prev_chs = block_out_chs + + def forward(self, x): + x = self.conv_down(x) + x = self.blocks(x) + return x + + +def _cfg_to_stage_args(cfg, curr_stride=2, output_stride=32): + # get per stage args for stage and containing blocks, calculate strides to meet target output_stride + num_stages = len(cfg['depth']) + if 'groups' not in cfg: + cfg['groups'] = (1, ) * num_stages + if 'down_growth' in cfg and not isinstance(cfg['down_growth'], + (list, tuple)): + cfg['down_growth'] = (cfg['down_growth'], ) * num_stages + stage_strides = [] + stage_dilations = [] + stage_first_dilations = [] + dilation = 1 + for cfg_stride in cfg['stride']: + stage_first_dilations.append(dilation) + if curr_stride >= output_stride: + dilation *= cfg_stride + stride = 1 + else: + stride = cfg_stride + curr_stride *= stride + stage_strides.append(stride) + stage_dilations.append(dilation) + cfg['stride'] = stage_strides + cfg['dilation'] = stage_dilations + cfg['first_dilation'] = stage_first_dilations + stage_args = [ + dict(zip(cfg.keys(), values)) for values in zip(*cfg.values()) + ] + return stage_args + + +class CSPNet(nn.Layer): + def __init__(self, + cfg, + in_chans=3, + class_num=1000, + output_stride=32, + global_pool='avg', + drop_rate=0., + act_layer=nn.LeakyReLU, + norm_layer=nn.BatchNorm2D, + zero_init_last_bn=True, + stage_fn=CrossStage, + block_fn=DarkBlock): + super().__init__() + self.class_num = class_num + self.drop_rate = drop_rate + assert output_stride in (8, 16, 32) + layer_args = dict(act_layer=act_layer, norm_layer=norm_layer) + + # Construct the stem + self.stem, stem_feat_info = create_stem(in_chans, **cfg['stem'], + **layer_args) + self.feature_info = [stem_feat_info] + prev_chs = stem_feat_info['num_chs'] + curr_stride = stem_feat_info[ + 'reduction'] # reduction does not include pool + if cfg['stem']['pool']: + curr_stride *= 2 + + # Construct the stages + per_stage_args = _cfg_to_stage_args( + cfg['stage'], curr_stride=curr_stride, output_stride=output_stride) + self.stages = nn.LayerList() + for i, sa in enumerate(per_stage_args): + self.stages.add_sublayer( + str(i), + stage_fn( + prev_chs, **sa, **layer_args, block_fn=block_fn)) + prev_chs = sa['out_chs'] + curr_stride *= sa['stride'] + self.feature_info += [ + dict( + num_chs=prev_chs, + reduction=curr_stride, + module=f'stages.{i}') + ] + + # Construct the head + self.num_features = prev_chs + + self.pool = nn.AdaptiveAvgPool2D(1) + self.flatten = nn.Flatten(1) + self.fc = nn.Linear( + prev_chs, + class_num, + weight_attr=ParamAttr(), + bias_attr=ParamAttr()) + + def forward(self, x): + x = self.stem(x) + for stage in self.stages: + x = stage(x) + x = self.pool(x) + x = self.flatten(x) + x = self.fc(x) + return x + + +def _load_pretrained(pretrained, model, model_url, use_ssld=False): + if pretrained is False: + pass + elif pretrained is True: + load_dygraph_pretrain_from_url(model, model_url, use_ssld=use_ssld) + elif isinstance(pretrained, str): + load_dygraph_pretrain(model, pretrained) + else: + raise RuntimeError( + "pretrained type is not available. Please use `string` or `boolean` type." + ) + + +def CSPDarkNet53(pretrained=False, use_ssld=False, **kwargs): + model = CSPNet(MODEL_CFGS["CSPDarkNet53"], block_fn=DarkBlock, **kwargs) + _load_pretrained( + pretrained, model, MODEL_URLS["CSPDarkNet53"], use_ssld=use_ssld) + return model diff --git a/ppcls/configs/ImageNet/CSPNet/CSPDarkNet53.yaml b/ppcls/configs/ImageNet/CSPNet/CSPDarkNet53.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cce4e3e591a1fad7ae8e78b1c523309ba7cec298 --- /dev/null +++ b/ppcls/configs/ImageNet/CSPNet/CSPDarkNet53.yaml @@ -0,0 +1,131 @@ +# global configs +Global: + checkpoints: null + pretrained_model: null + output_dir: ./output/ + device: gpu + save_interval: 1 + eval_during_train: True + eval_interval: 1 + epochs: 120 + print_batch_step: 10 + use_visualdl: False + # used for static mode and model export + image_shape: [3, 224, 224] + save_inference_dir: ./inference + # training model under @to_static + to_static: False + +# model architecture +Arch: + name: CSPDarkNet53 + class_num: 1000 + +# loss function config for traing/eval process +Loss: + Train: + - CELoss: + weight: 1.0 + Eval: + - CELoss: + weight: 1.0 + + +Optimizer: + name: Momentum + momentum: 0.9 + lr: + name: Piecewise + decay_epochs: [30, 60, 90] + values: [0.1, 0.01, 0.001, 0.0001] + regularizer: + name: 'L2' + coeff: 0.0001 + + +# data loader for train and eval +DataLoader: + Train: + dataset: + name: ImageNetDataset + image_root: ./dataset/ILSVRC2012/ + cls_label_path: ./dataset/ILSVRC2012/train_list.txt + transform_ops: + - DecodeImage: + to_rgb: True + channel_first: False + - RandCropImage: + size: 256 + - RandFlipImage: + flip_code: 1 + - NormalizeImage: + scale: 1.0/255.0 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + + sampler: + name: DistributedBatchSampler + batch_size: 64 + drop_last: False + shuffle: True + loader: + num_workers: 4 + use_shared_memory: True + + Eval: + dataset: + name: ImageNetDataset + image_root: ./dataset/ILSVRC2012/ + cls_label_path: ./dataset/ILSVRC2012/val_list.txt + transform_ops: + - DecodeImage: + to_rgb: True + channel_first: False + - ResizeImage: + resize_short: 288 + - CropImage: + size: 256 + - NormalizeImage: + scale: 1.0/255.0 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + sampler: + name: DistributedBatchSampler + batch_size: 64 + drop_last: False + shuffle: False + loader: + num_workers: 4 + use_shared_memory: True + +Infer: + infer_imgs: docs/images/whl/demo.jpg + batch_size: 10 + transforms: + - DecodeImage: + to_rgb: True + channel_first: False + - ResizeImage: + resize_short: 288 + - CropImage: + size: 256 + - NormalizeImage: + scale: 1.0/255.0 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + - ToCHWImage: + PostProcess: + name: Topk + topk: 5 + class_id_map_file: ppcls/utils/imagenet1k_label_list.txt + +Metric: + Train: + - TopkAcc: + topk: [1, 5] + Eval: + - TopkAcc: + topk: [1, 5] diff --git a/ppcls/data/preprocess/ops/operators.py b/ppcls/data/preprocess/ops/operators.py index e46823d2a751789d50c98e056fa34b496dee156e..e551fb768a2bf694d426f33ca6bf9ea67bca0906 100644 --- a/ppcls/data/preprocess/ops/operators.py +++ b/ppcls/data/preprocess/ops/operators.py @@ -60,7 +60,7 @@ class UnifiedResize(object): if isinstance(interpolation, str): interpolation = _cv2_interp_from_str[interpolation.lower()] # compatible with opencv < version 4.4.0 - elif not interpolation: + elif interpolation is None: interpolation = cv2.INTER_LINEAR self.resize_func = partial(cv2.resize, interpolation=interpolation) elif backend.lower() == "pil": diff --git a/ppcls/optimizer/__init__.py b/ppcls/optimizer/__init__.py index cc64a9caaaf2c90099f111c8863515f0bebec351..61db39f89a3775eec70fe3cfa63d7e820e3e60e6 100644 --- a/ppcls/optimizer/__init__.py +++ b/ppcls/optimizer/__init__.py @@ -41,7 +41,8 @@ def build_lr_scheduler(lr_config, epochs, step_each_epoch): return lr -def build_optimizer(config, epochs, step_each_epoch, model_list): +# model_list is None in static graph +def build_optimizer(config, epochs, step_each_epoch, model_list=None): config = copy.deepcopy(config) # step1 build lr lr = build_lr_scheduler(config.pop('lr'), epochs, step_each_epoch) diff --git a/ppcls/optimizer/optimizer.py b/ppcls/optimizer/optimizer.py index 72310f27b4ea15b5ba738820e5a5b7858f7ff2eb..f429755fcc4fc189871526bae11639b83e870d05 100644 --- a/ppcls/optimizer/optimizer.py +++ b/ppcls/optimizer/optimizer.py @@ -18,6 +18,8 @@ from __future__ import print_function from paddle import optimizer as optim +from ppcls.utils import logger + class Momentum(object): """ @@ -43,7 +45,9 @@ class Momentum(object): self.multi_precision = multi_precision def __call__(self, model_list): - parameters = sum([m.parameters() for m in model_list], []) + # model_list is None in static graph + parameters = sum([m.parameters() for m in model_list], + []) if model_list else None opt = optim.Momentum( learning_rate=self.learning_rate, momentum=self.momentum, @@ -79,7 +83,9 @@ class Adam(object): self.multi_precision = multi_precision def __call__(self, model_list): - parameters = sum([m.parameters() for m in model_list], []) + # model_list is None in static graph + parameters = sum([m.parameters() for m in model_list], + []) if model_list else None opt = optim.Adam( learning_rate=self.learning_rate, beta1=self.beta1, @@ -123,7 +129,9 @@ class RMSProp(object): self.grad_clip = grad_clip def __call__(self, model_list): - parameters = sum([m.parameters() for m in model_list], []) + # model_list is None in static graph + parameters = sum([m.parameters() for m in model_list], + []) if model_list else None opt = optim.RMSProp( learning_rate=self.learning_rate, momentum=self.momentum, @@ -160,18 +168,28 @@ class AdamW(object): self.one_dim_param_no_weight_decay = one_dim_param_no_weight_decay def __call__(self, model_list): - parameters = sum([m.parameters() for m in model_list], []) + # model_list is None in static graph + parameters = sum([m.parameters() for m in model_list], + []) if model_list else None + + # TODO(gaotingquan): model_list is None when in static graph, "no_weight_decay" not work. + if model_list is None: + if self.one_dim_param_no_weight_decay or len( + self.no_weight_decay_name_list) != 0: + msg = "\"AdamW\" does not support setting \"no_weight_decay\" in static graph. Please use dynamic graph." + logger.error(Exception(msg)) + raise Exception(msg) self.no_weight_decay_param_name_list = [ p.name for model in model_list for n, p in model.named_parameters() if any(nd in n for nd in self.no_weight_decay_name_list) - ] + ] if model_list else [] if self.one_dim_param_no_weight_decay: self.no_weight_decay_param_name_list += [ p.name for model in model_list for n, p in model.named_parameters() if len(p.shape) == 1 - ] + ] if model_list else [] opt = optim.AdamW( learning_rate=self.learning_rate, diff --git a/tests/config/DarkNet53.txt b/tests/config/DarkNet53.txt index 589d655112283d31de41ba27a5b9adb7e590c325..9b9b95c88f1dae2ac4472eaa7d175fc844fd8984 100644 --- a/tests/config/DarkNet53.txt +++ b/tests/config/DarkNet53.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/GhostNet_x0_5.txt b/tests/config/GhostNet_x0_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..b752da46a2bd3068284166bcbc400f159f12738f --- /dev/null +++ b/tests/config/GhostNet_x0_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:GhostNet_x0_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/GhostNet/GhostNet_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/GhostNet/GhostNet_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/GhostNet/GhostNet_x0_5.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/GhostNet_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/GhostNet_x1_0.txt b/tests/config/GhostNet_x1_0.txt new file mode 100644 index 0000000000000000000000000000000000000000..c927b2bf3358fc952bb2067e912fa5e6f65a5925 --- /dev/null +++ b/tests/config/GhostNet_x1_0.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:GhostNet_x1_0 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/GhostNet/GhostNet_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/GhostNet/GhostNet_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/GhostNet/GhostNet_x1_0.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/GhostNet_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/GhostNet_x1_3.txt b/tests/config/GhostNet_x1_3.txt new file mode 100644 index 0000000000000000000000000000000000000000..5766332f3c08f94c02237c724a20e8ec24442ec8 --- /dev/null +++ b/tests/config/GhostNet_x1_3.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:GhostNet_x1_3 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/GhostNet/GhostNet_x1_3.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/GhostNet/GhostNet_x1_3.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/GhostNet/GhostNet_x1_3.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/GhostNet_x1_3_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/HRNet_W18_C.txt b/tests/config/HRNet_W18_C.txt index 0609047b834044d2edcf0874c5da00e722a4b4e4..c5334e38df3a9516f2a2e5d05bd30c704350351d 100644 --- a/tests/config/HRNet_W18_C.txt +++ b/tests/config/HRNet_W18_C.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/LeViT_128S.txt b/tests/config/LeViT_128S.txt index 35feb2ffb1ecd55359d19d83e60d3d683e68d846..6ddc0cd9ffd51f991c7f67a1ce9723e6e4ac2381 100644 --- a/tests/config/LeViT_128S.txt +++ b/tests/config/LeViT_128S.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|Fasle -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/MobileNetV1.txt b/tests/config/MobileNetV1.txt index 278906219a377a362e728cd595a025f10f2ab820..319f852dbd7731ccedc22af9ab415080e32993fe 100644 --- a/tests/config/MobileNetV1.txt +++ b/tests/config/MobileNetV1.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/MobileNetV1_x0_25.txt b/tests/config/MobileNetV1_x0_25.txt new file mode 100644 index 0000000000000000000000000000000000000000..a46a8e30facf657324dd041f5cda44af85596fa2 --- /dev/null +++ b/tests/config/MobileNetV1_x0_25.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV1_x0_25 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV1/MobileNetV1_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/MobileNetV1/MobileNetV1_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/MobileNetV1/MobileNetV1_x0_25.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/MobileNetV1_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV1_x0_5.txt b/tests/config/MobileNetV1_x0_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..bca197b7900af161abf5d04335b10202801a0c26 --- /dev/null +++ b/tests/config/MobileNetV1_x0_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV1_x0_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV1/MobileNetV1_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/MobileNetV1/MobileNetV1_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/MobileNetV1/MobileNetV1_x0_5.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/MobileNetV1_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV1_x0_75.txt b/tests/config/MobileNetV1_x0_75.txt new file mode 100644 index 0000000000000000000000000000000000000000..ba81e35ce002b1278eacacc4e693e9932d1f195e --- /dev/null +++ b/tests/config/MobileNetV1_x0_75.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV1_x0_75 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV1/MobileNetV1_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/MobileNetV1/MobileNetV1_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/MobileNetV1/MobileNetV1_x0_75.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/MobileNetV1_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV2.txt b/tests/config/MobileNetV2.txt index 3904cb5d6081ea6dde63bb6ff69487d103cf55ef..d4cf3fc5d48685f627b4e76cb32e7524565c8944 100644 --- a/tests/config/MobileNetV2.txt +++ b/tests/config/MobileNetV2.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/MobileNetV2_x0_25.txt b/tests/config/MobileNetV2_x0_25.txt new file mode 100644 index 0000000000000000000000000000000000000000..5368aef958bfd8c4edef819b6963c55891388b84 --- /dev/null +++ b/tests/config/MobileNetV2_x0_25.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV2_x0_25 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_x0_25.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/MobileNetV2_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV2_x0_5.txt b/tests/config/MobileNetV2_x0_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..ba35c3affc57404382bd73215954d4de7454fce9 --- /dev/null +++ b/tests/config/MobileNetV2_x0_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV2_x0_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_x0_5.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/MobileNetV2_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV2_x0_75.txt b/tests/config/MobileNetV2_x0_75.txt new file mode 100644 index 0000000000000000000000000000000000000000..0f5a8ab8a71da4bcd44592f7f6cf3160def6b206 --- /dev/null +++ b/tests/config/MobileNetV2_x0_75.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV2_x0_75 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_x0_75.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/MobileNetV2_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV2_x1_5.txt b/tests/config/MobileNetV2_x1_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..55da65b1268b022831472eb9e8f88e8690e3a7dd --- /dev/null +++ b/tests/config/MobileNetV2_x1_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV2_x1_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_x1_5.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/MobileNetV2_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV2_x2_0.txt b/tests/config/MobileNetV2_x2_0.txt new file mode 100644 index 0000000000000000000000000000000000000000..cd32244ff257a39c248e5bb65aec0ef0590356df --- /dev/null +++ b/tests/config/MobileNetV2_x2_0.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV2_x2_0 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_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/MobileNetV2/MobileNetV2_x2_0.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/MobileNetV2_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_large_x0_35.txt b/tests/config/MobileNetV3_large_x0_35.txt new file mode 100644 index 0000000000000000000000000000000000000000..bc6e77c0bd3fa3ca32d2a848e1f8fe9337def63e --- /dev/null +++ b/tests/config/MobileNetV3_large_x0_35.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_large_x0_35 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_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/MobileNetV3/MobileNetV3_large_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/MobileNetV3/MobileNetV3_large_x0_35.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/MobileNetV3_large_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_large_x0_5.txt b/tests/config/MobileNetV3_large_x0_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..693423dacef1bd3029d65ba88dcfc3686ea3b13d --- /dev/null +++ b/tests/config/MobileNetV3_large_x0_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_large_x0_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_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/MobileNetV3/MobileNetV3_large_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/MobileNetV3/MobileNetV3_large_x0_5.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/MobileNetV3_large_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_large_x0_75.txt b/tests/config/MobileNetV3_large_x0_75.txt new file mode 100644 index 0000000000000000000000000000000000000000..24b35de56125df1770012c9111399a5a393051e0 --- /dev/null +++ b/tests/config/MobileNetV3_large_x0_75.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_large_x0_75 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_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/MobileNetV3/MobileNetV3_large_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/MobileNetV3/MobileNetV3_large_x0_75.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/MobileNetV3_large_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_large_x1_0.txt b/tests/config/MobileNetV3_large_x1_0.txt index f5add2e9a078a44de12aba3b48f1ad6e070960eb..873072f256deee6b107ae44f00c1f85eff1f13e1 100644 --- a/tests/config/MobileNetV3_large_x1_0.txt +++ b/tests/config/MobileNetV3_large_x1_0.txt @@ -31,17 +31,17 @@ norm_export:tools/export_model.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNe 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 -export1:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.save_inference_dir=./inference export2:null inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/MobileNetV3_large_x1_0_inference.tar infer_model:../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 +infer_export:null infer_quant:Fasle inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/MobileNetV3_large_x1_25.txt b/tests/config/MobileNetV3_large_x1_25.txt new file mode 100644 index 0000000000000000000000000000000000000000..34057be52366b5c1ea81ab12c2b883c8040dd027 --- /dev/null +++ b/tests/config/MobileNetV3_large_x1_25.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_large_x1_25 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_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/MobileNetV3/MobileNetV3_large_x1_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/MobileNetV3/MobileNetV3_large_x1_25.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/MobileNetV3_large_x1_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_small_x0_35.txt b/tests/config/MobileNetV3_small_x0_35.txt new file mode 100644 index 0000000000000000000000000000000000000000..0f8b75e9999f2f44d41b2d46153cffba3b926b2a --- /dev/null +++ b/tests/config/MobileNetV3_small_x0_35.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_small_x0_35 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_small_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/MobileNetV3/MobileNetV3_small_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/MobileNetV3/MobileNetV3_small_x0_35.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/MobileNetV3_small_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_small_x0_5.txt b/tests/config/MobileNetV3_small_x0_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..0693c086507c1bbc74f27281507a46f0b673457d --- /dev/null +++ b/tests/config/MobileNetV3_small_x0_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_small_x0_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_small_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/MobileNetV3/MobileNetV3_small_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/MobileNetV3/MobileNetV3_small_x0_5.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/MobileNetV3_small_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_small_x0_75.txt b/tests/config/MobileNetV3_small_x0_75.txt new file mode 100644 index 0000000000000000000000000000000000000000..ce42427370af1965d8dc988ee9d8a7bc59859825 --- /dev/null +++ b/tests/config/MobileNetV3_small_x0_75.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_small_x0_75 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_small_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/MobileNetV3/MobileNetV3_small_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/MobileNetV3/MobileNetV3_small_x0_75.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/MobileNetV3_small_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_small_x1_0.txt b/tests/config/MobileNetV3_small_x1_0.txt new file mode 100644 index 0000000000000000000000000000000000000000..a1f2b8b70321974710f5fe83a66d2a3d42110652 --- /dev/null +++ b/tests/config/MobileNetV3_small_x1_0.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_small_x1_0 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_small_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/MobileNetV3/MobileNetV3_small_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_small_x1_0.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/MobileNetV3_small_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/MobileNetV3_small_x1_25.txt b/tests/config/MobileNetV3_small_x1_25.txt new file mode 100644 index 0000000000000000000000000000000000000000..49831b6675bd2fc6cf3a2efc81fefbdcbf2f76c7 --- /dev/null +++ b/tests/config/MobileNetV3_small_x1_25.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:MobileNetV3_small_x1_25 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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_small_x1_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/MobileNetV3/MobileNetV3_small_x1_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/MobileNetV3/MobileNetV3_small_x1_25.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/MobileNetV3_small_x1_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/PPLCNet_x0_25.txt b/tests/config/PPLCNet_x0_25.txt new file mode 100644 index 0000000000000000000000000000000000000000..0777cfa4fc60e735563ee0c72ad039ce0fffb913 --- /dev/null +++ b/tests/config/PPLCNet_x0_25.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:PPLCNet_x0_25 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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: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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/PPLCNet_x0_35.txt b/tests/config/PPLCNet_x0_35.txt new file mode 100644 index 0000000000000000000000000000000000000000..0ce679e4d4444d6983d68e876cd71c6aebf200fb --- /dev/null +++ b/tests/config/PPLCNet_x0_35.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:PPLCNet_x0_35 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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: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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/PPLCNet_x0_5.txt b/tests/config/PPLCNet_x0_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..fbee882a9101a090259fe9ea98d757eb8d4263cd --- /dev/null +++ b/tests/config/PPLCNet_x0_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:PPLCNet_x0_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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: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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/PPLCNet_x1_0.txt b/tests/config/PPLCNet_x1_0.txt new file mode 100644 index 0000000000000000000000000000000000000000..1e991164903a91f89c139fdb43741e9fddcbfda7 --- /dev/null +++ b/tests/config/PPLCNet_x1_0.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:PPLCNet_x1_0 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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: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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/ResNeXt101_vd_64x4d.txt b/tests/config/ResNeXt101_vd_64x4d.txt index 90b7965573417e35302a15d736ba54138eef8ce3..aab18d564834368742469f491bd95dca3bae66a4 100644 --- a/tests/config/ResNeXt101_vd_64x4d.txt +++ b/tests/config/ResNeXt101_vd_64x4d.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/ResNet50_vd.txt b/tests/config/ResNet50_vd.txt index aa7f9ac10db613ecef88505a889d7f3bb738e7d8..9b8f27cc6485ff61f3b3999a870af544afca485b 100644 --- a/tests/config/ResNet50_vd.txt +++ b/tests/config/ResNet50_vd.txt @@ -31,17 +31,17 @@ norm_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.y quant_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_quantization.yaml fpgm_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_prune.yaml distill_export:null -export1:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.save_inference_dir=./inference export2:null infer_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/ResNet50_vd_inference.tar infer_model:../inference/ -kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.save_inference_dir=./inference +infer_export:null infer_quant:Fasle inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/ShuffleNetV2_x0_25.txt b/tests/config/ShuffleNetV2_x0_25.txt new file mode 100644 index 0000000000000000000000000000000000000000..1c80e4f4aef71ed2b211b7036c63be8f86d6e5ef --- /dev/null +++ b/tests/config/ShuffleNetV2_x0_25.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:ShuffleNetV2_x0_25 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/ShuffleNet/ShuffleNetV2_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/ShuffleNet/ShuffleNetV2_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/ShuffleNet/ShuffleNetV2_x0_25.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/ShuffleNetV2_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/ShuffleNetV2_x0_33.txt b/tests/config/ShuffleNetV2_x0_33.txt new file mode 100644 index 0000000000000000000000000000000000000000..34e813fb4d236e657bc3902c5dd1ad3eeca4c1fc --- /dev/null +++ b/tests/config/ShuffleNetV2_x0_33.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:ShuffleNetV2_x0_33 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/ShuffleNet/ShuffleNetV2_x0_33.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/ShuffleNet/ShuffleNetV2_x0_33.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/ShuffleNet/ShuffleNetV2_x0_33.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/ShuffleNetV2_x0_33_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/ShuffleNetV2_x0_5.txt b/tests/config/ShuffleNetV2_x0_5.txt new file mode 100644 index 0000000000000000000000000000000000000000..b918a780718157105c7d9a99205a77fca6537c5d --- /dev/null +++ b/tests/config/ShuffleNetV2_x0_5.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:ShuffleNetV2_x0_5 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_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/ShuffleNet/ShuffleNetV2_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/ShuffleNet/ShuffleNetV2_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/ShuffleNet/ShuffleNetV2_x0_5.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/ShuffleNetV2_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:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null diff --git a/tests/config/ShuffleNetV2_x1_0.txt b/tests/config/ShuffleNetV2_x1_0.txt index a208fa14d6536adc0ebd4801678dfbdf3cc8cb86..1055910ac9c807864dc0c3dfad50a5f942b3d79c 100644 --- a/tests/config/ShuffleNetV2_x1_0.txt +++ b/tests/config/ShuffleNetV2_x1_0.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/config/SwinTransformer_tiny_patch4_window7_224.txt b/tests/config/SwinTransformer_tiny_patch4_window7_224.txt index f2937b14b4c0c7e6b7afdab63b5863bc586e27f3..94acb1503d1ad9277231f0157259154925d47fef 100644 --- a/tests/config/SwinTransformer_tiny_patch4_window7_224.txt +++ b/tests/config/SwinTransformer_tiny_patch4_window7_224.txt @@ -41,7 +41,7 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu:True|False -o Global.enable_mkldnn:True|False -o Global.cpu_num_threads:1|6 --o Global.batch_size:1 +-o Global.batch_size:1|16 -o Global.use_tensorrt:True|False -o Global.use_fp16:True|False -o Global.inference_model_dir:../inference diff --git a/tests/prepare.sh b/tests/prepare.sh index 6f9701a101e42b3feba1d2d46008b449ca8c3519..4c2aa052a57923e3354847c07f2091bb3c0e5666 100644 --- a/tests/prepare.sh +++ b/tests/prepare.sh @@ -7,6 +7,15 @@ dataline=$(cat ${FILENAME}) # parser params IFS=$'\n' lines=(${dataline}) + +function func_parser_key(){ + strs=$1 + IFS=":" + array=(${strs}) + tmp=${array[0]} + echo ${tmp} +} + function func_parser_value(){ strs=$1 IFS=":" @@ -20,7 +29,8 @@ function func_parser_value(){ fi } model_name=$(func_parser_value "${lines[1]}") -inference_model_url=$(func_parser_value "${lines[35]}") +model_url_value=$(func_parser_value "${lines[35]}") +model_url_key=$(func_parser_key "${lines[35]}") if [ ${MODE} = "lite_train_infer" ] || [ ${MODE} = "whole_infer" ];then # pretrain lite train data @@ -44,9 +54,12 @@ elif [ ${MODE} = "infer" ] || [ ${MODE} = "cpp_infer" ];then mv val.txt val_list.txt ln -s val_list.txt train_list.txt cd ../../ - # download inference model - eval "wget -nc $inference_model_url" - tar xf "${model_name}_inference.tar" + # download inference or pretrained model + eval "wget -nc $model_url_value" + if [[ $model_url_key == *inference* ]]; then + rm -rf inference + tar xf "${model_name}_inference.tar" + fi elif [ ${MODE} = "whole_train_infer" ];then cd dataset diff --git a/tests/test.sh b/tests/test.sh index b369912647ff9fad27ffc279df870b0be5ecfd80..56af96ac23bbe4adbe9d059bb3b9118317eef8ad 100644 --- a/tests/test.sh +++ b/tests/test.sh @@ -113,14 +113,14 @@ norm_export=$(func_parser_value "${lines[29]}") pact_export=$(func_parser_value "${lines[30]}") fpgm_export=$(func_parser_value "${lines[31]}") distill_export=$(func_parser_value "${lines[32]}") -export_key1=$(func_parser_key "${lines[33]}") -export_value1=$(func_parser_value "${lines[33]}") +kl_quant_cmd_key=$(func_parser_key "${lines[33]}") +kl_quant_cmd_value=$(func_parser_value "${lines[33]}") export_key2=$(func_parser_key "${lines[34]}") export_value2=$(func_parser_value "${lines[34]}") # parser inference model infer_model_dir_list=$(func_parser_value "${lines[36]}") -infer_export_list=$(func_parser_value "${lines[37]}") +infer_export_flag=$(func_parser_value "${lines[37]}") infer_is_quant=$(func_parser_value "${lines[38]}") # parser inference inference_py=$(func_parser_value "${lines[39]}") @@ -295,8 +295,13 @@ if [ ${MODE} = "infer" ]; then eval $env export Count=0 IFS="|" - infer_run_exports=(${infer_export_list}) + infer_export_flag=(${infer_export_flag}) infer_quant_flag=(${infer_is_quant}) + if [ ${infer_export_flag} != "null" ] && [ ${infer_export_flag} != "False" ]; then + rm -rf ${infer_model_dir_list/..\//} + export_cmd="${python} ${norm_export} -o Global.pretrained_model=${model_name}_pretrained -o Global.save_inference_dir=${infer_model_dir_list/..\//}" + eval $export_cmd + fi cd deploy for infer_model in ${infer_model_dir_list[*]}; do #run inference @@ -308,9 +313,9 @@ if [ ${MODE} = "infer" ]; then cd .. # for kl_quant - echo "kl_quant" - if [ ${infer_run_exports} ]; then - command="${python} ${infer_run_exports}" + if [ ${kl_quant_cmd_value} != "null" ] && [ ${kl_quant_cmd_value} != "False" ]; then + echo "kl_quant" + command="${python} ${kl_quant_cmd_value}" eval $command last_status=${PIPESTATUS[0]} status_check $last_status "${command}" "${status_log}"