Merge pull request !6811 from chengxb7532/mastertags/v1.1.0
| @@ -112,6 +112,7 @@ sh run_eval.sh dataset/coco2014/ checkpoint/0-319_102400.ckpt | |||
| . | |||
| └─yolov3_darknet53 | |||
| ├─README.md | |||
| ├─mindspore_hub_conf.md # config for mindspore hub | |||
| ├─scripts | |||
| ├─run_standalone_train.sh # launch standalone training(1p) in ascend | |||
| ├─run_distribute_train.sh # launch distributed training(8p) in ascend | |||
| @@ -302,12 +303,12 @@ The above python command will run in the background. You can view the results th | |||
| ### Evaluation Performance | |||
| | Parameters | YOLO |YOLO | | |||
| | -------------------------- | ----------------------------------------------------------- |----------------------------------------------------------- | | |||
| | Model Version | YOLOv3 |YOLOv3 | | |||
| | Resource | Ascend 910; CPU 2.60GHz, 192cores; Memory, 755G | NV SMX2 V100-16G; CPU 2.10GHz, 96cores; Memory, 251G | | |||
| | Parameters | YOLO |YOLO | | |||
| | -------------------------- | ----------------------------------------------------------- |------------------------------------------------------------ | | |||
| | Model Version | YOLOv3 |YOLOv3 | | |||
| | Resource | Ascend 910; CPU 2.60GHz, 192cores; Memory, 755G | NV SMX2 V100-16G; CPU 2.10GHz, 96cores; Memory, 251G | | |||
| | uploaded Date | 06/31/2020 (month/day/year) | 09/02/2020 (month/day/year) | | |||
| | MindSpore Version | 0.5.0-alpha | 0.7.0 | | |||
| | MindSpore Version | 0.5.0-alpha | 0.7.0 | | |||
| | Dataset | COCO2014 | COCO2014 | | |||
| | Training Parameters | epoch=320, batch_size=32, lr=0.001, momentum=0.9 | epoch=320, batch_size=32, lr=0.001, momentum=0.9 | | |||
| | Optimizer | Momentum | Momentum | | |||
| @@ -315,7 +316,7 @@ The above python command will run in the background. You can view the results th | |||
| | outputs | boxes and label | boxes and label | | |||
| | Loss | 34 | 34 | | |||
| | Speed | 1pc: 350 ms/step; | 1pc: 600 ms/step; | | |||
| | Total time | 8pc: 25 hours | 8pc: 18 hours(shape=416) | | |||
| | Total time | 8pc: 18.5 hours | 8pc: 18 hours(shape=416) | | |||
| | Parameters (M) | 62.1 | 62.1 | | |||
| | Checkpoint for Fine tuning | 474M (.ckpt file) | 474M (.ckpt file) | | |||
| | Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53 | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53 | | |||
| @@ -331,15 +332,15 @@ The above python command will run in the background. You can view the results th | |||
| | MindSpore Version | 0.5.0-alpha | 0.7.0 | | |||
| | Dataset | COCO2014, 40,504 images | COCO2014, 40,504 images | | |||
| | batch_size | 1 | 1 | | |||
| | outputs | mAP | mAP | | |||
| | outputs | mAP | mAP | | |||
| | Accuracy | 8pcs: 31.1% | 8pcs: 29.7%~30.3% (shape=416)| | |||
| | Model for inference | 474M (.ckpt file) | 474M (.ckpt file) | | |||
| # [Description of Random Situation](#contents) | |||
| There are random seeds in distributed_sampler.py, transforms.py, yolo_dataset.py files. | |||
| There are random seeds in distributed_sampler.py, transforms.py, yolo_dataset.py files. | |||
| # [ModelZoo Homepage](#contents) | |||
| Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo). | |||
| # [ModelZoo Homepage](#contents) | |||
| Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo). | |||
| @@ -0,0 +1,22 @@ | |||
| # Copyright 2020 Huawei Technologies Co., Ltd | |||
| # | |||
| # 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. | |||
| # ============================================================================ | |||
| """hub config.""" | |||
| from src.yolo import YOLOV3DarkNet53 | |||
| def create_network(name, *args, **kwargs): | |||
| if name == "yolov3_darknet53": | |||
| yolov3_darknet53_net = YOLOV3DarkNet53(is_training=False) | |||
| return yolov3_darknet53_net | |||
| raise NotImplementedError(f"{name} is not implemented in the repo") | |||
| @@ -111,6 +111,7 @@ sh run_eval.sh dataset/coco2014/ checkpoint/yolov3_quant.ckpt 0 | |||
| . | |||
| └─yolov3_darknet53_quant | |||
| ├─README.md | |||
| ├─mindspore_hub_conf.md # config for mindspore hub | |||
| ├─scripts | |||
| ├─run_standalone_train.sh # launch standalone training(1p) in ascend | |||
| ├─run_distribute_train.sh # launch distributed training(8p) in ascend | |||
| @@ -284,7 +285,7 @@ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.558 | |||
| | outputs | boxes and label | | |||
| | Loss | 34 | | |||
| | Speed | 1pc: 135 ms/step; | | |||
| | Total time | 8pc: 24.5 hours | | |||
| | Total time | 8pc: 23.5 hours | | |||
| | Parameters (M) | 62.1 | | |||
| | Checkpoint for Fine tuning | 474M (.ckpt file) | | |||
| | Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53_quant | | |||
| @@ -0,0 +1,32 @@ | |||
| # Copyright 2020 Huawei Technologies Co., Ltd | |||
| # | |||
| # 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. | |||
| # ============================================================================ | |||
| """hub config.""" | |||
| from mindspore.train.quant import quant | |||
| from src.yolo import YOLOV3DarkNet53 | |||
| from src.config import ConfigYOLOV3DarkNet53 | |||
| def create_network(name, *args, **kwargs): | |||
| if name == "yolov3_darknet53_quant": | |||
| yolov3_darknet53_quant = YOLOV3DarkNet53(is_training=False) | |||
| config = ConfigYOLOV3DarkNet53() | |||
| # convert fusion network to quantization aware network | |||
| if config.quantization_aware: | |||
| yolov3_darknet53_quant = quant.convert_quant_network(yolov3_darknet53_quant, | |||
| bn_fold=True, | |||
| per_channel=[True, False], | |||
| symmetric=[True, False]) | |||
| return yolov3_darknet53_quant | |||
| raise NotImplementedError(f"{name} is not implemented in the repo") | |||
| @@ -98,6 +98,7 @@ After installing MindSpore via the official website, you can start training and | |||
| ``` | |||
| └── cv | |||
| ├── README.md // descriptions about all the models | |||
| ├── mindspore_hub_conf.md // config for mindspore hub | |||
| └── yolov3_resnet18 | |||
| ├── README.md // descriptions about yolov3_resnet18 | |||
| ├── scripts | |||
| @@ -0,0 +1,23 @@ | |||
| # Copyright 2020 Huawei Technologies Co., Ltd | |||
| # | |||
| # 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. | |||
| # ============================================================================ | |||
| """hub config.""" | |||
| from src.yolov3 import yolov3_resnet18 | |||
| from src.config import ConfigYOLOV3ResNet18 | |||
| def create_network(name, *args, **kwargs): | |||
| if name == "yolov3_resnet18": | |||
| yolov3_resnet18_net = yolov3_resnet18(ConfigYOLOV3ResNet18()) | |||
| return yolov3_resnet18_net | |||
| raise NotImplementedError(f"{name} is not implemented in the repo") | |||
| @@ -117,6 +117,7 @@ After installing MindSpore via the official website, you can start training and | |||
| . | |||
| └─deepfm | |||
| ├─README.md | |||
| ├─mindspore_hub_conf.md # config for mindspore hub | |||
| ├─scripts | |||
| ├─run_standalone_train.sh # launch standalone training(1p) in Ascend or GPU | |||
| ├─run_distribute_train.sh # launch distributed training(8p) in Ascend | |||
| @@ -0,0 +1,26 @@ | |||
| # Copyright 2020 Huawei Technologies Co., Ltd | |||
| # | |||
| # 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. | |||
| # ============================================================================ | |||
| """hub config.""" | |||
| from src.deepfm import ModelBuilder | |||
| from src.config import ModelConfig, TrainConfig | |||
| def create_network(name, *args, **kwargs): | |||
| if name == 'deepfm': | |||
| model_config = ModelConfig() | |||
| train_config = TrainConfig() | |||
| model_builder = ModelBuilder(model_config, train_config) | |||
| _, deepfm_eval_net = model_builder.get_train_eval_net() | |||
| return deepfm_eval_net | |||
| raise NotImplementedError(f"{name} is not implemented in the repo") | |||