diff --git a/model_zoo/official/README.md b/model_zoo/README.md similarity index 96% rename from model_zoo/official/README.md rename to model_zoo/README.md index abfff4ff2f..472b02b266 100644 --- a/model_zoo/official/README.md +++ b/model_zoo/README.md @@ -27,15 +27,15 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, - [AlexNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet/README.md) - [LeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet/README.md) - [LeNet_Quant](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet_quant/README.md) - - [InceptionV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3/README.md) + - [MobileNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2/README.md) + - [MobileNetV2_Quant](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2_quant/README.md) + - [MobileNetV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3/README.md) + - [InceptionV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3/README.md) - [Object Detection and Segmentation](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv) - [DeepLabV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3/README.md) - [FasterRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn/README.md) - [YoloV3-DarkNet53](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53/README.md) - [YoloV3-ResNet18](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18/README.md) - - [MobileNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2/README.md) - - [MobileNetV2_Quant](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2_quant/README.md) - - [MobileNetV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3/README.md) - [MaskRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn/README.md) - [SSD](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd/README.md) - [Warp-CTC](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc/README.md) @@ -59,6 +59,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, # Announcements | Date | News | | ------------ | ------------------------------------------------------------ | +| September 25, 2020 | Support [MindSpore v1.0.0](https://www.mindspore.cn/news/newschildren/en?id=262) | | September 01, 2020 | Support [MindSpore v0.7.0-beta](https://www.mindspore.cn/news/newschildren/en?id=246) | | July 31, 2020 | Support [MindSpore v0.6.0-beta](https://www.mindspore.cn/news/newschildren/en?id=237) | diff --git a/model_zoo/official/cv/googlenet/README.md b/model_zoo/official/cv/googlenet/README.md index 67f7bfcfab..299ab6e9a5 100644 --- a/model_zoo/official/cv/googlenet/README.md +++ b/model_zoo/official/cv/googlenet/README.md @@ -36,7 +36,7 @@ GoogleNet, a 22 layers deep network, was proposed in 2014 and won the first plac # [Model Architecture](#contents) -Specifically, the GoogleNet contains numerous inception modules, which are connected together to go deeper. In general, an inception module with dimensionality reduction consists of **1×1 conv**, **3×3 conv**, **5×5 conv**, and **3×3 max pooling**, which are done altogether for the previous input, and stack together again at output. +Specifically, the GoogleNet contains numerous inception modules, which are connected together to go deeper. In general, an inception module with dimensionality reduction consists of **1×1 conv**, **3×3 conv**, **5×5 conv**, and **3×3 max pooling**, which are done altogether for the previous input, and stack together again at output. In our model architecture, the kernel size used in inception module is 3×3 instead of 5×5. @@ -297,13 +297,14 @@ Parameters for both training and evaluation can be set in config.py ## [Performance](#contents) ### Evaluation Performance +#### GoogleNet on CIFAR-10 | Parameters | Ascend | GPU | | -------------------------- | ----------------------------------------------------------- | ---------------------- | | Model Version | Inception V1 | Inception V1 | -| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G | NV SMX2 V100-32G | +| Resource | Ascend 910 ；CPU 2.60GHz，192cores；Memory，755G | NV SMX2 V100-32G | | uploaded Date | 10/28/2020 (month/day/year) | 10/28/2020 (month/day/year) | -| MindSpore Version | 1.0.0 | 1.0.0 | +| MindSpore Version | 1.0.0 | 1.0.0 | | Dataset | CIFAR-10 | CIFAR-10 | | Training Parameters | epoch=125, steps=390, batch_size = 128, lr=0.1 | epoch=125, steps=390, batch_size=128, lr=0.1 | | Optimizer | SGD | SGD | @@ -317,8 +318,28 @@ Parameters for both training and evaluation can be set in config.py | Model for inference | 21.50M (.onnx file), 21.60M(.air file) | | | Scripts | [googlenet script](https://gitee.com/mindspore/mindspore/tree/r1.0/model_zoo/official/cv/googlenet) | [googlenet script](https://gitee.com/mindspore/mindspore/tree/r1.0/model_zoo/official/cv/googlenet) | +#### GoogleNet on 1200k images +| Parameters | Ascend | +| -------------------------- | ----------------------------------------------------------- | +| Model Version | Inception V1 | +| Resource | Ascend 910, CPU 2.60GHz, 56cores, Memory 314G | +| uploaded Date | 10/28/2020 (month/day/year) | +| MindSpore Version | 1.0.0 | +| Dataset | 1200k images | +| Training Parameters | epoch=300, steps=5000, batch_size=256, lr=0.1 | +| Optimizer | Momentum | +| Loss Function | Softmax Cross Entropy | +| outputs | probability | +| Loss | 2.0 | +| Speed | 1pc: 152 ms/step; 8pcs: 171 ms/step | +| Total time | 8pcs: 8.8 hours | +| Parameters (M) | 13.0 | +| Checkpoint for Fine tuning | 52M (.ckpt file) | +| Scripts | [googlenet script](https://gitee.com/mindspore/mindspore/tree/r1.0/model_zoo/official/cv/googlenet) | + ### Inference Performance +#### GoogleNet on CIFAR-10 | Parameters | Ascend | GPU | | ------------------- | --------------------------- | --------------------------- | @@ -332,6 +353,18 @@ Parameters for both training and evaluation can be set in config.py | Accuracy | 1pc: 93.4%; 8pcs: 92.17% | 1pc: 93%, 8pcs: 92.89% | | Model for inference | 21.50M (.onnx file) | | +#### GoogleNet on 1200k images +| Parameters | Ascend | +| ------------------- | --------------------------- | +| Model Version | Inception V1 | +| Resource | Ascend 910 | +| Uploaded Date | 10/28/2020 (month/day/year) | +| MindSpore Version | 1.0.0 | +| Dataset | 1200k images | +| batch_size | 256 | +| outputs | probability | +| Accuracy | 8pcs: 71.81% | + ## [How to use](#contents) ### Inference