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!6643 Modifying the hardware information in Readme.

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Merge pull request !6643 from linqingke/modelzoo
pull/6643/MERGE
mindspore-ci-bot 5 years ago committed by Gitee
parent 9a5f9d137d 3f7a5ed394
commit a712489a28
26 changed files with 32 additions and 32 deletions
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2
model_zoo/official/cv/alexnet/README.md
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@ -193,7 +193,7 @@ Before running the command below, please check the checkpoint path used for eval
| Parameters | Ascend | GPU |
| -------------------------- | ------------------------------------------------------------| -------------------------------------------------|
| 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 | 06/09/2020 (month/day/year) | 17/09/2020 (month/day/year) |
| MindSpore Version | 0.5.0-beta | 0.7.0-beta |
| Dataset | CIFAR-10 | CIFAR-10 |

4
model_zoo/official/cv/densenet121/scripts/run_distribute_eval.sh
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@ -16,8 +16,8 @@
echo "=============================================================================================================="
echo "Please run the scipt as: "
echo "sh run_distribute_eval.sh DEVICE_NUM RANK_TABLE_FILE DATASET CKPT_PATH"
echo "for example: sh run_distribute_train.sh 8 /data/hccl.json /path/to/dataset /path/to/ckpt"
echo "sh scripts/run_distribute_eval.sh DEVICE_NUM RANK_TABLE_FILE DATASET CKPT_PATH"
echo "for example: sh scripts/run_distribute_train.sh 8 /data/hccl.json /path/to/dataset /path/to/ckpt"
echo "It is better to use absolute path."
echo "================================================================================================================="

2
model_zoo/official/cv/faster_rcnn/README.md
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@ -207,7 +207,7 @@ Eval result will be stored in the example path, whose folder name is "eval". Und
| Parameters | FasterRcnn |
| -------------------------- | ----------------------------------------------------------- |
| Model Version | V1 |
| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |
| Resource | Ascend 910 ；CPU 2.60GHz，192cores；Memory，755G |
| uploaded Date | 08/31/2020 (month/day/year) |
| MindSpore Version | 0.7.0-beta |
| Dataset | COCO2017 |

2
model_zoo/official/cv/googlenet/README.md
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@ -310,7 +310,7 @@ For more configuration details, please refer the script `config.py`.
| 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 | 08/31/2020 (month/day/year) | 08/20/2020 (month/day/year) |
| MindSpore Version | 0.7.0-alpha | 0.6.0-alpha |
| Dataset | CIFAR-10 | CIFAR-10 |

4
model_zoo/official/cv/inceptionv3/README.md
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@ -222,7 +222,7 @@ metric: {'Loss': 1.778, 'Top1-Acc':0.788, 'Top5-Acc':0.942}
| Parameters | Ascend | GPU |
| -------------------------- | ---------------------------------------------- | ------------------------- |
| Model Version | InceptionV3 | InceptionV3 |
| Resource | Ascend 910, cpu:2.60GHz 56cores, memory:314G | NV SMI V100-16G(PCIE),cpu:2.10GHz 96cores, memory:250G |
| Resource | Ascend 910, cpu:2.60GHz 192cores, memory:755G | NV SMI V100-16G(PCIE),cpu:2.10GHz 96cores, memory:250G |
| uploaded Date | 08/21/2020 | 08/21/2020 |
| MindSpore Version | 0.6.0-beta | 0.6.0-beta |
| Dataset | 1200k images | 1200k images |
@ -244,7 +244,7 @@ metric: {'Loss': 1.778, 'Top1-Acc':0.788, 'Top5-Acc':0.942}
| Parameters | Ascend |
| ------------------- | --------------------------- |
| Model Version | InceptionV3 |
| Resource | Ascend 910, cpu:2.60GHz 56cores, memory:314G |
| Resource | Ascend 910, cpu:2.60GHz 192cores, memory:755G |
| Uploaded Date | 08/22/2020 |
| MindSpore Version | 0.6.0-beta |
| Dataset | 50k images |

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model_zoo/official/cv/lenet/README.md
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@ -164,7 +164,7 @@ You can view the results through the file "log.txt". The accuracy of the test da
| Parameters | LeNet |
| -------------------------- | ----------------------------------------------------------- |
| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |
| Resource | Ascend 910 ；CPU 2.60GHz，192cores；Memory，755G |
| uploaded Date | 06/09/2020 (month/day/year) |
| MindSpore Version | 0.5.0-beta |
| Dataset | MNIST |

2
model_zoo/official/cv/lenet_quant/Readme.md
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@ -161,7 +161,7 @@ You can view the results through the file "log.txt". The accuracy of the test da
| Parameters | LeNet |
| -------------------------- | ----------------------------------------------------------- |
| Resource | Ascend 910 CPU 2.60GHz 56cores Memory 314G |
| Resource | Ascend 910 CPU 2.60GHz 192cores Memory 755G |
| uploaded Date | 06/09/2020 (month/day/year) |
| MindSpore Version | 0.5.0-beta |
| Dataset | MNIST |

2
model_zoo/official/cv/maskrcnn/README.md
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@ -400,7 +400,7 @@ Accumulating evaluation results...
| Parameters | MaskRCNN |
| -------------------------- | ----------------------------------------------------------- |
| Model Version | V1 |
| Resource | Ascend 910; CPU 2.60GHz, 56cores; Memory, 314G |
| Resource | Ascend 910; CPU 2.60GHz, 192cores; Memory, 755G |
| uploaded Date | 08/01/2020 (month/day/year) |
| MindSpore Version | 0.6.0-alpha |
| Dataset | COCO2017 |

2
model_zoo/official/cv/mobilenetv2/README.md
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@ -181,7 +181,7 @@ result: {'acc': 0.71976314102564111} ckpt=/path/to/checkpoint/mobilenet-200_625.
| Parameters | MobilenetV2 | |
| -------------------------- | ---------------------------------------------------------- | ------------------------- |
| Model Version | V1 | 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 | 05/06/2020 | 05/06/2020 |
| MindSpore Version | 0.3.0 | 0.3.0 |
| Dataset | ImageNet | ImageNet |

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model_zoo/official/cv/mobilenetv2_quant/Readme.md
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@ -175,7 +175,7 @@ result: {'acc': 0.71976314102564111}
| Parameters | MobilenetV2 |
| -------------------------- | ---------------------------------------------------------- |
| Model Version | V2 |
| Resource | Ascend 910, cpu:2.60GHz 56cores, memory:314G |
| Resource | Ascend 910, cpu:2.60GHz 192cores, memory:755G |
| uploaded Date | 06/06/2020 |
| MindSpore Version | 0.3.0 |
| Dataset | ImageNet |

2
model_zoo/official/cv/psenet/README.md
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@ -161,7 +161,7 @@ Calculated!{"precision": 0.814796668299853, "recall": 0.8006740491092923, "hmean
| Parameters | PSENet |
| -------------------------- | ----------------------------------------------------------- |
| Model Version | Inception V1 |
| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |
| Resource | Ascend 910 ；CPU 2.60GHz，192cores；Memory，755G |
| uploaded Date | 09/15/2020 (month/day/year) |
| MindSpore Version | 1.0-alpha |
| Dataset | ICDAR2015 |

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model_zoo/official/cv/resnet/README.md
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@ -398,7 +398,7 @@ result: {'top_5_accuracy': 0.9342589628681178, 'top_1_accuracy': 0.7680657810499
| Parameters | Ascend 910 | GPU |
| -------------------------- | -------------------------------------- |---------------------------------- |
| Model Version | ResNet50-v1.5 |ResNet50-v1.5|
| Resource | Ascend 910，CPU 2.60GHz 56cores，Memory 314G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| uploaded Date | 04/01/2020 (month/day/year) | 08/01/2020 (month/day/year)
| MindSpore Version | 0.1.0-alpha |0.6.0-alpha |
| Dataset | CIFAR-10 | CIFAR-10
@ -417,7 +417,7 @@ result: {'top_5_accuracy': 0.9342589628681178, 'top_1_accuracy': 0.7680657810499
| Parameters | Ascend 910 | GPU |
| -------------------------- | -------------------------------------- |---------------------------------- |
| Model Version | ResNet50-v1.5 |ResNet50-v1.5|
| Resource | Ascend 910，CPU 2.60GHz 56cores，Memory 314G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| uploaded Date | 04/01/2020 (month/day/year) ； | 08/01/2020 (month/day/year)
| MindSpore Version | 0.1.0-alpha |0.6.0-alpha |
| Dataset | ImageNet2012 | ImageNet2012|
@ -436,7 +436,7 @@ result: {'top_5_accuracy': 0.9342589628681178, 'top_1_accuracy': 0.7680657810499
| Parameters | Ascend 910 | GPU |
| -------------------------- | -------------------------------------- |---------------------------------- |
| Model Version | ResNet101 |ResNet101|
| Resource | Ascend 910，CPU 2.60GHz 56cores，Memory 314G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| uploaded Date | 04/01/2020 (month/day/year) | 08/01/2020 (month/day/year)
| MindSpore Version | 0.1.0-alpha |0.6.0-alpha |
| Dataset | ImageNet2012 | ImageNet2012|
@ -456,7 +456,7 @@ result: {'top_5_accuracy': 0.9342589628681178, 'top_1_accuracy': 0.7680657810499
| Parameters | Ascend 910
| -------------------------- | ------------------------------------------------------------------------ |
| Model Version | SE-ResNet50 |
| Resource | Ascend 910，CPU 2.60GHz 56cores，Memory 314G |
| Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G |
| uploaded Date | 08/16/2020 (month/day/year) ； |
| MindSpore Version | 0.7.0-alpha |
| Dataset | ImageNet2012 |

2
model_zoo/official/cv/resnet50_quant/Readme.md
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@ -170,7 +170,7 @@ result: {'acc': 0.76576314102564111}
| Parameters | Resnet50 |
| -------------------------- | ---------------------------------------------------------- |
| Model Version | V1 |
| Resource | Ascend 910, cpu:2.60GHz 56cores, memory:314G |
| Resource | Ascend 910, cpu:2.60GHz 192cores, memory:755G |
| uploaded Date | 06/06/2020 |
| MindSpore Version | 0.3.0 |
| Dataset | ImageNet |

2
model_zoo/official/cv/resnet_thor/README.md
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@ -228,7 +228,7 @@ Inference result will be stored in the example path, whose folder name is "eval"
| Parameters | Ascend 910 | GPU |
| -------------------------- | -------------------------------------- |---------------------------------- |
| Model Version | ResNet50-v1.5 |ResNet50-v1.5|
| Resource | Ascend 910，CPU 2.60GHz 56cores，Memory 314G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G
| uploaded Date | 06/01/2020 (month/day/year) |
| MindSpore Version | 0.3.0-alpha | |
| Dataset | ImageNet2012 | ImageNet2012|

2
model_zoo/official/cv/resnext50/README.md
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@ -213,7 +213,7 @@ acc=93.88%(TOP5)
| Parameters | ResNeXt50 | |
| -------------------------- | ---------------------------------------------------------- | ------------------------- |
| 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 | 06/30/2020 | 07/23/2020 |
| MindSpore Version | 0.5.0 | 0.6.0 |
| Dataset | ImageNet | ImageNet |

2
model_zoo/official/cv/ssd/README.md
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@ -227,7 +227,7 @@ mAP: 0.23808886505483504
| Parameters | Ascend |
| -------------------------- | -------------------------------------------------------------|
| Model Version | SSD V1 |
| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |
| Resource | Ascend 910 ；CPU 2.60GHz，192cores；Memory，755G |
| uploaded Date | 06/01/2020 (month/day/year) |
| MindSpore Version | 0.3.0-alpha |
| Dataset | COCO2017 |

2
model_zoo/official/cv/unet/README.md
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@ -216,7 +216,7 @@ step: 300, loss is 0.18949677, fps is 57.63118508760329
| Parameters | Ascend |
| -------------------------- | ------------------------------------------------------------ |
| Model Version | Unet |
| Resource | Ascend 910 ;CPU 2.60GHz,56cores; Memory,314G |
| Resource | Ascend 910 ;CPU 2.60GHz,192cores; Memory,755G |
| uploaded Date | 09/15/2020 (month/day/year) |
| MindSpore Version | 1.0.0 |
| Dataset | ISBI |

2
model_zoo/official/cv/vgg16/README.md
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@ -339,7 +339,7 @@ after allreduce eval: top5_correct=45582, tot=50000, acc=91.16%
| Parameters | VGG16(Ascend) | VGG16(GPU) |
| -------------------------- | ---------------------------------------------- |------------------------------------|
| Model Version | VGG16 | VGG16 |
| 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 | 08/20/2020 |08/20/2020 |
| MindSpore Version | 0.5.0-alpha |0.5.0-alpha |
| Dataset | CIFAR-10 |ImageNet2012 |

2
model_zoo/official/cv/warpctc/README.md
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@ -200,7 +200,7 @@ bash run_eval.sh [DATASET_PATH] [CHECKPOINT_PATH] [PLATFORM]
| Parameters | Ascend 910 | GPU |
| -------------------------- | --------------------------------------------- |---------------------------------- |
| Model Version | v1.0 | v1.0 |
| Resource | Ascend 910，CPU 2.60GHz 56cores，Memory 314G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G /
| Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G | GPU(Tesla V100 SXM2)，CPU 2.1GHz 24cores，Memory 128G /
| uploaded Date | 07/01/2020 (month/day/year) | 08/01/2020 (month/day/year) |
| MindSpore Version | 0.5.0-alpha | 0.6.0-alpha |
| Dataset | Captcha | Captcha |

2
model_zoo/official/cv/yolov3_resnet18/README.md
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@ -202,7 +202,7 @@ Note the precision and recall values are results of two-classification(person an
| Parameters | Ascend |
| -------------------------- | ----------------------------------------------------------- |
| Model Version | YOLOv3_Resnet18 V1 |
| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |
| Resource | Ascend 910 ；CPU 2.60GHz，192cores；Memory，755G |
| uploaded Date | 06/01/2020 (month/day/year) |
| MindSpore Version | 0.2.0-alpha |
| Dataset | COCO2017 |

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model_zoo/official/nlp/bert/README.md
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@ -445,7 +445,7 @@ The result will be as follows:
| Parameters | Ascend | GPU |
| -------------------------- | ---------------------------------------------------------- | ------------------------- |
| Model Version | BERT_base | BERT_base |
| 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 | 08/22/2020 | 05/06/2020 |
| MindSpore Version | 0.6.0 | 0.3.0 |
| Dataset | cn-wiki-128(4000w) | ImageNet |
@ -465,7 +465,7 @@ The result will be as follows:
| Parameters | Ascend | GPU |
| -------------------------- | ---------------------------------------------------------- | ------------------------- |
| Model Version | BERT_NEZHA | BERT_NEZHA |
| 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 | 08/20/2020 | 05/06/2020 |
| MindSpore Version | 0.6.0 | 0.3.0 |
| Dataset | cn-wiki-128(4000w) | ImageNet |

2
model_zoo/official/nlp/bert_thor/README.md
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@ -192,7 +192,7 @@ step: 3000 Accuracy: [0.71377236]
| Parameters | Ascend 910 |
| -------------------------- | -------------------------------------- |
| Model Version | BERT-LARGE |
| Resource | Ascend 910，CPU 2.60GHz 56cores，Memory 314G |
| Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G |
| uploaded Date | 08/20/2020 (month/day/year) |
| MindSpore Version | 0.6.0-alpha |
| Dataset | MLPerf v0.7 dataset |

2
model_zoo/official/nlp/mass/README.md
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@ -588,7 +588,7 @@ The comparisons between MASS and other baseline methods in terms of PPL on Corne
| Parameters | Masked Sequence to Sequence Pre-training for Language Generation |
|:---------------------------|:--------------------------------------------------------------------------|
| Model Version | v1 |
| Resource | Ascend 910, cpu 2.60GHz, 56cores；memory, 314G |
| Resource | Ascend 910, cpu 2.60GHz, 192cores；memory, 755G |
| uploaded Date | 05/24/2020 |
| MindSpore Version | 0.2.0 |
| Dataset | News Crawl 2007-2017 English monolingual corpus, Gigaword corpus, Cornell Movie Dialog corpus |

2
model_zoo/official/nlp/tinybert/README.md
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@ -352,7 +352,7 @@ The best acc is 0.891176
| Parameters | Ascend | GPU |
| -------------------------- | ---------------------------------------------------------- | ------------------------- |
| Model Version | TinyBERT | TinyBERT |
| Resource | Ascend 910, cpu:2.60GHz 56cores, memory:314G | NV SMX2 V100-32G, cpu:2.10GHz 64cores, memory:251G |
| Resource | Ascend 910, cpu:2.60GHz 192cores, memory:755G | NV SMX2 V100-32G, cpu:2.10GHz 64cores, memory:251G |
| uploaded Date | 08/20/2020 | 08/24/2020 |
| MindSpore Version | 0.6.0 | 0.7.0 |
| Dataset | cn-wiki-128 | cn-wiki-128 |

2
model_zoo/official/recommend/deepfm/README.md
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@ -247,7 +247,7 @@ Parameters for both training and evaluation can be set in config.py
| Parameters | Ascend | GPU |
| -------------------------- | ----------------------------------------------------------- | ---------------------- |
| Model Version | DeepFM | To do |
| Resource | Ascend 910; CPU 2.60GHz, 192cores; Memory 314G | To do |
| Resource | Ascend 910; CPU 2.60GHz, 192cores; Memory 755G | To do |
| uploaded Date | 05/17/2020 (month/day/year) | To do |
| MindSpore Version | 0.3.0-alpha | To do |
| Dataset | [1] | To do |

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