forked from mindspore-Ecosystem/mindspore
99 lines
2.7 KiB
Markdown
99 lines
2.7 KiB
Markdown
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<TOC>
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# Title, Model name
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> The Description of Model. The paper present this model.
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## Model Architecture
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> There could be various architecture about some model. Represent the architecture of your implementation.
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## Features(optional)
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> Represent the distinctive feature you used in the model implementation. Such as distributed auto-parallel or some special training trick.
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## Dataset
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> Provide the information of the dataset you used. Check the copyrights of the dataset you used, usually don't provide the hyperlink to download the dataset.
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## Requirements
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> Provide details of the software required, including:
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>
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> * The additional python package required. Add a `requirements.txt` file to the root dir of model for installing dependencies.
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> * The necessary third-party code.
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> * Some other system dependencies.
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> * Some additional operations before training or prediction.
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## Quick Start
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> How to take a try without understanding anything about the model.
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## Script Description
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> The section provide the detail of implementation.
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### Scripts and Sample Code
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> Explain every file in your project.
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### Script Parameter
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> Explain every parameter of the model. Especially the parameters in `config.py`.
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## Training
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> Provide training information.
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### Training Process
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> Provide the usage of training scripts.
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e.g. Run the following command for distributed training on Ascend.
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```shell
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bash run_distribute_train.sh [RANK_TABLE_FILE] [PRETRAINED_MODEL]
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```
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### Transfer Training(Optional)
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> Provide the guidelines about how to run transfer training based on an pretrained model.
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### Training Result
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> Provide the result of training.
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e.g. Training checkpoint will be stored in `XXXX/ckpt_0`. You will get result from log file like the following:
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```
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epoch: 11 step: 7393 ,rpn_loss: 0.02003, rcnn_loss: 0.52051, rpn_cls_loss: 0.01761, rpn_reg_loss: 0.00241, rcnn_cls_loss: 0.16028, rcnn_reg_loss: 0.08411, rcnn_mask_loss: 0.27588, total_loss: 0.54054
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epoch: 12 step: 7393 ,rpn_loss: 0.00547, rcnn_loss: 0.39258, rpn_cls_loss: 0.00285, rpn_reg_loss: 0.00262, rcnn_cls_loss: 0.08002, rcnn_reg_loss: 0.04990, rcnn_mask_loss: 0.26245, total_loss: 0.39804
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```
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## Evaluation
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### Evaluation Process
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> Provide the use of evaluation scripts.
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### Evaluation Result
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> Provide the result of evaluation.
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## Performance
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### Training Performance
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> Provide the detail of training performance including finishing loss, throughput, checkpoint size and so on.
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### Inference Performance
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> Provide the detail of evaluation performance including latency, accuracy and so on.
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## Description of Random Situation
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> Explain the random situation in the project.
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## ModeZoo Homepage
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Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
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