[Docs]Fix docs about cfg (#184)
* add docs about config comment * fix blank * fix comment * fix comment * fix comment * fix commentpull/12/head
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@ -2,16 +2,17 @@
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<!-- TOC -->
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- [How to convert model](#how-to-convert-model)
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- [How to convert models from Pytorch to other backends](#how-to-convert-models-from-pytorch-to-other-backends)
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- [Prerequisite](#prerequisite)
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- [Usage](#usage)
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- [Description of all arguments](#description-of-all-arguments)
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- [Example](#example)
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- [How to evaluate the exported models](#how-to-evaluate-the-exported-models)
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- [List of supported models exportable to other backends](#list-of-supported-models-exportable-to-other-backends)
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- [Reminders](#reminders)
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- [FAQs](#faqs)
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- [Tutorial : How to convert model](#how-to-convert-model)
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- [How to convert models from Pytorch to BACKEND](#how-to-convert-models-from-pytorch-to-other-backends)
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- [Prerequisite](#prerequisite)
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- [Usage](#usage)
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- [Description of all arguments](#description-of-all-arguments)
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- [How to find the corresponding deployment config of a PyTorch model](#how-to-find-the-corresponding-deployment-config-of-a-pytorch-model)
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- [Example](#example)
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- [How to evaluate the exported models](#how-to-evaluate-the-exported-models)
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- [List of supported models exportable to BACKEND](#list-of-supported-models-exportable-to-other-backends)
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- [Reminders](#reminders)
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- [FAQs](#faqs)
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<!-- TOC -->
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@ -58,6 +59,12 @@ python ./tools/deploy.py \
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- `--show` : Whether to show detection outputs.
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- `--dump-info` : Whether to output information for SDK.
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#### How to find the corresponding deployment config of a PyTorch model
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1. Find model's codebase folder in `configs/ `. Example, convert a yolov3 model you need to find `configs/mmdet` folder.
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2. Find model's task folder in `configs/codebase_folder/ `. Just like yolov3 model, you need to find `configs/mmdet/single-stage` folder.
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3. Find deployment config file in `configs/codebase_folder/task_folder/ `. Just like deploy yolov3 model you can use `configs/mmdet/single-stage/single-stage_onnxruntime_dynamic.py`.
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#### Example
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```bash
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@ -19,9 +19,10 @@ This tutorial describes how to write a config for model conversion and deploymen
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- [3. How to write backend config](#3-how-to-write-backend-config)
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- [Example](#example-4)
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- [4. A complete example of mmcls on TensorRT](#4-a-complete-example-of-mmcls-on-tensorrt)
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- [5. How to write model config](#5-how-to-write-model-config)
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- [6. Reminder](#6-reminder)
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- [7. FAQs](#7-faqs)
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- [5. The name rules of our deployment config](#5-the-name-rules-of-our-deployment-config)
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- [6. How to write model config](#6-how-to-write-model-config)
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- [7. Reminder](#6-reminder)
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- [8. FAQs](#7-faqs)
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<!-- TOC -->
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@ -131,7 +132,7 @@ The backend config is mainly used to specify the backend on which model runs and
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backend_config = dict(
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type='tensorrt',
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common_config=dict(
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fp16_mode=False, log_level=trt.Logger.INFO, max_workspace_size=1 << 30)
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fp16_mode=False, log_level=trt.Logger.INFO, max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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@ -188,14 +189,33 @@ onnx_config = dict(
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partition_config = None
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```
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### 5. How to write model config
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### 5. The name rules of our deployment config
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There is a specific naming convention for the filename of deployment config files.
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```bash
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(task name)_(partition)_(backend name)_(dynamic or static).py
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```
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- `task name`: Model's task type.
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- `partition`: Optional, whether partition model is supported.
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- `backend name`: Backend's name. Note if you use the quantization function, you need to indicate the quantization type. Just like `tensorrt_int8`.
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- `dynamic or static`: Dynamic or static export. Note if the backend needs explicit shape information, you need to add a description of input size with `height x width` format. Just like `dynamic-512x1024-2048x2048`, it means that the min input shape is `512x1024` and the max input shape is `2048x2048`.
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#### Example
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```
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single-stage_partition_tensorrt-int8_dynamic-320x320-1344x1344.py
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```
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### 6. How to write model config
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According to model's codebase, write the model config file. Model's config file is used to initialize the model, referring to [MMClassification](https://github.com/open-mmlab/mmclassification/blob/master/docs/tutorials/config.md), [MMDetection](https://github.com/open-mmlab/mmdetection/blob/master/docs_zh-CN/tutorials/config.md), [MMSegmentation](https://github.com/open-mmlab/mmsegmentation/blob/master/docs_zh-CN/tutorials/config.md), [MMOCR](https://github.com/open-mmlab/mmocr/tree/main/configs), [MMEditing](https://github.com/open-mmlab/mmediting/blob/master/docs_zh-CN/config.md).
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### 6. Reminder
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### 7. Reminder
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None
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### 7. FAQs
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### 8. FAQs
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None
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