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[Docs] Fix mdformat version to support python3.6 #2014

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Jun 9, 2022
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[Docs] Fix mdformat version to support python3.6 #2014

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c1b710f
[Docs] Refine documentation
zhouzaida May 27, 2022
a7cff22
fix mdformat version to support python3.6
zhouzaida Jun 7, 2022
f13a7ef
remove ruby dependency from CI
zhouzaida Jun 9, 2022
4a26f60
fix invalid links
zhouzaida Jun 9, 2022
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4 changes: 0 additions & 4 deletions .github/workflows/lint.yml
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Expand Up @@ -17,10 +17,6 @@ jobs:
python-version: 3.7
- name: Install pre-commit hook
run: |
# markdownlint requires ruby >= 2.7
sudo apt-add-repository ppa:brightbox/ruby-ng -y
sudo apt-get update
sudo apt-get install -y ruby2.7
pip install pre-commit
pre-commit install
- name: Linting
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4 changes: 2 additions & 2 deletions .pre-commit-config.yaml
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Expand Up @@ -30,12 +30,12 @@ repos:
hooks:
- id: codespell
- repo: https://github.com/executablebooks/mdformat
rev: 0.7.14
rev: 0.7.9
hooks:
- id: mdformat
args: ["--number"]
additional_dependencies:
- mdformat-gfm
- mdformat-openmmlab
- mdformat_frontmatter
- linkify-it-py
- repo: https://github.com/myint/docformatter
Expand Down
46 changes: 23 additions & 23 deletions TERMINOLOGY.md
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Expand Up @@ -4,27 +4,27 @@ This document is used as a reference for English-Chinese terminology translation

该文档用作中英文翻译对照参考。

| English | 中文 |
| :---------------: | :----: |
| annotation | 标注 |
| backbone | 主干网络 |
| benchmark | 基准测试 |
| English | 中文 |
| :---------------: | :----------: |
| annotation | 标注 |
| backbone | 主干网络 |
| benchmark | 基准测试 |
| checkpoint | 模型权重文件 |
| classifier | 分类器 |
| cls_head | 分类头 |
| decoder | 解码器 |
| detector | 检测器 |
| encoder | 编码器 |
| finetune | 微调 |
| ground truth | 真实标签 |
| hook | 钩子 |
| localizer | 定位器 |
| neck | 模型颈部 |
| pipeline | 流水线 |
| recognizer | 识别器 |
| register | 注册器 |
| schedule | 调整 |
| scheduler | 调度器 |
| segmentor | 分割器 |
| tensor | 张量 |
| training schedule | 训练策略 |
| classifier | 分类器 |
| cls_head | 分类头 |
| decoder | 解码器 |
| detector | 检测器 |
| encoder | 编码器 |
| finetune | 微调 |
| ground truth | 真实标签 |
| hook | 钩子 |
| localizer | 定位器 |
| neck | 模型颈部 |
| pipeline | 流水线 |
| recognizer | 识别器 |
| register | 注册器 |
| schedule | 调整 |
| scheduler | 调度器 |
| segmentor | 分割器 |
| tensor | 张量 |
| training schedule | 训练策略 |
4 changes: 2 additions & 2 deletions docs/en/deployment/onnxruntime_op.md
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Expand Up @@ -107,7 +107,7 @@ Take custom operator `soft_nms` for example.

2. Add source `soft_nms.cpp` to ONNX Runtime source directory `mmcv/ops/csrc/onnxruntime/cpu/`

3. Register `soft_nms` operator in [onnxruntime_register.cpp](../../mmcv/ops/csrc/onnxruntime/cpu/onnxruntime_register.cpp)
3. Register `soft_nms` operator in [onnxruntime_register.cpp](../../../mmcv/ops/csrc/onnxruntime/cpu/onnxruntime_register.cpp)

```c++
#include "soft_nms.h"
Expand All @@ -133,4 +133,4 @@ Take custom operator `soft_nms` for example.
### References

- [How to export Pytorch model with custom op to ONNX and run it in ONNX Runtime](https://github.com/onnx/tutorials/blob/master/PyTorchCustomOperator/README.md)
- [How to add a custom operator/kernel in ONNX Runtime](https://github.com/microsoft/onnxruntime/blob/master/docs/AddingCustomOp.md)
- [How to add a custom operator/kernel in ONNX Runtime](https://onnxruntime.ai/docs/reference/operators/add-custom-op.html)
152 changes: 76 additions & 76 deletions docs/zh_cn/deployment/onnxruntime_custom_ops.md
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Expand Up @@ -2,55 +2,55 @@

<!-- TOC -->

- [ONNX Runtime自定义算子](#onnx-runtime%E8%87%AA%E5%AE%9A%E4%B9%89%E7%AE%97%E5%AD%90)
- [ONNX Runtime自定义算子](#onnx-runtime自定义算子)
- [SoftNMS](#softnms)
- [描述](#%E6%8F%8F%E8%BF%B0)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0)
- [输入](#%E8%BE%93%E5%85%A5)
- [输出](#%E8%BE%93%E5%87%BA)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F)
- [描述](#描述)
- [模型参数](#模型参数)
- [输入](#输入)
- [输出](#输出)
- [类型约束](#类型约束)
- [RoIAlign](#roialign)
- [描述](#%E6%8F%8F%E8%BF%B0-1)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0-1)
- [输入](#%E8%BE%93%E5%85%A5-1)
- [输出](#%E8%BE%93%E5%87%BA-1)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F-1)
- [描述](#描述-1)
- [模型参数](#模型参数-1)
- [输入](#输入-1)
- [输出](#输出-1)
- [类型约束](#类型约束-1)
- [NMS](#nms)
- [描述](#%E6%8F%8F%E8%BF%B0-2)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0-2)
- [输入](#%E8%BE%93%E5%85%A5-2)
- [输出](#%E8%BE%93%E5%87%BA-2)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F-2)
- [描述](#描述-2)
- [模型参数](#模型参数-2)
- [输入](#输入-2)
- [输出](#输出-2)
- [类型约束](#类型约束-2)
- [grid_sampler](#grid_sampler)
- [描述](#%E6%8F%8F%E8%BF%B0-3)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0-3)
- [输入](#%E8%BE%93%E5%85%A5-3)
- [输出](#%E8%BE%93%E5%87%BA-3)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F-3)
- [描述](#描述-3)
- [模型参数](#模型参数-3)
- [输入](#输入-3)
- [输出](#输出-3)
- [类型约束](#类型约束-3)
- [CornerPool](#cornerpool)
- [描述](#%E6%8F%8F%E8%BF%B0-4)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0-4)
- [输入](#%E8%BE%93%E5%85%A5-4)
- [输出](#%E8%BE%93%E5%87%BA-4)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F-4)
- [描述](#描述-4)
- [模型参数](#模型参数-4)
- [输入](#输入-4)
- [输出](#输出-4)
- [类型约束](#类型约束-4)
- [cummax](#cummax)
- [描述](#%E6%8F%8F%E8%BF%B0-5)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0-5)
- [输入](#%E8%BE%93%E5%85%A5-5)
- [输出](#%E8%BE%93%E5%87%BA-5)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F-5)
- [描述](#描述-5)
- [模型参数](#模型参数-5)
- [输入](#输入-5)
- [输出](#输出-5)
- [类型约束](#类型约束-5)
- [cummin](#cummin)
- [描述](#%E6%8F%8F%E8%BF%B0-6)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0-6)
- [输入](#%E8%BE%93%E5%85%A5-6)
- [输出](#%E8%BE%93%E5%87%BA-6)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F-6)
- [描述](#描述-6)
- [模型参数](#模型参数-6)
- [输入](#输入-6)
- [输出](#输出-6)
- [类型约束](#类型约束-6)
- [MMCVModulatedDeformConv2d](#mmcvmodulateddeformconv2d)
- [描述](#%E6%8F%8F%E8%BF%B0-7)
- [模型参数](#%E6%A8%A1%E5%9E%8B%E5%8F%82%E6%95%B0-7)
- [输入](#%E8%BE%93%E5%85%A5-7)
- [输出](#%E8%BE%93%E5%87%BA-7)
- [类型约束](#%E7%B1%BB%E5%9E%8B%E7%BA%A6%E6%9D%9F-7)
- [描述](#描述-7)
- [模型参数](#模型参数-7)
- [输入](#输入-7)
- [输出](#输出-7)
- [类型约束](#类型约束-7)

<!-- TOC -->

Expand All @@ -62,13 +62,13 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| ------- | --------------- | -------------------------------------------------- |
| `float` | `iou_threshold` | 用来判断候选框重合度的阈值，取值范围\[0, 1\]。默认值为0 |
| `float` | `sigma` | 高斯方法的超参数 |
| `float` | `min_score` | NMS的score阈值 |
| 类型 | 参数名 | 描述 |
| ------- | --------------- | ------------------------------------------------------- |
| `float` | `iou_threshold` | 用来判断候选框重合度的阈值，取值范围\[0, 1\]。默认值为0 |
| `float` | `sigma` | 高斯方法的超参数 |
| `float` | `min_score` | NMS的score阈值 |
| `int` | `method` | NMS的计算方式, (0: `naive`, 1: `linear`, 2: `gaussian`) |
| `int` | `offset` | 用来计算候选框的宽高(x2 - x1 + offset)。可选值0或1 |
| `int` | `offset` | 用来计算候选框的宽高(x2 - x1 + offset)。可选值0或1 |
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#### 输入

Expand Down Expand Up @@ -100,13 +100,13 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| ------- | ---------------- | ----------------------------------- |
| `int` | `output_height` | roi特征的输出高度 |
| `int` | `output_width` | roi特征的输出宽度 |
| `float` | `spatial_scale` | 输入检测框的缩放系数 |
| `int` | `sampling_ratio` | 输出的采样率。`0`表示使用密集采样 |
| `str` | `mode` | 池化方式。 `avg`或`max` |
| 类型 | 参数名 | 描述 |
| ------- | ---------------- | ------------------------------------------------------- |
| `int` | `output_height` | roi特征的输出高度 |
| `int` | `output_width` | roi特征的输出宽度 |
| `float` | `spatial_scale` | 输入检测框的缩放系数 |
| `int` | `sampling_ratio` | 输出的采样率。`0`表示使用密集采样 |
| `str` | `mode` | 池化方式。 `avg`或`max` |
| `int` | `aligned` | 如果`aligned=1`，则像素会进行-0.5的偏移以达到更好的对齐 |

#### 输入
Expand Down Expand Up @@ -137,10 +137,10 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| ------- | --------------- | ----------------------------------- |
| `float` | `iou_threshold` | 用来判断候选框重合度的阈值，取值范围\[0, 1\]。默认值为0 |
| `int` | `offset` | 用来计算候选框的宽高(x2 - x1 + offset)。可选值0或1 |
| 类型 | 参数名 | 描述 |
| ------- | --------------- | ------------------------------------------------------- |
| `float` | `iou_threshold` | 用来判断候选框重合度的阈值，取值范围\[0, 1\]。默认值为0 |
| `int` | `offset` | 用来计算候选框的宽高(x2 - x1 + offset)。可选值0或1 |

#### 输入

Expand Down Expand Up @@ -170,10 +170,10 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| ----- | -------------------- | ------------------------------------------------------------------------------------------------ |
| `int` | `interpolation_mode` | 计算输出使用的插值模式。(0: `bilinear` , 1: `nearest`) |
| `int` | `padding_mode` | 边缘填充模式。(0: `zeros`, 1: `border`, 2: `reflection`) |
| 类型 | 参数名 | 描述 |
| ----- | -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| `int` | `interpolation_mode` | 计算输出使用的插值模式。(0: `bilinear` , 1: `nearest`) |
| `int` | `padding_mode` | 边缘填充模式。(0: `zeros`, 1: `border`, 2: `reflection`) |
| `int` | `align_corners` | 如果`align_corners=1`，则极值(`-1`和`1`)会被当做输入边缘像素的中心点。如果`align_corners=0`，则它们会被看做是边缘像素的边缘点,减小分辨率对采样的影响 |

#### 输入
Expand Down Expand Up @@ -204,8 +204,8 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| ----- | ------ | --------------------------------------------------- |
| 类型 | 参数名 | 描述 |
| ----- | ------ | -------------------------------------------------------- |
| `int` | `mode` | 池化模式。(0: `top`, 1: `bottom`, 2: `left`, 3: `right`) |

#### 输入
Expand Down Expand Up @@ -234,9 +234,9 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| ----- | ----- | --------- |
| `int` | `dim` | 进行累计计算的维度 |
| 类型 | 参数名 | 描述 |
| ----- | ------ | ------------------ |
| `int` | `dim` | 进行累计计算的维度 |

#### 输入

Expand Down Expand Up @@ -266,9 +266,9 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| ----- | ----- | --------- |
| `int` | `dim` | 进行累计计算的维度 |
| 类型 | 参数名 | 描述 |
| ----- | ------ | ------------------ |
| `int` | `dim` | 进行累计计算的维度 |

#### 输入

Expand Down Expand Up @@ -298,12 +298,12 @@

#### 模型参数

| 类型 | 参数名 | 描述 |
| -------------- | ------------------- | -------------------------------------- |
| `list of ints` | `stride` | 卷积的步长 (sH, sW) |
| `list of ints` | `padding` | 输入特征填充大小 (padH, padW) |
| `list of ints` | `dilation` | 卷积核各元素间隔 (dH, dW) |
| `int` | `deformable_groups` | 可变偏移量的分组，通常置位1即可 |
| 类型 | 参数名 | 描述 |
| -------------- | ------------------- | ------------------------------------------------------------- |
| `list of ints` | `stride` | 卷积的步长 (sH, sW) |
| `list of ints` | `padding` | 输入特征填充大小 (padH, padW) |
| `list of ints` | `dilation` | 卷积核各元素间隔 (dH, dW) |
| `int` | `deformable_groups` | 可变偏移量的分组，通常置位1即可 |
| `int` | `groups` | 卷积分组数，`input_channel`会根据这个值被分为数个分组进行计算 |

#### 输入
Expand Down
24 changes: 12 additions & 12 deletions docs/zh_cn/deployment/onnxruntime_op.md
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Expand Up @@ -15,16 +15,16 @@

### MMCV已支持的算子

| 算子 | CPU | GPU | MMCV版本 |
| :------------------------------------------------------------------------------: | :-: | :-: | :----: |
| [SoftNMS](onnxruntime_custom_ops.md#softnms) | Y | N | 1.2.3 |
| [RoIAlign](onnxruntime_custom_ops.md#roialign) | Y | N | 1.2.5 |
| [NMS](onnxruntime_custom_ops.md#nms) | Y | N | 1.2.7 |
| [grid_sampler](onnxruntime_custom_ops.md#grid_sampler) | Y | N | 1.3.1 |
| [CornerPool](onnxruntime_custom_ops.md#cornerpool) | Y | N | 1.3.4 |
| [cummax](onnxruntime_custom_ops.md#cummax) | Y | N | 1.3.4 |
| [cummin](onnxruntime_custom_ops.md#cummin) | Y | N | 1.3.4 |
| [MMCVModulatedDeformConv2d](onnxruntime_custom_ops.md#mmcvmodulateddeformconv2d) | Y | N | 1.3.12 |
| 算子 | CPU | GPU | MMCV版本 |
| :------------------------------------------------------------------------------: | :-: | :-: | :------: |
| [SoftNMS](onnxruntime_custom_ops.md#softnms) | Y | N | 1.2.3 |
| [RoIAlign](onnxruntime_custom_ops.md#roialign) | Y | N | 1.2.5 |
| [NMS](onnxruntime_custom_ops.md#nms) | Y | N | 1.2.7 |
| [grid_sampler](onnxruntime_custom_ops.md#grid_sampler) | Y | N | 1.3.1 |
| [CornerPool](onnxruntime_custom_ops.md#cornerpool) | Y | N | 1.3.4 |
| [cummax](onnxruntime_custom_ops.md#cummax) | Y | N | 1.3.4 |
| [cummin](onnxruntime_custom_ops.md#cummin) | Y | N | 1.3.4 |
| [MMCVModulatedDeformConv2d](onnxruntime_custom_ops.md#mmcvmodulateddeformconv2d) | Y | N | 1.3.12 |

### 如何编译ONNX Runtime自定义算子？

Expand Down Expand Up @@ -100,7 +100,7 @@ onnx_results = sess.run(None, {'input' : input_data})

2. 在ONNX Runtime源码目录`mmcv/ops/csrc/onnxruntime/cpu/`下添加算子实现`soft_nms.cpp`

3. 在[onnxruntime_register.cpp](../../mmcv/ops/csrc/onnxruntime/cpu/onnxruntime_register.cpp)中注册实现的算子`soft_nms`
3. 在[onnxruntime_register.cpp](../../../mmcv/ops/csrc/onnxruntime/cpu/onnxruntime_register.cpp)中注册实现的算子`soft_nms`

```c++
#include "soft_nms.h"
Expand All @@ -126,4 +126,4 @@ onnx_results = sess.run(None, {'input' : input_data})
### 引用

- [How to export Pytorch model with custom op to ONNX and run it in ONNX Runtime](https://github.com/onnx/tutorials/blob/master/PyTorchCustomOperator/README.md)
- [How to add a custom operator/kernel in ONNX Runtime](https://github.com/microsoft/onnxruntime/blob/master/docs/AddingCustomOp.md)
- [How to add a custom operator/kernel in ONNX Runtime](https://onnxruntime.ai/docs/reference/operators/add-custom-op.html)
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