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[Docs] Replace NPU with Ascend in installation documentation #2469

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[Docs] Replace NPU with Ascend in installation documentation #2469

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48 changes: 48 additions & 0 deletions docs/en/get_started/build.md
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Expand Up @@ -327,3 +327,51 @@ Firstly, you need to apply for an IPU cloud machine, see [here](https://www.grap
1. Build MMCV

2. Use pip to install sdk according to [IPU PyTorch document](https://docs.graphcore.ai/projects/poptorch-user-guide/en/latest/installation.html). Also, you need to apply for machine and sdk to Graphcore.

### Build mmcv-full on Ascend NPU machine

- Before building mmcv-full, `torch_npu` should be installed. See the complete installation tutorial [PyTorch Installation Guide](https://gitee.com/ascend/pytorch/blob/master/docs/en/PyTorch%20Installation%20Guide/PyTorch%20Installation%20Guide.md)
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#### Option 1: Install mmcv-full with pip

The Ascend compiled version of mmcv-full is already supported when the version of mmcv >= 1.7.0, we can pip install directly

```bash
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/ascend/torch1.8.0/index.html
```

#### Option 2: Build mmcv-full NPU (Ascend) from Source

- Pull the source code

```bash
git pull https://github.com/open-mmlab/mmcv/tree/master
```

- Build

```bash
MMCV_WITH_OPS=1 MAX_JOBS=8 FORCE_NPU=1 python setup.py build_ext
```

- Install

```bash
MMCV_WITH_OPS=1 FORCE_NPU=1 python setup.py develop
```

#### Test Case

```python
import torch
import torch_npu
from mmcv.ops import softmax_focal_loss

# Init tensor to the NPU
x = torch.randn(3, 10).npu()
y = torch.tensor([1, 5, 3]).npu()
w = torch.ones(10).float().npu()

output = softmax_focal_loss(x, y, 2.0, 0.25, w, 'none')
print(output)
```
116 changes: 58 additions & 58 deletions docs/en/understand_mmcv/ops.md
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Expand Up @@ -2,61 +2,61 @@

We implement common ops used in detection, segmentation, etc.

| Device | CPU | CUDA | MLU | MPS | NPU |
| ---------------------------- | --- | ---- | --- | --- | --- |
| ActiveRotatedFilter | √ | √ | | | |
| AssignScoreWithK | | √ | | | |
| BallQuery | | √ | | | |
| BBoxOverlaps | | √ | √ | √ | |
| BorderAlign | | √ | | | |
| BoxIouRotated | √ | √ | | | |
| BoxIouQuadri | √ | √ | | | |
| CARAFE | | √ | √ | | |
| ChamferDistance | | √ | | | |
| CrissCrossAttention | | √ | | | |
| ContourExpand | √ | | | | |
| ConvexIoU | | √ | | | |
| CornerPool | | √ | | | |
| Correlation | | √ | | | |
| Deformable Convolution v1/v2 | √ | √ | | | |
| Deformable RoIPool | | √ | √ | | |
| DiffIoURotated | | √ | | | |
| DynamicScatter | | √ | | | |
| FurthestPointSample | | √ | | | |
| FurthestPointSampleWithDist | | √ | | | |
| FusedBiasLeakyrelu | | √ | | | |
| GatherPoints | | √ | | | |
| GroupPoints | | √ | | | |
| Iou3d | | √ | √ | | |
| KNN | | √ | | | |
| MaskedConv | | √ | √ | | √ |
| MergeCells | | √ | | | |
| MinAreaPolygon | | √ | | | |
| ModulatedDeformConv2d | √ | √ | √ | | √ |
| MultiScaleDeformableAttn | | √ | √ | | |
| NMS | √ | √ | √ | | √ |
| NMSRotated | √ | √ | | | |
| NMSQuadri | √ | √ | | | |
| PixelGroup | √ | | | | |
| PointsInBoxes | √ | √ | | | |
| PointsInPolygons | | √ | | | |
| PSAMask | √ | √ | √ | | |
| RotatedFeatureAlign | √ | √ | | | |
| RoIPointPool3d | | √ | √ | | |
| RoIPool | | √ | √ | | |
| RoIAlignRotated | √ | √ | √ | | |
| RiRoIAlignRotated | | √ | | | |
| RoIAlign | √ | √ | √ | | |
| RoIAwarePool3d | | √ | √ | | |
| SAConv2d | | √ | | | |
| SigmoidFocalLoss | | √ | √ | | √ |
| SoftmaxFocalLoss | | √ | | | √ |
| SoftNMS | | √ | | | |
| Sparse Convolution | | √ | | | |
| Synchronized BatchNorm | | √ | | | |
| ThreeInterpolate | | √ | | | |
| ThreeNN | | √ | √ | | |
| TINShift | | √ | √ | | |
| UpFirDn2d | | √ | | | |
| Voxelization | √ | √ | | | |
| PrRoIPool | | √ | | | |
| Device | CPU | CUDA | MLU | MPS | Ascend |
| ---------------------------- | --- | ---- | --- | --- | ------ |
| ActiveRotatedFilter | √ | √ | | | |
| AssignScoreWithK | | √ | | | |
| BallQuery | | √ | | | |
| BBoxOverlaps | | √ | √ | √ | |
| BorderAlign | | √ | | | |
| BoxIouRotated | √ | √ | | | |
| BoxIouQuadri | √ | √ | | | |
| CARAFE | | √ | √ | | |
| ChamferDistance | | √ | | | |
| CrissCrossAttention | | √ | | | |
| ContourExpand | √ | | | | |
| ConvexIoU | | √ | | | |
| CornerPool | | √ | | | |
| Correlation | | √ | | | |
| Deformable Convolution v1/v2 | √ | √ | | | |
| Deformable RoIPool | | √ | √ | | |
| DiffIoURotated | | √ | | | |
| DynamicScatter | | √ | | | |
| FurthestPointSample | | √ | | | |
| FurthestPointSampleWithDist | | √ | | | |
| FusedBiasLeakyrelu | | √ | | | |
| GatherPoints | | √ | | | |
| GroupPoints | | √ | | | |
| Iou3d | | √ | √ | | |
| KNN | | √ | | | |
| MaskedConv | | √ | √ | | √ |
| MergeCells | | √ | | | |
| MinAreaPolygon | | √ | | | |
| ModulatedDeformConv2d | √ | √ | √ | | √ |
| MultiScaleDeformableAttn | | √ | √ | | |
| NMS | √ | √ | √ | | √ |
| NMSRotated | √ | √ | | | |
| NMSQuadri | √ | √ | | | |
| PixelGroup | √ | | | | |
| PointsInBoxes | √ | √ | | | |
| PointsInPolygons | | √ | | | |
| PSAMask | √ | √ | √ | | |
| RotatedFeatureAlign | √ | √ | | | |
| RoIPointPool3d | | √ | √ | | |
| RoIPool | | √ | √ | | |
| RoIAlignRotated | √ | √ | √ | | |
| RiRoIAlignRotated | | √ | | | |
| RoIAlign | √ | √ | √ | | |
| RoIAwarePool3d | | √ | √ | | |
| SAConv2d | | √ | | | |
| SigmoidFocalLoss | | √ | √ | | √ |
| SoftmaxFocalLoss | | √ | | | √ |
| SoftNMS | | √ | | | |
| Sparse Convolution | | √ | | | |
| Synchronized BatchNorm | | √ | | | |
| ThreeInterpolate | | √ | | | |
| ThreeNN | | √ | √ | | |
| TINShift | | √ | √ | | |
| UpFirDn2d | | √ | | | |
| Voxelization | √ | √ | | | |
| PrRoIPool | | √ | | | |
35 changes: 21 additions & 14 deletions docs/zh_cn/get_started/build.md
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Expand Up @@ -344,41 +344,48 @@ mmcv-full 有两个版本：

### 在昇腾 NPU 机器编译 mmcv-full

#### 1. 安装 torch_npu
在编译 mmcv-full 前，需要安装 torch_npu，完整安装教程详见 [PyTorch 安装指南](https://gitee.com/ascend/pytorch/blob/master/docs/zh/PyTorch%E5%AE%89%E8%A3%85%E6%8C%87%E5%8D%97/PyTorch%E5%AE%89%E8%A3%85%E6%8C%87%E5%8D%97.md#pytorch%E5%AE%89%E8%A3%85%E6%8C%87%E5%8D%97)

- torch_npu 完整安装教程详见 [PyTorch安装指南](https://gitee.com/ascend/pytorch/blob/master/docs/zh/PyTorch%E5%AE%89%E8%A3%85%E6%8C%87%E5%8D%97/PyTorch%E5%AE%89%E8%A3%85%E6%8C%87%E5%8D%97.md#pytorch%E5%AE%89%E8%A3%85%E6%8C%87%E5%8D%97)
#### 选项 1: 使用 pip 安装 Ascend 编译版本的 mmcv-full

#### 2. 编译 MMCV NPU
- Ascend 编译版本的 mmcv-full 在 mmcv >= 1.7.0 时已经支持直接 pip 安装
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拉取 [MMCV 源码](https://github.com/open-mmlab/mmcv/tree/master) 进行编译安装
```bash
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/ascend/torch1.8.0/index.html
```

#### 选项 2: 使用 NPU 设备源码编译安装 mmcv-full

- 拉取 [MMCV 源码](https://github.com/open-mmlab/mmcv/tree/master)

```bash
git pull https://github.com/open-mmlab/mmcv/tree/master
```

编译：
- 编译

```bash
MMCV_WITH_OPS=1 MAX_JOBS=8 FORCE_NPU=1 python setup.py build_ext
```

安装：
- 安装

```bash
MMCV_WITH_OPS=1 FORCE_NPU=1 python setup.py develop
```

验证：
#### 验证

```python
import torch
import torch_npu
from mmcv.ops import softmax_focal_loss

# Init tensor to the NPU
x = torch.randn(3, 10).npu()
x.requires_grad = True
y = torch.tensor([1, 5, 3]).npu()
w = torch.ones(10).float().npu()
output = softmax_focal_loss(x, y, 2.0, 0.25, w, 'none')
```

使用说明：

```{note}
在 tensor 末尾加上 .npu() 就可以调用到 npu 算子
output = softmax_focal_loss(x, y, 2.0, 0.25, w, 'none')
print(output)
```
116 changes: 58 additions & 58 deletions docs/zh_cn/understand_mmcv/ops.md
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Expand Up @@ -2,61 +2,61 @@

MMCV 提供了检测、分割等任务中常用的算子

| Device | CPU | CUDA | MLU | MPS | NPU |
| ---------------------------- | --- | ---- | --- | --- | --- |
| ActiveRotatedFilter | √ | √ | | | |
| AssignScoreWithK | | √ | | | |
| BallQuery | | √ | | | |
| BBoxOverlaps | | √ | √ | √ | |
| BorderAlign | | √ | | | |
| BoxIouRotated | √ | √ | | | |
| BoxIouQuadri | √ | √ | | | |
| CARAFE | | √ | √ | | |
| ChamferDistance | | √ | | | |
| CrissCrossAttention | | √ | | | |
| ContourExpand | √ | | | | |
| ConvexIoU | | √ | | | |
| CornerPool | | √ | | | |
| Correlation | | √ | | | |
| Deformable Convolution v1/v2 | √ | √ | | | |
| Deformable RoIPool | | √ | √ | | |
| DiffIoURotated | | √ | | | |
| DynamicScatter | | √ | | | |
| FurthestPointSample | | √ | | | |
| FurthestPointSampleWithDist | | √ | | | |
| FusedBiasLeakyrelu | | √ | | | |
| GatherPoints | | √ | | | |
| GroupPoints | | √ | | | |
| Iou3d | | √ | √ | | |
| KNN | | √ | | | |
| MaskedConv | | √ | √ | | √ |
| MergeCells | | √ | | | |
| MinAreaPolygon | | √ | | | |
| ModulatedDeformConv2d | √ | √ | √ | | √ |
| MultiScaleDeformableAttn | | √ | √ | | |
| NMS | √ | √ | √ | | √ |
| NMSRotated | √ | √ | | | |
| NMSQuadri | √ | √ | | | |
| PixelGroup | √ | | | | |
| PointsInBoxes | √ | √ | | | |
| PointsInPolygons | | √ | | | |
| PSAMask | √ | √ | √ | | |
| RotatedFeatureAlign | √ | √ | | | |
| RoIPointPool3d | | √ | √ | | |
| RoIPool | | √ | √ | | |
| RoIAlignRotated | √ | √ | √ | | |
| RiRoIAlignRotated | | √ | | | |
| RoIAlign | √ | √ | √ | | |
| RoIAwarePool3d | | √ | √ | | |
| SAConv2d | | √ | | | |
| SigmoidFocalLoss | | √ | √ | | √ |
| SoftmaxFocalLoss | | √ | | | √ |
| SoftNMS | | √ | | | |
| Sparse Convolution | | √ | | | |
| Synchronized BatchNorm | | √ | | | |
| ThreeInterpolate | | √ | | | |
| ThreeNN | | √ | √ | | |
| TINShift | | √ | √ | | |
| UpFirDn2d | | √ | | | |
| Voxelization | √ | √ | | | |
| PrRoIPool | | √ | | | |
| Device | CPU | CUDA | MLU | MPS | Ascend |
| ---------------------------- | --- | ---- | --- | --- | ------ |
| ActiveRotatedFilter | √ | √ | | | |
| AssignScoreWithK | | √ | | | |
| BallQuery | | √ | | | |
| BBoxOverlaps | | √ | √ | √ | |
| BorderAlign | | √ | | | |
| BoxIouRotated | √ | √ | | | |
| BoxIouQuadri | √ | √ | | | |
| CARAFE | | √ | √ | | |
| ChamferDistance | | √ | | | |
| CrissCrossAttention | | √ | | | |
| ContourExpand | √ | | | | |
| ConvexIoU | | √ | | | |
| CornerPool | | √ | | | |
| Correlation | | √ | | | |
| Deformable Convolution v1/v2 | √ | √ | | | |
| Deformable RoIPool | | √ | √ | | |
| DiffIoURotated | | √ | | | |
| DynamicScatter | | √ | | | |
| FurthestPointSample | | √ | | | |
| FurthestPointSampleWithDist | | √ | | | |
| FusedBiasLeakyrelu | | √ | | | |
| GatherPoints | | √ | | | |
| GroupPoints | | √ | | | |
| Iou3d | | √ | √ | | |
| KNN | | √ | | | |
| MaskedConv | | √ | √ | | √ |
| MergeCells | | √ | | | |
| MinAreaPolygon | | √ | | | |
| ModulatedDeformConv2d | √ | √ | √ | | √ |
| MultiScaleDeformableAttn | | √ | √ | | |
| NMS | √ | √ | √ | | √ |
| NMSRotated | √ | √ | | | |
| NMSQuadri | √ | √ | | | |
| PixelGroup | √ | | | | |
| PointsInBoxes | √ | √ | | | |
| PointsInPolygons | | √ | | | |
| PSAMask | √ | √ | √ | | |
| RotatedFeatureAlign | √ | √ | | | |
| RoIPointPool3d | | √ | √ | | |
| RoIPool | | √ | √ | | |
| RoIAlignRotated | √ | √ | √ | | |
| RiRoIAlignRotated | | √ | | | |
| RoIAlign | √ | √ | √ | | |
| RoIAwarePool3d | | √ | √ | | |
| SAConv2d | | √ | | | |
| SigmoidFocalLoss | | √ | √ | | √ |
| SoftmaxFocalLoss | | √ | | | √ |
| SoftNMS | | √ | | | |
| Sparse Convolution | | √ | | | |
| Synchronized BatchNorm | | √ | | | |
| ThreeInterpolate | | √ | | | |
| ThreeNN | | √ | √ | | |
| TINShift | | √ | √ | | |
| UpFirDn2d | | √ | | | |
| Voxelization | √ | √ | | | |
| PrRoIPool | | √ | | | |