From 121655a83ebf4a4de8a6c45a39190667161b1f78 Mon Sep 17 00:00:00 2001
From: jshilong <zhangshilong@pjlab.org.cn>
Date: Fri, 1 Apr 2022 15:02:51 +0800
Subject: [PATCH 1/3] add quick install command

---
 docs/en/getting_started.md    | 19 +++++++++++++++++++
 docs/zh_cn/getting_started.md | 18 ++++++++++++++++++
 2 files changed, 37 insertions(+)

diff --git a/docs/en/getting_started.md b/docs/en/getting_started.md
index a42f3a29e..fef9fde9c 100644
--- a/docs/en/getting_started.md
+++ b/docs/en/getting_started.md
@@ -37,6 +37,25 @@ The required versions of MMCV, MMDetection and MMSegmentation for different vers
 
 ## Install MMDetection3D
 
+### Quick installation instructions script
+
+Assuming that you already have CUDA 11.0 installed, here is a full script for quick installation of MMDetection3D with conda.
+Otherwise, you should refer to the step-by-step installation instructions in the next section.
+
+```shell
+conda create -n open-mmlab python=3.7 pytorch=1.9 cudatoolkit=11.0 torchvision -c pytorch -y
+conda activate open-mmlab
+pip3 install openmim
+mim install mmcv-full
+mim install mmdet
+mim install mmsegmentation
+git clone https://github.com/open-mmlab/mmdetection3d.git
+cd mmdetection3d
+pip3 install -e .
+```
+
+### Step-by-step installation instructions
+
 **a. Create a conda virtual environment and activate it.**
 
 ```shell
diff --git a/docs/zh_cn/getting_started.md b/docs/zh_cn/getting_started.md
index 5784e448a..c16db0f72 100644
--- a/docs/zh_cn/getting_started.md
+++ b/docs/zh_cn/getting_started.md
@@ -34,6 +34,24 @@
 
 ## MMdetection3D 安装流程
 
+### 快速安装脚本
+
+如果你已经成功安装 CUDA 11.0，那么你可以使用这个快速安装命令进行 MMDetection3D 的安装。 否则，则参考下一小节的详细安装流程。
+
+```shell
+conda create -n open-mmlab python=3.7 pytorch=1.9 cudatoolkit=11.0 torchvision -c pytorch -y
+conda activate open-mmlab
+pip3 install openmim
+mim install mmcv-full
+mim install mmdet
+mim install mmsegmentation
+git clone https://github.com/open-mmlab/mmdetection3d.git
+cd mmdetection3d
+pip3 install -e .
+```
+
+### 详细安装流程
+
 **a. 使用 conda 新建虚拟环境，并进入该虚拟环境。**
 
 ```shell

From 16f86605d90d65dd278acdd7d5dde50d538cffc8 Mon Sep 17 00:00:00 2001
From: zhangshilong <2392587229zsl@gmail.com>
Date: Wed, 27 Apr 2022 11:45:56 +0800
Subject: [PATCH 2/3] fix SyncBatchNorm

---
 mmdet3d/ops/norm.py | 35 ++++++++++++++++++++++++++++++++---
 1 file changed, 32 insertions(+), 3 deletions(-)

diff --git a/mmdet3d/ops/norm.py b/mmdet3d/ops/norm.py
index 52a1363d2..5f4162b9c 100644
--- a/mmdet3d/ops/norm.py
+++ b/mmdet3d/ops/norm.py
@@ -53,11 +53,27 @@ def __init__(self, *args, **kwargs):
     # TODO: make mmcv fp16 utils handle customized norm layers
     @force_fp32(out_fp16=True)
     def forward(self, input):
+        """
+        Args:
+            input (tensor): Has shape (N, C) or (N, C, L), where N is
+                the batch size, C is the number of features or
+                channels, and L is the sequence length
+
+        Returns:
+            tensor: Has shape (N, C) or (N, C, L), has same shape
+            as input.
+        """
         assert input.dtype == torch.float32, \
             f'input should be in float32 type, got {input.dtype}'
-        if dist.get_world_size() == 1 or not self.training:
+        using_dist = dist.is_available() and dist.is_initialized()
+        if (not using_dist) or dist.get_world_size() == 1 \
+                or not self.training:
             return super().forward(input)
         assert input.shape[0] > 0, 'SyncBN does not support empty inputs'
+        is_two_dim = input.dim() == 2
+        if is_two_dim:
+            input.unsqueeze_(2)
+
         C = input.shape[1]
         mean = torch.mean(input, dim=[0, 2])
         meansqr = torch.mean(input * input, dim=[0, 2])
@@ -76,7 +92,10 @@ def forward(self, input):
         bias = self.bias - mean * scale
         scale = scale.reshape(1, -1, 1)
         bias = bias.reshape(1, -1, 1)
-        return input * scale + bias
+        output = input * scale + bias
+        if is_two_dim:
+            output = output.squeeze(2)
+        return output
 
 
 @NORM_LAYERS.register_module('naiveSyncBN2d')
@@ -107,9 +126,19 @@ def __init__(self, *args, **kwargs):
     # TODO: make mmcv fp16 utils handle customized norm layers
     @force_fp32(out_fp16=True)
     def forward(self, input):
+        """
+        Args:
+            Input (tensor): Feature has shape (N, C, H, W).
+
+        Returns:
+            tensor: Has shape (N, C, H, W), same shape as input.
+        """
         assert input.dtype == torch.float32, \
             f'input should be in float32 type, got {input.dtype}'
-        if dist.get_world_size() == 1 or not self.training:
+        using_dist = dist.is_available() and dist.is_initialized()
+        if (not using_dist) or \
+                dist.get_world_size() == 1 or \
+                not self.training:
             return super().forward(input)
 
         assert input.shape[0] > 0, 'SyncBN does not support empty inputs'

From c8c0b5c7f6030d11ea0f4b1fa32adc2efeef4ac3 Mon Sep 17 00:00:00 2001
From: zhangshilong <2392587229zsl@gmail.com>
Date: Thu, 28 Apr 2022 14:31:59 +0800
Subject: [PATCH 3/3] fix SyncBatchNorm

---
 mmdet3d/ops/norm.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/mmdet3d/ops/norm.py b/mmdet3d/ops/norm.py
index 5f4162b9c..98ec7f117 100644
--- a/mmdet3d/ops/norm.py
+++ b/mmdet3d/ops/norm.py
@@ -72,7 +72,7 @@ def forward(self, input):
         assert input.shape[0] > 0, 'SyncBN does not support empty inputs'
         is_two_dim = input.dim() == 2
         if is_two_dim:
-            input.unsqueeze_(2)
+            input = input.unsqueeze(2)
 
         C = input.shape[1]
         mean = torch.mean(input, dim=[0, 2])