[Featuure] Support Vacc Backend (open-mmlab#1679)

* [Enhancement] Support vacc backend

* update vacc wrapper

* vacc docs

* update vacc docs and remove some comments

* update vacc backend configs

* get vacc_det real output

* Fix vacc: pre-commit run

* fix pre-commit

* update vacc quantize

* update vacc docs.

* update vacc docs.

* [Fix]vacc wrapper and support set calib_num

* add vacc_seg model_type

* update vacc_det type

* update vacc_det type

* fix typo

* [Fix] some typo

* feats: update mmseg vacc sample

* feats: update mmseg vacc sample

* feats: update mmdet vacc sample

* feats: update vacc quant_dataset func.

* update vacc wrapper exit-code

* update vacc segmentor setting

* update vacc seg base_decode_head rewriter

* fix vacc wrapper outputs

Author: AndyLiu93

configs/_base_/backends/vacc.py

@@ -0,0 +1,17 @@
+backend_config = dict(
+    type='vacc',
+    common_config=dict(name='end2end'),
+    model_inputs=[
+        dict(
+            shape=dict(input=[1, 3, 224, 224]),
+            qconfig=dict(
+                dtype='fp16',
+                calibrate_mode='percentile',
+                weight_scale='max',
+                data_transmode=1,
+                per_channel=False,
+                cluster_mode=0,
+                skip_conv_layers=[],
+                calib_num=1000,
+            ))
+    ])

configs/mmcls/classification_vacc-fp16_static.py

@@ -0,0 +1,26 @@
+_base_ = ['./classification_static.py', '../_base_/backends/vacc.py']
+
+backend_config = dict(
+    common_config=dict(
+        vdsp_params_info=dict(
+            vdsp_op_type=300,
+            iimage_format=5000,
+            iimage_width=256,
+            iimage_height=256,
+            iimage_width_pitch=256,
+            iimage_height_pitch=256,
+            short_edge_threshold=256,
+            resize_type=1,
+            color_cvt_code=2,
+            color_space=0,
+            crop_size=224,
+            meanr=22459,
+            meang=22340,
+            meanb=22136,
+            stdr=21325,
+            stdg=21284,
+            stdb=21292,
+            norma_type=3)),
+    model_inputs=[
+        dict(shape=dict(input=[1, 3, 224, 224]), qconfig=dict(dtype='fp16'))
+    ])

configs/mmcls/classification_vacc-int8_static.py

@@ -0,0 +1,5 @@
+_base_ = ['./classification_static.py', '../_base_/backends/vacc.py']
+
+backend_config = dict(model_inputs=[
+    dict(shape=dict(input=[1, 3, 224, 224]), qconfig=dict(dtype='int8'))
+])

configs/mmdet/detection/detection_vacc-fp16_static_416x416.py

@@ -0,0 +1,43 @@
+_base_ = ['../_base_/base_static.py', '../../_base_/backends/vacc.py']
+
+onnx_config = dict(input_shape=[416, 416])
+
+backend_config = dict(
+    common_config=dict(
+        vdsp_params_info=dict(
+            vdsp_op_type=303,
+            iimage_format=5000,
+            iimage_width=640,
+            iimage_height=640,
+            oimage_width=416,
+            oimage_height=416,
+            iimage_width_pitch=640,
+            iimage_height_pitch=640,
+            resize_type=1,
+            color_cvt_code=2,
+            color_space=0,
+            padding_value_r=114,
+            padding_value_g=114,
+            padding_value_b=114,
+            edge_padding_type=0,
+            meanr=0,
+            meang=0,
+            meanb=0,
+            stdr=23544,
+            stdg=23544,
+            stdb=23544,
+            norma_type=3)),
+    model_inputs=[
+        dict(shape=dict(input=[1, 3, 416, 416]), qconfig=dict(dtype='fp16'))
+    ])
+
+partition_config = dict(
+    type='vacc_det',
+    apply_marks=True,
+    partition_cfg=[
+        dict(
+            save_file='model.onnx',
+            start=['detector_forward:input'],
+            end=['yolo_head:input'],
+            output_names=[f'pred_maps.{i}' for i in range(3)])
+    ])

configs/mmdet/detection/detection_vacc-int8_static_416x416.py

@@ -0,0 +1,18 @@
+_base_ = ['../_base_/base_static.py', '../../_base_/backends/vacc.py']
+
+onnx_config = dict(input_shape=[416, 416])
+
+backend_config = dict(model_inputs=[
+    dict(shape=dict(input=[1, 3, 416, 416]), qconfig=dict(dtype='int8'))
+])
+
+partition_config = dict(
+    type='vacc_det',
+    apply_marks=True,
+    partition_cfg=[
+        dict(
+            save_file='model.onnx',
+            start=['detector_forward:input'],
+            end=['yolo_head:input'],
+            output_names=[f'pred_maps.{i}' for i in range(3)])
+    ])

configs/mmseg/segmentation_vacc-fp16_static_512x512.py

@@ -0,0 +1,41 @@
+_base_ = ['./segmentation_static.py', '../_base_/backends/vacc.py']
+
+onnx_config = dict(input_shape=[512, 512])
+
+backend_config = dict(
+    common_config=dict(
+        vdsp_params_info=dict(
+            vdsp_op_type=301,
+            iimage_format=5000,
+            iimage_width=512,
+            iimage_height=512,
+            oimage_width=512,
+            oimage_height=512,
+            iimage_width_pitch=512,
+            iimage_height_pitch=512,
+            resize_type=1,
+            color_cvt_code=2,
+            color_space=0,
+            meanr=22459,
+            meang=22340,
+            meanb=22136,
+            stdr=21325,
+            stdg=21284,
+            stdb=21292,
+            norma_type=3)),
+    model_inputs=[dict(shape=dict(input=[1, 3, 512, 512]))])
+
+codebase_config = dict(model_type='vacc_seg')
+
+partition_config = dict(
+    type='vacc_seg',
+    apply_marks=True,
+    partition_cfg=[
+        dict(
+            save_file='model.onnx',
+            start=['segmentor_forward:output'],
+            # 'decode_head' will skip `ArgMax`
+            # 'seg_maps' will skip `Resize` and `ArgMax`
+            end=['decode_head:input'],
+            output_names=['feat'])
+    ])

configs/mmseg/segmentation_vacc-int8_static_512x512.py

@@ -0,0 +1,20 @@
+_base_ = ['./segmentation_static.py', '../_base_/backends/vacc.py']
+
+onnx_config = dict(input_shape=[512, 512])
+
+backend_config = dict(model_inputs=[
+    dict(shape=dict(input=[1, 3, 512, 512]), qconfig=dict(dtype='int8'))
+])
+
+partition_config = dict(
+    type='vacc_seg',
+    apply_marks=True,
+    partition_cfg=[
+        dict(
+            save_file='model.onnx',
+            start=['segmentor_forward:output'],
+            # 'decode_head' will skip `ArgMax`
+            # 'seg_maps' will skip `Resize` and `ArgMax`
+            end=['decode_head:input'],
+            output_names=['feat'])
+    ])

docs/en/05-supported-backends/vacc.md

@@ -0,0 +1,95 @@
+# VACC Backend
+
+- cmake 3.10.0+
+- gcc/g++ 7.5.0
+- llvm 9.0.1
+- ubuntu 18.04
+
+## PCIE
+
+### 1.package
+
+- dkms (>=1.95)
+- linux-headers
+- dpkg (Ubuntu)
+- rpm  (CentOS)
+- python2
+- python3
+
+Check if there is a vacc card：`lspci -d:0100`
+
+1. Requirements
+
+   ```bash
+   sudo apt-get install dkms dpkg python2 python3
+   ```
+
+2. install driver
+
+   ```bash
+   sudo dpkg -i vastai-pci_xx.xx.xx.xx_xx.deb
+   ```
+
+3. Verify installation
+
+   ```bash
+   dpkg --status vastai-pci-xxx
+
+   #output
+   Package: vastai-pci-dkms
+   Status: install ok installed
+   ……
+   Version: xx.xx.xx.xx
+   Provides: vastai-pci-modules (= xx.xx.xx.xx)
+   Depends: dkms (>= 1.95)
+   Description: vastai-pci driver in DKMS format.
+
+   lsmod | grep vastai_pci
+
+   #output
+   vastai_pci        xxx  x
+   ```
+
+4. Upgrade driver
+
+   ```bash
+   sudo dpkg -i vastai-pci_dkms_xx.xx.xx.xx_xx.deb
+   ```
+
+5. Uninstall driver
+
+   ```bash
+   sudo dpkg -r vastai-pci_dkms_xx.xx.xx.xx_xx
+   ```
+
+### 2.reboot pcie
+
+```bash
+sudo chmod 666 /dev/kchar:0 && sudo echo reboot > /dev/kchar:0
+```
+
+## SDK
+
+### step.1
+
+```bash
+pip install torch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0
+pip install onnx==1.10.0 tqdm==4.64.1
+pip install h5py==3.8.0
+pip install decorator==5.1.1 scipy==1.7.3
+```
+
+### step.2
+
+```bash
+sudo vi ~/.bashrc
+
+export VASTSTREAM_PIPELINE=true
+export VACC_IRTEXT_ENABLE=1
+export TVM_HOME="/opt/vastai/vaststream/tvm"
+export VASTSTREAM_HOME="/opt/vastai/vaststream/vacl"
+export LD_LIBRARY_PATH=$TVM_HOME/lib:$VASTSTREAM_HOME/lib
+export PYTHONPATH=$TVM_HOME/python:$TVM_HOME/vacc/python:$TVM_HOME/topi/python:${PYTHONPATH}:$VASTSTREAM_HOME/python
+
+source ~/.bashrc
+```

docs/zh_cn/05-supported-backends/vacc.md

@@ -0,0 +1,97 @@
+# VACC Backend
+
+- cmake 3.10.0+
+- gcc/g++ 7.5.0
+- llvm 9.0.1
+- ubuntu 18.04
+
+## PCIE
+
+### 1.package
+
+- dkms (>=1.95)
+- linux-headers
+- dpkg (Ubuntu)
+- rpm  (CentOS)
+- python2
+- python3
+
+查看是否有瀚博推理卡：`lspci -d:0100`
+
+1. 环境准备
+
+   ```bash
+   sudo apt-get install dkms dpkg python2 python3
+   ```
+
+2. driver安装
+
+   ```bash
+   sudo dpkg -i vastai-pci_xx.xx.xx.xx_xx.deb
+   ```
+
+3. 查看安装
+
+   ```bash
+   # 1.查看deb包是否安装成功
+   dpkg --status vastai-pci-xxx
+
+   #output
+   Package: vastai-pci-dkms
+   Status: install ok installed
+   ……
+   Version: xx.xx.xx.xx
+   Provides: vastai-pci-modules (= xx.xx.xx.xx)
+   Depends: dkms (>= 1.95)
+   Description: vastai-pci driver in DKMS format.
+
+   # 2.查看驱动是否已加载到内核
+   lsmod | grep vastai_pci
+
+   #output
+   vastai_pci        xxx  x
+   ```
+
+4. 升级驱动
+
+   ```bash
+   sudo dpkg -i vastai-pci_dkms_xx.xx.xx.xx_xx.deb
+   ```
+
+5. 卸载驱动
+
+   ```bash
+   sudo dpkg -r vastai-pci_dkms_xx.xx.xx.xx_xx
+   ```
+
+### 2.reboot pcie
+
+```bash
+sudo chmod 666 /dev/kchar:0 && sudo echo reboot > /dev/kchar:0
+```
+
+## SDK
+
+### step.1
+
+```bash
+pip install torch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0
+pip install onnx==1.10.0 tqdm==4.64.1
+pip install h5py==3.8.0
+pip install decorator==5.1.1 scipy==1.7.3
+```
+
+### step.2
+
+```bash
+sudo vi ~/.bashrc
+
+export VASTSTREAM_PIPELINE=true
+export VACC_IRTEXT_ENABLE=1
+export TVM_HOME="/opt/vastai/vaststream/tvm"
+export VASTSTREAM_HOME="/opt/vastai/vaststream/vacl"
+export LD_LIBRARY_PATH=$TVM_HOME/lib:$VASTSTREAM_HOME/lib
+export PYTHONPATH=$TVM_HOME/python:$TVM_HOME/vacc/python:$TVM_HOME/topi/python:${PYTHONPATH}:$VASTSTREAM_HOME/python
+
+source ~/.bashrc
+```

mmdeploy/apis/vacc/__init__.py

@@ -0,0 +1,13 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+from mmdeploy.backend.vacc import is_available
+from ..core import PIPELINE_MANAGER
+
+__all__ = ['is_available']
+
+if is_available():
+    try:
+        from mmdeploy.backend.vacc import from_onnx as _from_onnx
+        from_onnx = PIPELINE_MANAGER.register_pipeline()(_from_onnx)
+        __all__ += ['from_onnx']
+    except Exception:
+        pass