Merge branch 'dtk24.04.1' into 'main'

Dtk24.04.1

See merge request aibear/controlnet_pytorch!1

BasicSR/basicsr/ops/dcn/src/deform_conv_hip_kernel.hip

 // !!! This is a file automatically generated by hipify!!!
+#include <ATen/dtk_macros.h>
 #include "hip/hip_runtime.h"
 /*!
  ******************* BEGIN Caffe Copyright Notice and Disclaimer ****************

BasicSR/basicsr/ops/fused_act/src/fused_bias_act_kernel.hip

 // !!! This is a file automatically generated by hipify!!!
+#include <ATen/dtk_macros.h>
 // from https://github.com/rosinality/stylegan2-pytorch/blob/master/op/fused_bias_act_kernel.cu
 // Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
 //

BasicSR/basicsr/ops/upfirdn2d/src/upfirdn2d_kernel.hip

 // !!! This is a file automatically generated by hipify!!!
+#include <ATen/dtk_macros.h>
 // from https://github.com/rosinality/stylegan2-pytorch/blob/master/op/upfirdn2d_kernel.cu
 // Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
 //

Dockerfile

-FROM image.sourcefind.cn:5000/dcu/admin/base/pytorch:1.13.1-centos7.6-dtk-23.04-py38-latest
+FROM image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-ubuntu20.04-dtk24.04.1-py3.10
 

README.md

@@ -46,8 +46,8 @@ zero convolution：初始权重为零的卷积层；
 
 ### Docker (方法一)
 
-    docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:1.13.1-centos7.6-dtk-23.04-py38-latest
-    docker run --shm-size 10g --network=host --name=controlnet --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -v 项目地址(绝对路径):/home/ -it <your IMAGE ID> bash   
+    docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-ubuntu20.04-dtk24.04.1-py3.10
+    docker run --shm-size 10g --network=host --name=controlnet --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -v /opt/hyhal:/opt/hyhal:ro -v 项目地址(绝对路径):/home/ -it <your IMAGE ID> bash   
     pip install -r requirements.txt
     cd BasicSR 
     BASICSR_EXT=True python setup.py develop
@@ -57,7 +57,7 @@ zero convolution：初始权重为零的卷积层；
     # 需要在对应的目录下
     docker build -t <IMAGE_NAME>:<TAG> .
     # <your IMAGE ID>用以上拉取的docker的镜像ID替换
-    docker run -it --shm-size 10g --network=host --name=controlnet --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined <your IMAGE ID> bash
+    docker run --shm-size 10g --network=host --name=controlnet --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -v /opt/hyhal:/opt/hyhal:ro -v 项目地址(绝对路径):/home/ -it <your IMAGE ID> bash  
     pip install -r requirements.txt
     cd BasicSR
     BASICSR_EXT=True python setup.py develop
@@ -66,13 +66,10 @@ zero convolution：初始权重为零的卷积层；
 1、关于本项目DCU显卡所需的特殊深度学习库可从光合开发者社区下载安装：
 https://developer.hpccube.com/tool/
 
-    DTK驱动：dtk23.04
-    python：python3.8
-    torch:1.13.1
-    torchvision:0.14.1
-    torchaudio:0.13.1
-    deepspeed:0.9.2
-    apex:0.1
+    DTK驱动：dtk24.04.1
+    python：python3.10
+    torch:2.1.0
+    torchvision:0.16.0
 
 Tips：以上dtk驱动、python、torch等DCU相关工具版本需要严格一一对应
 

ldm/modules/attention.py

@@ -9,12 +9,13 @@ from typing import Optional, Any
 from ldm.modules.diffusionmodules.util import checkpoint
 
 
-try:
-    import xformers
-    import xformers.ops
-    XFORMERS_IS_AVAILBLE = True
-except:
-    XFORMERS_IS_AVAILBLE = False
+# try:
+#     import xformers
+#     import xformers.ops
+#     XFORMERS_IS_AVAILBLE = True
+# except:
+#     XFORMERS_IS_AVAILBLE = False
+XFORMERS_IS_AVAILBLE = False
 
 # CrossAttn precision handling
 import os

ldm/modules/diffusionmodules/model.py

@@ -8,13 +8,16 @@ from typing import Optional, Any
 
 from ldm.modules.attention import MemoryEfficientCrossAttention
 
-try:
-    import xformers
-    import xformers.ops
-    XFORMERS_IS_AVAILBLE = True
-except:
-    XFORMERS_IS_AVAILBLE = False
-    print("No module 'xformers'. Proceeding without it.")
+# try:
+#     import xformers
+#     import xformers.ops
+#     XFORMERS_IS_AVAILBLE = True
+# except:
+#     XFORMERS_IS_AVAILBLE = False
+#     print("No module 'xformers'. Proceeding without it.")
+
+XFORMERS_IS_AVAILBLE = False
+# print("No support 'xformers'. Proceeding without it.")
 
 
 def get_timestep_embedding(timesteps, embedding_dim):

requirements.txt

-gradio==3.16.2
+gradio==3.50.2
 albumentations==1.3.0
-opencv-contrib-python==4.4.0.46
+opencv-contrib-python
 imageio==2.9.0
 imageio-ffmpeg==0.4.2
 pytorch-lightning==1.5.0