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README.md

 # <div align="center"><strong>MMCV</strong></div>
 ## 简介
-MMCV是计算机视觉研究的基础库，主要提供以下功能：图像处理、图像和标注结果可视化、图像转换、多种CNN网络结构、高质量实现的常见CUDA算子。
+MMCV是计算机视觉研究的基础库，主要提供以下功能：图像处理、图像和标注结果可视化、图像转换、多种CNN网络结构、高质量实现的常见CUDA算子。DAS软件栈中的MMCV版本，不仅保证了组件核心功能在DCU加速卡的可用性,还针对DCU特有的硬件架构进行了深度定制优化。这使得开发者能够以极低的成本，轻松实现应用程序在DCU加速卡上的快速迁移和性能提升。
 
 ## 安装
-组件支持
-+ Python 3.7、3.8、3.9
+组件支持组合
+
+   | PyTorch版本 | fastpt版本  |MMCV版本      | DTK版本                  | Python版本       | 推荐编译方式 |
+   | ----------- | ----------- | ----------- | ------------------------ | -----------------| ------------ |
+   | 2.5.1       | 2.1.0       |2.0.1        | >= 25.04                 | 3.8、3.10、3.11  | fastpt不转码 |
+   | 2.4.1       | 2.0.1       |2.0.1        | >= 25.04                 | 3.8、3.10、3.11  | fastpt不转码 |
+   | 其他        | 其他        | 其他        | 其他                     | 3.8、3.10、3.11  | hip转码      |
+
++ pytorch版本大于2.4.1 && dtk版本大于25.04 推荐使用fastpt不转码编译。
 
 ### 1、使用pip方式安装
-mmcv whl包下载目录：[https://cancon.hpccube.com:65024/4/main/mmcv/dtk24.04](https://cancon.hpccube.com:65024/4/main/mmcv/dtk24.04)，选择对应的pytorch版本和python版本下载对应mmcv的whl包
+mmcv whl包下载目录：[光和开发者社区](https://download.sourcefind.cn:65024/4/main/mmcv)，选择对应的pytorch版本和python版本下载对应mmcv的whl包
 ```shell
-pip install mmcv* (下载的mmcv的whl包)
+pip install torch* (下载torch的whl包)
+pip install fastpt* --no-deps (下载fastpt的whl包)
+source  /usr/local/bin/fastpt -E
+pip install mmcv* (下载的mmcv-fastpt的whl包)
 ```
 ### 2、使用源码编译方式安装
 
 #### 编译环境准备
-提供2种环境准备方式：
+提供基于fastpt不转码编译：
 
-1. 基于光源pytorch基础镜像环境：镜像下载地址：[https://sourcefind.cn/#/image/dcu/pytorch](https://sourcefind.cn/#/image/dcu/pytorch)，根据pytorch、python、dtk及系统下载对应的镜像版本。
+1. 基于光源pytorch基础镜像环境：镜像下载地址：[光合开发者社区](https://sourcefind.cn/#/image/dcu/pytorch)，根据pytorch、python、dtk及系统下载对应的镜像版本。
 
-2. 基于现有python环境：安装pytorch，pytorch whl包下载目录：[https://cancon.hpccube.com:65024/4/main/pytorch/dtk24.04](https://cancon.hpccube.com:65024/4/main/pytorch/dtk24.04)，根据python、dtk版本,下载对应pytorch的whl包。安装命令如下：
+2. 基于现有python环境：安装pytorch，fastpt whl包下载目录：[光合开发者社区](https://sourcefind.cn/#/image/dcu/pytorch)，根据python、dtk版本,下载对应pytorch的whl包。安装命令如下：
 ```shell
-pip install torch* (下载的torch的whl包)
+pip install torch* (下载torch的whl包)
+pip install fastpt* --no-deps (下载fastpt的whl包, 安装顺序，先安装torch，后安装fastpt)
+pip install setuptools==59.5.0 wheel
 ```
 
 #### 源码编译安装
 - 代码下载
 ```shell
-git http://developer.hpccube.com/codes/OpenDAS/mmcv.git  # 根据编译需要切换分支
+git clone http://developer.sourcefind.cn/codes/OpenDAS/mmcv.git # 根据编译需要切换分支
 ```
 - 提供2种源码编译方式（进入mmcv目录）：
 ```
-1. 编译whl包并安装
-MMCV_WITH_OPS=1 ROCM_HOME=${ROCM_PATH} python3 setup.py -v bdist_wheel
+1. 设置不转码编译环境变量
+export FORCE_CUDA=1
+source /usr/local/bin/fastpt -C
+
+2. 编译whl包并安装
+MMCV_WITH_OPS=1 python3 setup.py -v bdist_wheel
 pip install dist/mmcv*
 
-2. 源码编译安装
-MMCV_WITH_OPS=1 ROCM_HOME=${ROCM_PATH} python3 setup.py install
+3. 源码编译安装
+MMCV_WITH_OPS=1 python3 setup.py install
 ```
 #### 注意事项
 + 若使用pip install下载安装过慢，可添加pypi清华源：-i https://pypi.tuna.tsinghua.edu.cn/simple/
 + ROCM_PATH为dtk的路径，默认为/opt/dtk
++ 在pytorch2.5.1环境下编译需要支持c++17语法，打开setup.py文件，把文件中的 -std=c++14 修改为 -std=c++17
 
 ## 验证
-- python -c "import mmcv; mmcv.\_\_version__"，版本号与官方版本同步，查询该软件的版本号，例如2.0.0；
+- python -c "import mmcv; mmcv.\_\_version__"，版本号与官方版本同步，查询该软件的版本号，例如2.0.1；
 
 ## Known Issue
 - 无

get_version.py

+import os
+import re
+import subprocess
+from pathlib import Path
+
+import torch
+
+ROOT_DIR = Path(__file__).parent.resolve()
+
+def _run_cmd(cmd, shell=False):
+    try:
+        return subprocess.check_output(cmd, cwd=ROOT_DIR, stderr=subprocess.DEVNULL, shell=shell).decode("ascii").strip()
+    except Exception:
+        return None
+
+def _get_version():
+    if os.path.exists(ROOT_DIR / "mmcv/version.py"):
+        with open(ROOT_DIR / "mmcv/version.py", "r") as f:
+            content = f.read().strip()
+        version_match = re.search("__version__\s*=\s*['\"]([^'\"]+)['\"]", content)
+        if version_match:
+            print(f"version_match.group(1) = {version_match.group(1)}")
+            print(f"version_match.group(0) = {version_match.group(0)}")
+            version = version_match.group(1)
+    else:
+        version = '2.2.0'
+    if os.getenv("BUILD_VERSION"):
+        version = os.getenv("BUILD_VERSION")
+    return version
+
+def _update_hcu_version(version, das_version, sha, abi, dtk, torch_version, branch):
+    """
+    修改 __hcu_version__ 的值，不改变其他内容。
+    
+    :param file_path: 要修改的 .py 文件路径
+    :param new_value: 新的版本号字符串，比如 '2.2.0+das.opt1.dtk25041'
+    """
+    sha = "Unknown" if sha is None else sha
+    hcu_version = f"{das_version}"
+    file_path = ROOT_DIR / "mmcv" / "version.py"
+
+    # 读取整个文件内容
+    with open(file_path, "r", encoding="utf-8") as f:
+        content = f.read()
+
+    # 正则匹配 __hcu_version__ 行，并替换引号内的值
+    pattern = r"(__hcu_version__\s*=\s*)['\"]([^'\"]*)['\"]"
+    replacement = rf"\g<1>'{hcu_version}'"
+
+    # 执行替换
+    updated_content = re.sub(pattern, replacement, content)
+
+    # 写回文件
+    with open(file_path, "w", encoding="utf-8") as f:
+        f.write(updated_content)
+
+    return hcu_version
+
+def get_origin_version():
+    version_file = ROOT_DIR / 'mmcv/version.py'
+    with open(version_file, encoding='utf-8') as f:
+        exec(compile(f.read(), version_file, 'exec'))
+    return locals()['__version__']
+
+def _make_version_file(version, das_version, sha, abi, dtk, torch_version, branch):
+    sha = "Unknown" if sha is None else sha
+    # torch_version = '.'.join(torch_version.split('.')[:2])
+    # hcu_version = f"{das_version}.git{sha}.abi{abi}.dtk{dtk}.torch{torch_version}"
+    hcu_version = f"{das_version}"
+    version_path = ROOT_DIR / "mmcv" / "version.py"
+    with open(version_path, "a", encoding="utf-8") as f:
+        #f.write(f"version = '{version}'\n")
+        #f.write(f"git_hash = '{sha}'\n")
+        #f.write(f"git_branch = '{branch}'\n")
+        #f.write(f"abi = 'abi{abi}'\n")
+        #f.write(f"dtk = '{dtk}'\n")
+        #f.write(f"torch_version = '{torch_version}'\n")
+        f.write(f"__hcu_version__ = '{hcu_version}'\n")
+    return hcu_version
+
+def _get_pytorch_version():
+    if "PYTORCH_VERSION" in os.environ:
+        return f"{os.environ['PYTORCH_VERSION']}"
+    return torch.__version__
+
+def get_version():
+    ROCM_HOME = os.getenv("ROCM_PATH")
+    print("ROCM_HOME = {ROCM_HOME}")
+    if not ROCM_HOME:
+        return get_origin_version()
+    sha = _run_cmd(["git", "rev-parse", "HEAD"])
+    sha = sha[:7]
+    branch = _run_cmd(["git", "rev-parse", "--abbrev-ref", "HEAD"])
+    tag = _run_cmd(["git", "describe", "--tags", "--exact-match", "@"])
+    das_tag = _run_cmd(["git", "describe", "--abbrev=0"])
+    print("-- Git branch:", branch)
+    print("-- Git SHA:", sha)
+    print("-- Git tag:", tag)
+    torch_version = _get_pytorch_version()
+    print("-- PyTorch:", torch_version)
+    version = _get_version()
+    print("-- Building version", version)
+    # das_version = tag
+    das_version = version+"+das.opt1"
+    print("-- Building das_version", das_version)
+    abi = _run_cmd(["echo '#include <string>' | gcc -x c++ -E -dM - | fgrep _GLIBCXX_USE_CXX11_ABI | awk '{print $3}'"], shell=True)
+    print("-- _GLIBCXX_USE_CXX11_ABI:", abi)
+    dtk = _run_cmd(["cat", os.path.join(ROCM_HOME, '.info/rocm_version')])
+    dtk = ''.join(dtk.split('.'))
+    print("-- DTK:", dtk)
+    das_version += ".dtk" +dtk
+
+    #return _make_version_file(version, das_version, sha, abi, dtk, torch_version, branch)
+    return _update_hcu_version(version, das_version, sha, abi, dtk, torch_version, branch)

mmcv/ops/csrc/common/cuda/bbox_overlaps_cuda_kernel.cuh

@@ -88,7 +88,7 @@ __global__ void bbox_overlaps_cuda_kernel(const T* bbox1, const T* bbox2,
   }
 }
 
-#if __CUDA_ARCH__ >= 530
+#if __CUDACC__ >= 530
 __device__ __forceinline__ __half __half_area(const __half x1, const __half y1,
                                               const __half x2, const __half y2,
                                               const __half offset) {
@@ -142,6 +142,6 @@ __device__ void bbox_overlaps_cuda_kernel_half(
     ious[index] = __hdiv(interS, baseS);
   }
 }
-#endif  // __CUDA_ARCH__ >= 530
+#endif  // __CUDACC__ >= 530
 
 #endif  // BBOX_OVERLAPS_CUDA_KERNEL_CUH

mmcv/ops/csrc/common/cuda/parrots_cudawarpfunction.cuh

@@ -15,13 +15,13 @@
 #ifdef PARROTS_USE_HALF
 #include <cuda_fp16.h>
 #endif
-#ifdef __CUDA_ARCH__
+#ifdef __CUDACC__
 #define CUDA_INTRINSIC_FUNC(Expr) Expr
 #else
 #define CUDA_INTRINSIC_FUNC(Expr)
 #endif
 
-#if !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 300
+#if !defined(__CUDACC__) || __CUDACC__ >= 300
 
 #ifdef PARROTS_USE_HALF
 
@@ -104,6 +104,6 @@ __device__ inline T __shfl_xor_sync(unsigned mask, T var, int laneMask,
 
 #endif  // CUDA_VERSION < 9000
 
-#endif  // !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 300
+#endif  // !defined(__CUDACC__) || __CUDACC__ >= 300
 
 #endif  // INCLUDE_PARROTS_DARRAY_CUDAWARPFUNCTION_CUH_

mmcv/ops/csrc/common/cuda/scatter_points_cuda_kernel.cuh

@@ -42,9 +42,9 @@ __device__ __forceinline__ static void reduceAdd(double *address, double val) {
   atomicAdd(address, val);
 }
 #else
-#ifdef __CUDA_ARCH__
+#ifdef __CUDACC__
 __device__ __forceinline__ static void reduceAdd(float *address, float val) {
-#if (__CUDA_ARCH__ < 200)
+#if (__CUDACC__ < 200)
 #ifdef _MSC_VER
 #pragma message( \
     "compute capability lower than 2.x. fall back to use CAS version of atomicAdd for float32")
@@ -65,7 +65,7 @@ __device__ __forceinline__ static void reduceAdd(float *address, float val) {
 }
 
 __device__ __forceinline__ static void reduceAdd(double *address, double val) {
-#if (__CUDA_ARCH__ < 600)
+#if (__CUDACC__ < 600)
 #ifdef _MSC_VER
 #pragma message( \
     "compute capability lower than 6.x. fall back to use CAS version of atomicAdd for float64")
@@ -85,7 +85,7 @@ __device__ __forceinline__ static void reduceAdd(double *address, double val) {
   atomicAdd(address, val);
 #endif
 }
-#endif  // __CUDA_ARCH__
+#endif  // __CUDACC__
 #endif  // MMCV_WITH_HIP
 
 template <typename T>

mmcv/ops/csrc/common/parrots_cuda_helper.hpp

@@ -60,7 +60,7 @@ using phalf = float16;
   }()
 
 /** atomicAdd **/
-#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ < 600
+#if defined(__CUDACC__) && __CUDACC__ < 600
 
 static __inline__ __device__ double atomicAdd(double* address, double val) {
   unsigned long long int* address_as_ull = (unsigned long long int*)address;

mmcv/ops/csrc/common/utils/spconv/tensorview/tensorview.h

@@ -561,7 +561,7 @@ struct TensorView {
   }
   TV_HOST_DEVICE_INLINE scalar_t &operator()() {
 #if defined TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mPtr != nullptr,
                       "you want get value but the view is empty.%s", "\n");
     TV_DEVICE_REQUIRE(mShape.ndim() == 0,
@@ -577,7 +577,7 @@ struct TensorView {
   }
   TV_HOST_DEVICE_INLINE const scalar_t &operator()() const {
 #if defined TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mPtr != nullptr,
                       "you want get value but the view is empty.%s", "\n");
     TV_DEVICE_REQUIRE(mShape.ndim() == 0,
@@ -595,7 +595,7 @@ struct TensorView {
   template <class T1>
   TV_HOST_DEVICE_INLINE scalar_t &operator()(T1 i1) {
 #if defined TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 1,
                       "you provide 1 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -612,7 +612,7 @@ struct TensorView {
   template <class T1, class T2>
   TV_HOST_DEVICE_INLINE scalar_t &operator()(T1 i1, T2 i2) {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 2,
                       "you provide 2 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -635,7 +635,7 @@ struct TensorView {
   template <class T1, class T2, class T3>
   TV_HOST_DEVICE_INLINE scalar_t &operator()(T1 i1, T2 i2, T3 i3) {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 3,
                       "you provide 3 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -663,7 +663,7 @@ struct TensorView {
   template <class T1, class T2, class T3, class T4>
   TV_HOST_DEVICE_INLINE scalar_t &operator()(T1 i1, T2 i2, T3 i3, T4 i4) {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 4,
                       "you provide 4 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -697,7 +697,7 @@ struct TensorView {
   template <class T1>
   TV_HOST_DEVICE_INLINE const scalar_t &operator()(T1 i1) const {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 1,
                       "you provide 1 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -715,7 +715,7 @@ struct TensorView {
   template <class T1, class T2>
   TV_HOST_DEVICE_INLINE const scalar_t &operator()(T1 i1, T2 i2) const {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 2,
                       "you provide 2 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -739,7 +739,7 @@ struct TensorView {
   template <class T1, class T2, class T3>
   TV_HOST_DEVICE_INLINE const scalar_t &operator()(T1 i1, T2 i2, T3 i3) const {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 3,
                       "you provide 3 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -768,7 +768,7 @@ struct TensorView {
   TV_HOST_DEVICE_INLINE const scalar_t &operator()(T1 i1, T2 i2, T3 i3,
                                                    T4 i4) const {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(mShape.ndim() == 4,
                       "you provide 4 indexes, but dim is %ld\n", mShape.ndim());
     TV_DEVICE_REQUIRE(i1 >= 0 && i1 < mShape[0],
@@ -801,7 +801,7 @@ struct TensorView {
 
   TV_HOST_DEVICE_INLINE scalar_t &operator[](int idx) {
 #ifdef TV_DEBUG
-#if defined(__CUDA_ARCH__)
+#if defined(__CUDACC__)
     TV_DEVICE_REQUIRE(idx >= 0 && idx < size(),
                       "index(%d) out-of-range: [0, %ld)\n", int(idx), size());
 #else

mmcv/ops/csrc/pytorch/cuda/bbox_overlaps_cuda.cu

@@ -4,7 +4,7 @@
 
 // Disable fp16 on ROCm device
 #ifndef MMCV_WITH_HIP
-#if __CUDA_ARCH__ >= 530
+#if __CUDACC__ >= 530
 template <>
 __global__ void bbox_overlaps_cuda_kernel<at::Half>(
     const at::Half* bbox1, const at::Half* bbox2, at::Half* ious,
@@ -16,7 +16,7 @@ __global__ void bbox_overlaps_cuda_kernel<at::Half>(
                                  num_bbox2, mode, aligned, offset);
 }
 
-#endif  // __CUDA_ARCH__ >= 530
+#endif  // __CUDACC__ >= 530
 #endif  // MMCV_WITH_HIP
 
 void BBoxOverlapsCUDAKernelLauncher(const Tensor bboxes1, const Tensor bboxes2,

mmcv/version.py

 # Copyright (c) OpenMMLab. All rights reserved.
 __version__ = '2.0.1'
+__hcu_version__ = '2.0.1'
 
 
 def parse_version_info(version_str: str, length: int = 4) -> tuple:
@@ -32,4 +33,4 @@ def parse_version_info(version_str: str, length: int = 4) -> tuple:
 
 version_info = tuple(int(x) for x in __version__.split('.')[:3])
 
-__all__ = ['__version__', '__dcu_version__', 'version_info', 'parse_version_info']
+__all__ = ['__version__', '__hcu_version__', 'version_info', 'parse_version_info']

setup.py

@@ -4,10 +4,7 @@ import platform
 import re
 from pkg_resources import DistributionNotFound, get_distribution, parse_version
 from setuptools import find_packages, setup
-import subprocess
-from typing import Optional, Union
-from pathlib import Path
-
+from get_version import get_version
 
 EXT_TYPE = ''
 try:
@@ -27,7 +24,6 @@ except ModuleNotFoundError:
     cmd_class = {}
     print('Skip building ext ops due to the absence of torch.')
 
-
 def choose_requirement(primary, secondary):
     """If some version of primary requirement installed, return primary, else
     return secondary."""
@@ -39,65 +35,11 @@ def choose_requirement(primary, secondary):
 
     return str(primary)
 
-
-def get_sha(pytorch_root: Union[str, Path]) -> str:
-    try:
-        return subprocess.check_output(['git', 'rev-parse', 'HEAD'], cwd=pytorch_root).decode('ascii').strip()
-    except Exception:
-        return 'Unknown'
-
-
-def get_abi():
-    try:
-        command = "echo '#include <string>' | gcc -x c++ -E -dM - | fgrep _GLIBCXX_USE_CXX11_ABI" 
-        result = subprocess.run(command, shell=True, capture_output=True, text=True) 
-        output = result.stdout.strip() 
-        abi = "abi" + output.split(" ")[-1]
-        return abi
-    except Exception:
-        return 'abiUnknown'
-
-
-def get_version_add(sha: Optional[str] = None) -> str:
-    version=''
-    mmcv_root = os.path.dirname(os.path.abspath(__file__))
-    add_version_path = os.path.join(os.path.join(mmcv_root, "mmcv"), "version.py")
-    if sha != 'Unknown':
-        if sha is None:
-            sha = get_sha(mmcv_root)
-        version = 'git' + sha[:7]
-
-    # abi
-    version += "." + get_abi()
-
-    # dtk version
-    if os.getenv("ROCM_PATH"):
-        rocm_path = os.getenv('ROCM_PATH', "")
-        rocm_version_path = os.path.join(rocm_path, '.info', "rocm_version")
-        with open(rocm_version_path, 'r',encoding='utf-8') as file:
-            lines = file.readlines()
-        rocm_version=lines[0][:-2].replace(".", "")
-        version += ".dtk" + rocm_version
-    
-    # torch version
-    version += ".torch" + torch.__version__[:4]
-
-    lines=[]
-    with open(add_version_path, 'r',encoding='utf-8') as file:
-        lines = file.readlines()
-    lines[2] = "__dcu_version__ = '2.0.1+{}'\n".format(version)
-    with open(add_version_path, encoding="utf-8",mode="w") as file:
-        file.writelines(lines)
-    file.close()
-
-
-def get_version():
-    get_version_add()
-    version_file = 'mmcv/version.py'
-    with open(version_file, encoding='utf-8') as f:
-        exec(compile(f.read(), version_file, 'exec'))
-    return locals()['__dcu_version__']
-
+#def get_version():
+#    version_file = 'mmcv/version.py'
+#    with open(version_file, encoding='utf-8') as f:
+#        exec(compile(f.read(), version_file, 'exec'))
+#    return locals()['__version__']
 
 def parse_requirements(fname='requirements/runtime.txt', with_version=True):
     """Parse the package dependencies listed in a requirements file but strips
@@ -189,7 +131,6 @@ except ImportError:
     for main, secondary in CHOOSE_INSTALL_REQUIRES:
         install_requires.append(choose_requirement(main, secondary))
 
-
 def get_extensions():
     extensions = []
 
@@ -319,7 +260,7 @@ def get_extensions():
             define_macros += [('MMCV_WITH_CUDA', None)]
             cuda_args = os.getenv('MMCV_CUDA_ARGS')
             extra_compile_args['nvcc'] = [cuda_args] if cuda_args else []
-            if is_rocm_pytorch and platform.system() != 'Windows':
+            if platform.system() != 'Windows':
                 extra_compile_args['nvcc'] += \
                     ['--gpu-max-threads-per-block=1024']
             op_files = glob.glob('./mmcv/ops/csrc/pytorch/*.cpp') + \