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你可以通过运行以下 Python 代码来验证环境变量是否设置成功: importosprint(os.environ.get("PYTORCH_CUDA_ALLOC_CONF"))# 输出应该是你之前设置的值,比如 "max_split_size_mb:64" 1. 2. 3. 序列图示意 下面是设置过程的简单序列图,帮助你理解每一步的执行顺序。 PythonScriptTerminalUserPythonScriptTerminalUs...
Problem The sign "=" is not supported in Windows environment variables. Thus, PYTORCH_CUDA_ALLOC_CONF=expandable_segments cannot be used on that platform. Solution Could you please either give me an alternative route I might have overloo...
请参阅内存管理和PYTORCH_CUDA_ALLOC_CONF 的文档 分享3910 pocketmirror吧 游游档 使用工具对内部文件修改进行翻译的步骤其实我开这个翻译工作还是算个有点心血来潮的想法……但既然大家都有想法那就弄得正式一点吧。 1.首 +1 59811 克苏鲁神话吧 无形的吹奏者 【无节操搬运】怪老头 译:Setarium 著:爱手艺1L...
You can enable this feature by `export PYTORCH_NPU_ALLOC_CONF = expandable_segments:True`. (function operator()) Traceback (most recent call last): File "/data_home/cly/ModelZoo-PyTorch/PyTorch/built-in/foundation/ChatGLM-6B/ptuning/preprocess.py", line 48, in <module> import ...
avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF I think the issue is that the dtype cast allocates a new tensor which if this tensor is already on the gpu might cause an OOM. One fix is to make sure all the tensors are on cpu first when loading...
从 运行时错误：CUDA内存不足。尝试分配33.84 GiB（GPU 0;79.35 GiB总容量;36.51 GiB已分配;32....
PYTORCH_CUDA_ALLOC_CONF是一个环境变量,用于配置 PyTorch 的 CUDA 内存分配行为。通过该变量,用户可以设置内存的预留方式、回收策略等,以优化深度学习任务的内存使用情况。例如,可以设定最大的内存分配单元、是否启用显存碎片整理等。 配置示例 为了更好地解释PYTORCH_CUDA_ALLOC_CONF的使用,下面是一个具体的代码示例。
memory in use. Of the allocated memory 20.40 GiB is allocated by PyTorch, and 2.72 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF ...