conda-package-handling: 1.8.1-py37h8cc25b3_0 cpuonly: 2.0-0 pytorch libuv: 1.40.0-he774522_0 pytorch: 1.11.0-py3.7_cpu_0 pytorch pytorch-mutex: 1.0-cpu pytorch torchaudio: 0.11.0-py37_cpu pytorch torchvision: 0.12.0-py37_cpu pytorch typing_extensions: 4.1.1-pyh06a4308_0 The foll...
KernelFunction kernel, c10::optional<impl::CppSignature> cpp_signature, std::unique_ptr<FunctionSchema> inferred_function_schema, std::string debug ) { std::lock_guard<std::mutex> lock(mutex_); auto op = findOrRegisterName_(op_name); auto handle = op.operatorDef_-...
(参考:conda安装GPU版pytorch,却是cpu版本的原因_pytorch-mutex-CSDN博客) 在Anaconda Prompt里面打开虚拟环境,然后输入conda uninstall pytorch-mutex 在完成对 pytorch-mutex 库的卸载后,会发现cudatoolkit被降级为11.3版本。 重新安装pytorch: conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch ...
mutex2.release() # mutex2 解锁 mutex1.release() # mutex1 解锁 def func2(self): mutex2.acquire() print("func2 mutex2 acquire") time.sleep(1) mutex1.acquire() print("func2 mutex1 acquire") mutex1.release() mutex2.release() def run(self): self.func1() self.func2() mutex1 = ...
对于每个GraphTask,我们维护cpu_ready_queue_,这样在设备线程(即GPU)上执行时,如果是下一个NodeTask 应该在CPU上运行,我们就知道应该推送 NodeTask 到哪个就绪队列。 mutex_ :保护如下变量:not_ready_, dependencies_, captured_vars,has_error_, future_result_, cpu_ready_queue_, and leaf_streams。
对于每个GraphTask,我们维护cpu_ready_queue_,这样在设备线程(即GPU)上执行时,如果是下一个NodeTask 应该在CPU上运行,我们就知道应该推送 NodeTask 到哪个就绪队列。 mutex_ :保护如下变量:not_ready_, dependencies_, captured_vars,has_error_, future_result_, cpu_ready_queue_, and leaf_streams。
[conda] pytorch-mutex 1.0 cpu pytorch [conda] torchaudio 0.13.1 py38_cpu pytorch [conda] torchvision 0.14.1 py38_cpu pytorch cc@seemethere@malfet@osalpekar@atalman zou3519addedmodule: binariesAnything related to official binaries that we release to userstriagedThis issue has been looked at a...
std::mutex mutex; std::condition_variable not_done; std::unordered_map<Function*, InputBuffer> not_ready; std::unordered_map<Function*, int> dependencies; struct ExecInfo { bool needed = false; }; std::unordered_map<Function*, ExecInfo> exec_info; ...
7_cpu_0 pytorch-mutex anaconda/cloud/pytorch/noarch::pytorch-mutex-1.0-cpu requests anaconda/cloud/conda-forge/noarch::requests-2.28.2-pyhd8ed1ab_0 tbb anaconda/cloud/conda-forge/win-64::tbb-2021.7.0-h91493d7_1 tk anaconda/cloud/conda-forge/win-64::tk-8.6.12-h8ffe710_0 torchaudio ...
Like if we change cpuonly to be a mutex package then the installation instructions should still be: conda install -c pytorch pytorch cpuonly If those stay the same then yes I'd say this is reasonable. Author wolfv commented Jun 19, 2020 Yep, the installation instructions should stay the...