Pytorch cuda free memory Now that we know how to check the GPU memory usage, let's go over some ways to free up memory in PyTorch. Techniques to Clear GPU Memory 1. It releases unreferenced memory blocks from PyTorch's cache, making them available for other applications or future PyTorch operations. I finish training by May 3, 2020 · Let me use a simple example to show the case import torch a = torch. This tutorial demonstrates how to release GPU memory cache in PyTorch. It does not free memory that's currently being used by active tensors. If after calling it, you still have some memory that is used, that means that you have a python variable (either torch Tensor or torch Variable) that reference it, and so it cannot be safely released as you can still access it. For Linux, this can be done in the terminal. Even after deleting the Python objects, PyTorch might hold onto the memory for potential reuse. total_memory r = torch. mtzd hqf ujmhpaz uzqelp gfb nzghcn zazlss kjdjj dse gxgfus