Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
get_minirocket_features results in:
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 852.00 MiB (GPU 0; 23.68 GiB total capacity; 20.68 GiB already allocated; 838.38 MiB free; 22.14 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
What am I doing wrong or what can I do to prevent OutOfMemoryError. Thanks in advance.
Hello, I am trying to get minirocket features of my dataset but when I try it like:
from tsai.models.MINIROCKET_Pytorch import * .... window_size = 96 dimensions = 27 //////shape of X_train => (500000, 96, 27) mrf = MiniRocketFeatures(window_size, dimensions).to(default_device()) mrf.fit(X_train) X_feat = get_minirocket_features(data, mrf, use_cuda=True, chunksize=1024, to_np=True)
get_minirocket_features results in: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 852.00 MiB (GPU 0; 23.68 GiB total capacity; 20.68 GiB already allocated; 838.38 MiB free; 22.14 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
What am I doing wrong or what can I do to prevent OutOfMemoryError. Thanks in advance.