deploy: braindecode/braindecode@fca0027

Author: bruAristimunha

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -15,7 +15,7 @@
       },
       "outputs": [],
       "source": [
-        "# Authors: Hubert Banville <hubert.jbanville@gmail.com>\n#\n# License: BSD (3-clause)\n\nimport time\nfrom itertools import product\n\nimport mne\nimport numpy as np\nimport pandas as pd\nimport seaborn as sns\nimport torch\nfrom torch import nn, optim\nfrom torch.utils.data import DataLoader\n\nfrom braindecode.datasets import TUHAbnormal\nfrom braindecode.models import Deep4Net, ShallowFBCSPNet\nfrom braindecode.preprocessing import create_fixed_length_windows\n\nmne.set_log_level(\"WARNING\")  # avoid messages every time a window is extracted"
+        "# Authors: Hubert Banville <hubert.jbanville@gmail.com>\n#\n# License: BSD (3-clause)\n\nimport time\nfrom itertools import product\n\nimport mne\nimport numpy as np\nimport pandas as pd\nimport seaborn as sns\nimport torch\nfrom torch import nn, optim\nfrom torch.utils.data import DataLoader\n\nfrom braindecode.datasets import TUHAbnormal\nfrom braindecode.models import Deep4Net, ShallowFBCSPNet\nfrom braindecode.preprocessing import create_fixed_length_windows\nfrom braindecode.util import set_random_seeds\n\nmne.set_log_level(\"WARNING\")  # avoid messages every time a window is extracted"
       ]
     },
     {
@@ -33,7 +33,7 @@
       },
       "outputs": [],
       "source": [
-        "N_JOBS = 8\ntorch.backends.cudnn.benchmark = True  # Enables automatic algorithm optimizations\ntorch.set_num_threads(N_JOBS)  # Sets the available number of threads"
+        "N_JOBS = 8\ntorch.backends.cudnn.benchmark = True  # Enables automatic algorithm optimizations\ntorch.set_num_threads(N_JOBS)  # Sets the available number of threads\ncuda = torch.cuda.is_available()\nseed = 20240205\nset_random_seeds(seed=seed, cuda=cuda)"
       ]
     },
     {