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Add support for Intel GPU to MNIST examples #1315

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Add support for Intel GPU to MNIST examples #1315

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13 changes: 9 additions & 4 deletions mnist/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,28 +82,33 @@ def main():
help='learning rate (default: 1.0)')
parser.add_argument('--gamma', type=float, default=0.7, metavar='M',
help='Learning rate step gamma (default: 0.7)')
parser.add_argument('--no-cuda', action='store_true', default=False,
parser.add_argument('--no-cuda', action='store_true',
help='disables CUDA training')
parser.add_argument('--no-mps', action='store_true', default=False,
parser.add_argument('--no-mps', action='store_true',
help='disables macOS GPU training')
parser.add_argument('--dry-run', action='store_true', default=False,
parser.add_argument('--no-xpu', action='store_true',
help='disables Intel GPU training')
parser.add_argument('--dry-run', action='store_true',
help='quickly check a single pass')
parser.add_argument('--seed', type=int, default=1, metavar='S',
help='random seed (default: 1)')
parser.add_argument('--log-interval', type=int, default=10, metavar='N',
help='how many batches to wait before logging training status')
parser.add_argument('--save-model', action='store_true', default=False,
parser.add_argument('--save-model', action='store_true',
help='For Saving the current Model')
args = parser.parse_args()
use_cuda = not args.no_cuda and torch.cuda.is_available()
use_mps = not args.no_mps and torch.backends.mps.is_available()
use_xpu = not args.no_mps and torch.xpu.is_available()

torch.manual_seed(args.seed)

if use_cuda:
device = torch.device("cuda")
elif use_mps:
device = torch.device("mps")
elif use_xpu:
device = torch.device("xpu")
else:
device = torch.device("cpu")

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1 change: 1 addition & 0 deletions mnist_forward_forward/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@ optional arguments:
--lr LR learning rate (default: 0.03)
--no_cuda disables CUDA training
--no_mps disables MPS training
--no_xpu disables XPU training
--seed SEED random seed (default: 1)
--save_model For saving the current Model
--train_size TRAIN_SIZE
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12 changes: 8 additions & 4 deletions mnist_forward_forward/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -102,18 +102,20 @@ def train(self, x_pos, x_neg):
help="learning rate (default: 0.03)",
)
parser.add_argument(
"--no_cuda", action="store_true", default=False, help="disables CUDA training"
"--no_cuda", action="store_true", help="disables CUDA training"
)
parser.add_argument(
"--no_mps", action="store_true", default=False, help="disables MPS training"
"--no_mps", action="store_true", help="disables MPS training"
)
parser.add_argument(
"--no_xpu", action="store_true", help="disables XPU training"
)
parser.add_argument(
"--seed", type=int, default=1, metavar="S", help="random seed (default: 1)"
)
parser.add_argument(
"--save_model",
action="store_true",
default=False,
help="For saving the current Model",
)
parser.add_argument(
Expand All @@ -126,7 +128,6 @@ def train(self, x_pos, x_neg):
parser.add_argument(
"--save-model",
action="store_true",
default=False,
help="For Saving the current Model",
)
parser.add_argument(
Expand All @@ -139,10 +140,13 @@ def train(self, x_pos, x_neg):
args = parser.parse_args()
use_cuda = not args.no_cuda and torch.cuda.is_available()
use_mps = not args.no_mps and torch.backends.mps.is_available()
use_xpu = not args.no_xpu and torch.xpu.is_available()
if use_cuda:
device = torch.device("cuda")
elif use_mps:
device = torch.device("mps")
elif use_xpu:
device = torch.device("xpu")
else:
device = torch.device("cpu")

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17 changes: 17 additions & 0 deletions mnist_rnn/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -8,3 +8,20 @@ pip install -r requirements.txt
python main.py
# CUDA_VISIBLE_DEVICES=2 python main.py # to specify GPU id to ex. 2
```

```bash
optional arguments:
-h, --help show this help message and exit
--batch_size input batch_size for training (default:64)
--testing_batch_size input batch size for testing (default: 1000)
--epochs EPOCHS number of epochs to train (default: 14)
--lr LR learning rate (default: 0.1)
--gamma learning rate step gamma (default: 0.7)
--cuda enables CUDA training
--xpu enables XPU training
--mps enables macos GPU training
--seed SEED random seed (default: 1)
--save_model For saving the current Model
--log_interval how many batches to wait before logging training status
--dry-run quickly check a single pass
```
10 changes: 7 additions & 3 deletions mnist_rnn/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -93,22 +93,26 @@ def main():
help='learning rate step gamma (default: 0.7)')
parser.add_argument('--cuda', action='store_true', default=False,
help='enables CUDA training')
parser.add_argument('--mps', action="store_true", default=False,
parser.add_argument('--mps', action="store_true",
help="enables MPS training")
parser.add_argument('--dry-run', action='store_true', default=False,
parser.add_argument('--xpu', action='store_true',
help='enables XPU training')
parser.add_argument('--dry-run', action='store_true',
help='quickly check a single pass')
parser.add_argument('--seed', type=int, default=1, metavar='S',
help='random seed (default: 1)')
parser.add_argument('--log-interval', type=int, default=10, metavar='N',
help='how many batches to wait before logging training status')
parser.add_argument('--save-model', action='store_true', default=False,
parser.add_argument('--save-model', action='store_true',
help='for Saving the current Model')
args = parser.parse_args()

if args.cuda and not args.mps:
device = "cuda"
elif args.mps and not args.cuda:
device = "mps"
elif args.xpu:
device = "xpu"
else:
device = "cpu"

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