add --device

dcgan/README.md

@@ -24,7 +24,7 @@ usage: main.py [-h] --dataset DATASET --dataroot DATAROOT [--workers WORKERS]
                [--batchSize BATCHSIZE] [--imageSize IMAGESIZE] [--nz NZ]
                [--ngf NGF] [--ndf NDF] [--niter NITER] [--lr LR]
                [--beta1 BETA1] [--cuda] [--ngpu NGPU] [--netG NETG]
-               [--netD NETD] [--mps]
+               [--netD NETD] [--mps] [--device DEVICE]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -41,6 +41,7 @@ optional arguments:
   --beta1 BETA1         beta1 for adam. default=0.5
   --cuda                enables cuda
   --mps                 enables macOS GPU
+  --device              backend device
   --ngpu NGPU           number of GPUs to use
   --netG NETG           path to netG (to continue training)
   --netD NETD           path to netD (to continue training)

dcgan/main.py

@@ -34,6 +34,7 @@
 parser.add_argument('--manualSeed', type=int, help='manual seed')
 parser.add_argument('--classes', default='bedroom', help='comma separated list of classes for the lsun data set')
 parser.add_argument('--mps', action='store_true', default=False, help='enables macOS GPU training')
+parser.add_argument('--device', type=str, default='cpu', help='backend device')
 
 opt = parser.parse_args()
 print(opt)
@@ -112,7 +113,7 @@
 elif use_mps:
     device = torch.device("mps")
 else:
-    device = torch.device("cpu")
+    device = torch.device(opt.device)
 
 ngpu = int(opt.ngpu)
 nz = int(opt.nz)

gat/README.md

@@ -69,7 +69,7 @@ python main.py --epochs 300 --lr 0.005 --l2 5e-4 --dropout-p 0.6 --num-heads 8 -
 In more detail, the `main.py` script recieves following arguments:
 ```
 usage: main.py [-h] [--epochs EPOCHS] [--lr LR] [--l2 L2] [--dropout-p DROPOUT_P] [--hidden-dim HIDDEN_DIM] [--num-heads NUM_HEADS] [--concat-heads] [--val-every VAL_EVERY]
-               [--no-cuda] [--no-mps] [--dry-run] [--seed S]
+               [--no-cuda] [--no-mps] [--dry-run] [--seed S] [--device DEVICE]
 
 PyTorch Graph Attention Network
 
@@ -89,6 +89,7 @@ options:
                         epochs to wait for print training and validation evaluation (default: 20)
   --no-cuda             disables CUDA training
   --no-mps              disables macOS GPU training
+  --device DEVICE       backend device
   --dry-run             quickly check a single pass
   --seed S              random seed (default: 13)
 ```

gat/main.py

@@ -311,6 +311,8 @@ def test(model, criterion, input, target, mask):
                         help='disables CUDA training')
     parser.add_argument('--no-mps', action='store_true', default=False,
                         help='disables macOS GPU training')
+    parser.add_argument('--device', type=str, default='cpu',
+                        help='backend device')
     parser.add_argument('--dry-run', action='store_true', default=False,
                         help='quickly check a single pass')
     parser.add_argument('--seed', type=int, default=13, metavar='S',
@@ -327,7 +329,7 @@ def test(model, criterion, input, target, mask):
     elif use_mps:
         device = torch.device('mps')
     else:
-        device = torch.device('cpu')
+        device = torch.device(args.device)
     print(f'Using {device} device')
 
     # Load the dataset

gcn/main.py

@@ -220,6 +220,8 @@ def test(model, criterion, input, target, mask):
                         help='disables CUDA training')
     parser.add_argument('--no-mps', action='store_true', default=False,
                         help='disables macOS GPU training')
+    parser.add_argument('--device', type=str, default='cpu',
+                        help='backend device')
     parser.add_argument('--dry-run', action='store_true', default=False,
                         help='quickly check a single pass')
     parser.add_argument('--seed', type=int, default=42, metavar='S',
@@ -236,7 +238,7 @@ def test(model, criterion, input, target, mask):
     elif use_mps:
         device = torch.device('mps')
     else:
-        device = torch.device('cpu')
+        device = torch.device(args.device)
     print(f'Using {device} device')
 
     cora_url = 'https://linqs-data.soe.ucsc.edu/public/lbc/cora.tgz'

language_translation/main.py

@@ -272,9 +272,9 @@ def main(opts):
                         help="Default learning rate")
     parser.add_argument("--batch", type=int, default=128,
                         help="Batch size")
-    parser.add_argument("--backend", type=str, default="cpu",
-                        help="Batch size")
-    
+    parser.add_argument("--device", type=str, default="cpu",
+                        help="backend device")
+
     # Transformer settings
     parser.add_argument("--attn_heads", type=int, default=8,
                         help="Number of attention heads")
@@ -298,7 +298,7 @@ def main(opts):
 
     args = parser.parse_args()
 
-    DEVICE = torch.device("cuda" if args.backend == "gpu" and torch.cuda.is_available() else "cpu")
+    DEVICE = torch.device("cuda" if args.device == "gpu" and torch.cuda.is_available() else args.device)
 
     if args.inference:
         inference(args)

legacy/snli/README.md

@@ -25,7 +25,7 @@ spacy
 Start the training process with:
 
 ```bash
-python train.py --lower --word-vectors [PATH_TO_WORD_VECTORS] --vector-cache [PATH_TO_VECTOR_CACHE] --epochs [NUMBER_OF_EPOCHS] --batch-size [BATCH_SIZE] --save-path [PATH_TO_SAVE_MODEL] --gpu [GPU_NUMBER]
+python train.py --lower --word-vectors [PATH_TO_WORD_VECTORS] --vector-cache [PATH_TO_VECTOR_CACHE] --epochs [NUMBER_OF_EPOCHS] --batch-size [BATCH_SIZE] --save-path [PATH_TO_SAVE_MODEL] --gpu [GPU_NUMBER] --device [BACKEND_DEVICE]
 ```
 
 ## 🏋️‍♀️ Training

legacy/snli/train.py

@@ -20,7 +20,7 @@
 elif torch.backends.mps.is_available():
     device = torch.device('mps')
 else:
-    device = torch.device('cpu')
+    device = torch.device(args.device)
 
 inputs = data.Field(lower=args.lower, tokenize='spacy')
 answers = data.Field(sequential=False)

legacy/snli/util.py

@@ -20,6 +20,8 @@ def makedirs(name):
 
 def get_args():
     parser = ArgumentParser(description='PyTorch/torchtext SNLI example')
+    parser.add_argument('--device', type=str, default='cpu',
+                        help='backend device')
     parser.add_argument('--epochs', type=int, default=50,
                         help='the number of total epochs to run.')
     parser.add_argument('--batch_size', type=int, default=128,

mnist/main.py

@@ -86,6 +86,8 @@ def main():
                         help='disables CUDA training')
     parser.add_argument('--no-mps', action='store_true', default=False,
                         help='disables macOS GPU training')
+    parser.add_argument('--device', type=str, default='cpu',
+                        help='backend device')
     parser.add_argument('--dry-run', action='store_true', default=False,
                         help='quickly check a single pass')
     parser.add_argument('--seed', type=int, default=1, metavar='S',
@@ -105,7 +107,7 @@ def main():
     elif use_mps:
         device = torch.device("mps")
     else:
-        device = torch.device("cpu")
+        device = torch.device(args.device)
 
     train_kwargs = {'batch_size': args.batch_size}
     test_kwargs = {'batch_size': args.test_batch_size}

mnist_forward_forward/README.md

@@ -18,6 +18,7 @@ optional arguments:
   --lr LR               learning rate (default: 0.03)
   --no_cuda             disables CUDA training
   --no_mps              disables MPS training
+  --device DEVICE       backend device
   --seed SEED           random seed (default: 1)
   --save_model          For saving the current Model
   --train_size TRAIN_SIZE

mnist_forward_forward/main.py

@@ -108,6 +108,9 @@ def train(self, x_pos, x_neg):
     parser.add_argument(
         "--no_mps", action="store_true", default=False, help="disables MPS training"
     )
+    parser.add_argument(
+        '--device', type=str, default='cpu', help='backend device'
+    )
     parser.add_argument(
         "--seed", type=int, default=1, metavar="S", help="random seed (default: 1)"
     )
@@ -145,7 +148,7 @@ def train(self, x_pos, x_neg):
     elif use_mps:
         device = torch.device("mps")
     else:
-        device = torch.device("cpu")
+        device = torch.device(args.device)
 
     train_kwargs = {"batch_size": args.train_size}
     test_kwargs = {"batch_size": args.test_size}

mnist_hogwild/README.md

@@ -21,6 +21,7 @@ optional arguments:
   --log_interval        how many batches to wait before logging training status
   --num_process         how many training processes to use (default: 2)
   --cuda                enables CUDA training
+  --device DEVICE       backend device
   --dry-run             quickly check a single pass
   --save-model          For Saving the current Model
 ```

mnist_hogwild/main.py

@@ -31,6 +31,8 @@
                     help='enables CUDA training')
 parser.add_argument('--mps', action='store_true', default=False,
                     help='enables macOS GPU training')
+parser.add_argument('--device', type=str, default='cpu',
+                    help='backend device')
 parser.add_argument('--save_model', action='store_true', default=False,
                     help='save the trained model to state_dict')
 parser.add_argument('--dry-run', action='store_true', default=False,
@@ -65,7 +67,7 @@ def forward(self, x):
     elif use_mps:
         device = torch.device("mps")
     else:
-        device = torch.device("cpu")
+        device = torch.device(args.device)
 
     transform=transforms.Compose([
         transforms.ToTensor(),

mnist_rnn/main.py

@@ -95,6 +95,8 @@ def main():
                         help='enables CUDA training')
     parser.add_argument('--mps', action="store_true", default=False,
                         help="enables MPS training")
+    parser.add_argument('--device', type=str, default='cpu',
+                        help='backend device')
     parser.add_argument('--dry-run', action='store_true', default=False,
                         help='quickly check a single pass')
     parser.add_argument('--seed', type=int, default=1, metavar='S',
@@ -110,7 +112,7 @@ def main():
     elif args.mps and not args.cuda:
         device = "mps"
     else:
-        device = "cpu"
+        device = args.device
 
     device = torch.device(device)