release code

Dassl.ProGrad.pytorch/configs/trainers/da/m3sda/digit5.yaml

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+DATALOADER:
+  TRAIN_X:
+    SAMPLER: "RandomDomainSampler"
+    BATCH_SIZE: 256
+  TRAIN_U:
+    SAME_AS_X: False
+    BATCH_SIZE: 64
+  TEST:
+    BATCH_SIZE: 256
+
+OPTIM:
+  NAME: "sgd"
+  LR: 0.05
+  STEPSIZE: [30]
+  MAX_EPOCH: 30
+  LR_SCHEDULER: "cosine"

Dassl.ProGrad.pytorch/configs/trainers/da/m3sda/domainnet.yaml

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+DATALOADER:
+  NUM_WORKERS: 4
+  TRAIN_X:
+    SAMPLER: "RandomDomainSampler"
+    BATCH_SIZE: 30
+  TRAIN_U:
+    SAME_AS_X: False
+    BATCH_SIZE: 6
+  TEST:
+    BATCH_SIZE: 30
+
+OPTIM:
+  NAME: "sgd"
+  LR: 0.002
+  MAX_EPOCH: 40
+  LR_SCHEDULER: "cosine"

Dassl.ProGrad.pytorch/configs/trainers/da/m3sda/mini_domainnet.yaml

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+DATALOADER:
+  NUM_WORKERS: 8
+  TRAIN_X:
+    SAMPLER: "RandomDomainSampler"
+    BATCH_SIZE: 192
+  TRAIN_U:
+    SAME_AS_X: False
+    BATCH_SIZE: 64
+  TEST:
+    BATCH_SIZE: 200
+
+OPTIM:
+  NAME: "sgd"
+  LR: 0.005
+  MAX_EPOCH: 60
+  LR_SCHEDULER: "cosine"