release code

Dassl.ProGrad.pytorch/configs/datasets/da/cifar_stl.yaml

@@ -0,0 +1,7 @@
+INPUT:
+  SIZE: (32, 32)
+  PIXEL_MEAN: [0.5, 0.5, 0.5]
+  PIXEL_STD: [0.5, 0.5, 0.5]
+
+DATASET:
+  NAME: "CIFARSTL"

Dassl.ProGrad.pytorch/configs/datasets/da/digit5.yaml

@@ -0,0 +1,12 @@
+INPUT:
+  SIZE: (32, 32)
+  PIXEL_MEAN: [0.5, 0.5, 0.5]
+  PIXEL_STD: [0.5, 0.5, 0.5]
+  TRANSFORMS: ["normalize"]
+
+DATASET:
+  NAME: "Digit5"
+
+MODEL:
+  BACKBONE:
+    NAME: "cnn_digit5_m3sda"

Dassl.ProGrad.pytorch/configs/datasets/da/domainnet.yaml

@@ -0,0 +1,10 @@
+INPUT:
+  SIZE: (224, 224)
+  TRANSFORMS: ["random_flip", "random_translation", "normalize"]
+
+DATASET:
+  NAME: "DomainNet"
+
+MODEL:
+  BACKBONE:
+    NAME: "resnet101"

Dassl.ProGrad.pytorch/configs/datasets/da/mini_domainnet.yaml

@@ -0,0 +1,10 @@
+INPUT:
+  SIZE: (96, 96)
+  TRANSFORMS: ["random_flip", "random_translation", "normalize"]
+
+DATASET:
+  NAME: "miniDomainNet"
+
+MODEL:
+  BACKBONE:
+    NAME: "resnet18"

Dassl.ProGrad.pytorch/configs/datasets/da/office31.yaml

@@ -0,0 +1,14 @@
+INPUT:
+  SIZE: (224, 224)
+  TRANSFORMS: ["random_flip", "random_translation", "normalize"]
+
+DATASET:
+  NAME: "Office31"
+
+MODEL:
+  BACKBONE:
+    NAME: "resnet50"
+  HEAD:
+    NAME: "mlp"
+    HIDDEN_LAYERS: [256]
+    DROPOUT: 0.

Dassl.ProGrad.pytorch/configs/datasets/da/office_home.yaml

@@ -0,0 +1,5 @@
+INPUT:
+  SIZE: (224, 224)
+
+DATASET:
+  NAME: "OfficeHome"

Dassl.ProGrad.pytorch/configs/datasets/da/visda17.yaml

@@ -0,0 +1,13 @@
+INPUT:
+  SIZE: (224, 224)
+  TRANSFORMS: ["random_flip", "center_crop", "normalize"]
+
+DATASET:
+  NAME: "VisDA17"
+
+MODEL:
+  BACKBONE:
+    NAME: "resnet101"
+
+TEST:
+  PER_CLASS_RESULT: True