update to pl 2.0

WangLibo1995 · May 12, 2023 · 6028412 · 6028412
1 parent b178af2
commit 6028412
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Showing 17 changed files with 2,147 additions and 2,018 deletions.
diff --git a/config/loveda/dcswin.py b/config/loveda/dcswin.py
@@ -26,8 +26,9 @@
 save_top_k = 1  # save the top k model weights on the validation set
 save_last = True  # save the last model weight, e.g. test_weights_name='last'
 check_val_every_n_epoch = 1  # run validation every n epoch
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # continue training with the checkpoint, default False
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network, use pretrained backbone, the weight path of backbone
 net = dcswin_small(num_classes=num_classes, pretrained=True, weight_path='pretrain_weights/stseg_small.pth')

diff --git a/config/potsdam/dcswin.py b/config/potsdam/dcswin.py
@@ -27,8 +27,9 @@
 save_top_k = 1
 save_last = False
 check_val_every_n_epoch = 1
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # more setting can refer to pytorch_lightning
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network
 net = dcswin_small(num_classes=num_classes)

diff --git a/config/potsdam/ftunetformer.py b/config/potsdam/ftunetformer.py
@@ -26,8 +26,9 @@
 save_top_k = 1
 save_last = False
 check_val_every_n_epoch = 1
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # continue training with the checkpoint, default False
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network
 net = ft_unetformer(num_classes=num_classes, decoder_channels=256)

diff --git a/config/potsdam/unetformer.py b/config/potsdam/unetformer.py
@@ -28,8 +28,9 @@
 save_top_k = 1
 save_last = True
 check_val_every_n_epoch = 1
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # continue training with the checkpoint, default False
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network
 net = UNetFormer(num_classes=num_classes)

diff --git a/config/uavid/unetformer.py b/config/uavid/unetformer.py
@@ -30,8 +30,9 @@
 save_top_k = 1
 save_last = True
 check_val_every_n_epoch = 1
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # continue training with the checkpoint, default False
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network
 net = UNetFormer(num_classes=num_classes)

diff --git a/config/vaihingen/dcswin.py b/config/vaihingen/dcswin.py
@@ -27,8 +27,9 @@
 save_top_k = 1
 save_last = False
 check_val_every_n_epoch = 1
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # continue training with the checkpoint, default False
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network
 net = dcswin_small(num_classes=num_classes)

diff --git a/config/vaihingen/ftunetformer.py b/config/vaihingen/ftunetformer.py
@@ -26,8 +26,9 @@
 save_top_k = 1
 save_last = False
 check_val_every_n_epoch = 1
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # continue training with the checkpoint, default False
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network
 net = ft_unetformer(num_classes=num_classes, decoder_channels=256)

diff --git a/config/vaihingen/unetformer.py b/config/vaihingen/unetformer.py
@@ -26,8 +26,9 @@
 save_top_k = 1
 save_last = True
 check_val_every_n_epoch = 1
+pretrained_ckpt_path = None # the path for the pretrained model weight
 gpus = 'auto'  # default or gpu ids:[0] or gpu nums: 2, more setting can refer to pytorch_lightning
-enable_checkpointing = False  # continue training with the checkpoint, default False
+enable_checkpointing = None  # whether continue training with the checkpoint, default None
 
 #  define the network
 net = UNetFormer(num_classes=num_classes)