0717-0003

diffusion.py

@@ -237,7 +237,7 @@ class TrainConfig:
     # dim = 2
     dim = 3
     stride = (2,2) if dim == 2 else (2,2,4)
-    num_image = 1000#32000#20000#15000#7000#25600#3000#10000#1000#10000#5000#2560#800#2560
+    num_image = 1000#2000#20000#15000#7000#25600#3000#10000#1000#10000#5000#2560#800#2560
     batch_size = 1#2#50#20#2#100 # 10
     n_epoch = 8#4# 10#50#20#20#2#5#25 # 120
     HII_DIM = 64
@@ -586,7 +586,7 @@ def train(rank, world_size):
 
     ddp_setup(rank, world_size)
     
-    num_train_image_list = [3200]#[200]#[1600,3200,6400,12800,25600]
+    num_train_image_list = [3000]#[200]#[1600,3200,6400,12800,25600]
     for i, num_image in enumerate(num_train_image_list):
         config.num_image = num_image
         # config.world_size = world_size
@@ -677,7 +677,7 @@ if __name__ == "__main__":
     world_size = torch.cuda.device_count()
     print(f" sampling, world_size = {world_size} ".center(100,'-'))
     # num_train_image_list = [1600,3200,6400,12800,25600]
-    num_train_image_list = [3200]
+    num_train_image_list = [3000]
     num_new_img_per_gpu = 9
     max_num_img_per_gpu = 1