Better learning rate progression for 1-4 GPUs.

train.py

@@ -40,14 +40,17 @@
     #desc += '-car';      dataset = EasyDict(tfrecord_dir='lsun-car-512x384');  train.mirror_augment = False
     #desc += '-cat';      dataset = EasyDict(tfrecord_dir='lsun-cat-full');     train.mirror_augment = False
 
-    # Config presets from Progressive GAN (choose one).
-    #desc += '-1gpu'; submit_config.num_gpus = 1; sched.minibatch_base = 4; sched.minibatch_dict = {4: 128, 8: 128, 16: 128, 32: 64, 64: 32, 128: 16, 256: 8, 512: 4}; sched.G_lrate_dict = {1024: 0.0015}; sched.D_lrate_dict = EasyDict(sched.G_lrate_dict); train.total_kimg = 12000
-    #desc += '-2gpu'; submit_config.num_gpus = 2; sched.minibatch_base = 8; sched.minibatch_dict = {4: 256, 8: 256, 16: 128, 32: 64, 64: 32, 128: 16, 256: 8}; sched.G_lrate_dict = {512: 0.0015, 1024: 0.002}; sched.D_lrate_dict = EasyDict(sched.G_lrate_dict); train.total_kimg = 12000
-    #desc += '-4gpu'; submit_config.num_gpus = 4; sched.minibatch_base = 16; sched.minibatch_dict = {4: 512, 8: 256, 16: 128, 32: 64, 64: 32, 128: 16}; sched.G_lrate_dict = {256: 0.0015, 512: 0.002, 1024: 0.003}; sched.D_lrate_dict = EasyDict(sched.G_lrate_dict); train.total_kimg = 12000
-    desc += '-8gpu'; submit_config.num_gpus = 8; sched.minibatch_base = 32; sched.minibatch_dict = {4: 512, 8: 256, 16: 128, 32: 64, 64: 32}; sched.G_lrate_dict = {128: 0.0015, 256: 0.002, 512: 0.003, 1024: 0.003}; sched.D_lrate_dict = EasyDict(sched.G_lrate_dict); train.total_kimg = 12000
-
-    # Tuned config for StyleGAN.
-    train.total_kimg = 25000; sched.lod_initial_resolution = 8
+    # Number of GPUs.
+    #desc += '-1gpu'; submit_config.num_gpus = 1; sched.minibatch_base = 4; sched.minibatch_dict = {4: 128, 8: 128, 16: 128, 32: 64, 64: 32, 128: 16, 256: 8, 512: 4}
+    #desc += '-2gpu'; submit_config.num_gpus = 2; sched.minibatch_base = 8; sched.minibatch_dict = {4: 256, 8: 256, 16: 128, 32: 64, 64: 32, 128: 16, 256: 8}
+    #desc += '-4gpu'; submit_config.num_gpus = 4; sched.minibatch_base = 16; sched.minibatch_dict = {4: 512, 8: 256, 16: 128, 32: 64, 64: 32, 128: 16}
+    desc += '-8gpu'; submit_config.num_gpus = 8; sched.minibatch_base = 32; sched.minibatch_dict = {4: 512, 8: 256, 16: 128, 32: 64, 64: 32}
+
+    # Default options.
+    train.total_kimg = 25000
+    sched.lod_initial_resolution = 8
+    sched.G_lrate_dict = {128: 0.0015, 256: 0.002, 512: 0.003, 1024: 0.003}
+    sched.D_lrate_dict = EasyDict(sched.G_lrate_dict)
 
     # WGAN-GP loss for CelebA-HQ.
     #desc += '-wgangp'; G_loss = EasyDict(func_name='training.loss.G_wgan'); D_loss = EasyDict(func_name='training.loss.D_wgan_gp'); sched.G_lrate_dict = {k: min(v, 0.002) for k, v in sched.G_lrate_dict.items()}; sched.D_lrate_dict = EasyDict(sched.G_lrate_dict)