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authorGustaf Rydholm <gustaf.rydholm@gmail.com>2021-09-30 23:08:31 +0200
committerGustaf Rydholm <gustaf.rydholm@gmail.com>2021-09-30 23:08:31 +0200
commit9e98c19d9e218b465a7d03c1b22c1d480f065741 (patch)
tree03e37dbf0f753976f055a7434ae6dbb9112129c0 /training/conf/experiment/vqgan.yaml
parent4f0469f755507b15dae65510b2000a0ce077b423 (diff)
Updates to config files
Diffstat (limited to 'training/conf/experiment/vqgan.yaml')
-rw-r--r--training/conf/experiment/vqgan.yaml37
1 files changed, 26 insertions, 11 deletions
diff --git a/training/conf/experiment/vqgan.yaml b/training/conf/experiment/vqgan.yaml
index 34886ec..572c320 100644
--- a/training/conf/experiment/vqgan.yaml
+++ b/training/conf/experiment/vqgan.yaml
@@ -11,30 +11,41 @@ defaults:
criterion:
_target_: text_recognizer.criterions.vqgan_loss.VQGANLoss
reconstruction_loss:
- _target_: torch.nn.MSELoss
+ _target_: torch.nn.BCEWithLogitsLoss
reduction: mean
discriminator:
_target_: text_recognizer.criterions.n_layer_discriminator.NLayerDiscriminator
in_channels: 1
num_channels: 64
num_layers: 3
- vq_loss_weight: 1.0
+ commitment_weight: 0.25
discriminator_weight: 0.8
discriminator_factor: 1.0
- discriminator_iter_start: 7e4
+ discriminator_iter_start: 8.0e4
datamodule:
- batch_size: 8
+ batch_size: 12
# resize: [288, 320]
+ augment: false
lr_schedulers:
generator:
- _target_: torch.optim.lr_scheduler.CosineAnnealingLR
- T_max: 128
- eta_min: 4.5e-6
+ _target_: torch.optim.lr_scheduler.OneCycleLR
+ max_lr: 3.0e-4
+ total_steps: null
+ epochs: 64
+ steps_per_epoch: 1685
+ pct_start: 0.3
+ anneal_strategy: cos
+ cycle_momentum: true
+ base_momentum: 0.85
+ max_momentum: 0.95
+ div_factor: 25.0
+ final_div_factor: 10000.0
+ three_phase: true
last_epoch: -1
-
- interval: epoch
+ verbose: false
+ interval: step
monitor: val/loss
# discriminator:
@@ -66,7 +77,11 @@ optimizers:
parameters: loss_fn.discriminator
trainer:
- max_epochs: 128
+ max_epochs: 64
# limit_train_batches: 0.1
# limit_val_batches: 0.1
- gradient_clip_val: 100
+ # gradient_clip_val: 100
+
+# tune: false
+# train: true
+# test: false