summaryrefslogtreecommitdiff
path: root/training/conf/experiment/vqgan_iam_lines.yaml
diff options
context:
space:
mode:
Diffstat (limited to 'training/conf/experiment/vqgan_iam_lines.yaml')
-rw-r--r--training/conf/experiment/vqgan_iam_lines.yaml105
1 files changed, 105 insertions, 0 deletions
diff --git a/training/conf/experiment/vqgan_iam_lines.yaml b/training/conf/experiment/vqgan_iam_lines.yaml
new file mode 100644
index 0000000..8bdf415
--- /dev/null
+++ b/training/conf/experiment/vqgan_iam_lines.yaml
@@ -0,0 +1,105 @@
+# @package _global_
+
+defaults:
+ - override /network: null
+ - override /criterion: null
+ - override /datamodule: null
+ - override /model: lit_vqgan
+ - override /callbacks: wandb_vae
+ - override /optimizers: null
+ - override /lr_schedulers: null
+
+criterion:
+ _target_: text_recognizer.criterions.vqgan_loss.VQGANLoss
+ reconstruction_loss:
+ _target_: torch.nn.BCEWithLogitsLoss
+ reduction: mean
+ discriminator:
+ _target_: text_recognizer.criterions.n_layer_discriminator.NLayerDiscriminator
+ in_channels: 1
+ num_channels: 64
+ num_layers: 3
+ commitment_weight: 0.25
+ discriminator_weight: 0.8
+ discriminator_factor: 1.0
+ discriminator_iter_start: 1.5e4
+
+datamodule:
+ _target_: text_recognizer.data.iam_lines.IAMLines
+ batch_size: 24
+ num_workers: 12
+ train_fraction: 0.8
+ augment: true
+ pin_memory: false
+
+lr_schedulers:
+ generator:
+ _target_: torch.optim.lr_scheduler.CosineAnnealingLR
+ T_max: 64
+ eta_min: 4.5e-6
+ last_epoch: -1
+ interval: epoch
+ monitor: val/loss
+# discriminator:
+# _target_: torch.optim.lr_scheduler.CosineAnnealingLR
+# T_max: 64
+# eta_min: 0.0
+# last_epoch: -1
+#
+# interval: epoch
+# monitor: val/loss
+
+optimizers:
+ generator:
+ _target_: madgrad.MADGRAD
+ lr: 1.0e-4
+ momentum: 0.5
+ weight_decay: 0
+ eps: 1.0e-7
+ parameters: network
+
+ discriminator:
+ _target_: madgrad.MADGRAD
+ lr: 4.5e-6
+ momentum: 0.5
+ weight_decay: 0
+ eps: 1.0e-6
+ parameters: loss_fn.discriminator
+
+network:
+ _target_: text_recognizer.networks.vqvae.vqvae.VQVAE
+ hidden_dim: 256
+ embedding_dim: 32
+ num_embeddings: 512
+ decay: 0.99
+ encoder:
+ _target_: text_recognizer.networks.vqvae.encoder.Encoder
+ in_channels: 1
+ hidden_dim: 32
+ channels_multipliers: [1, 4, 8]
+ dropout_rate: 0.0
+ activation: mish
+ use_norm: true
+ num_residuals: 2
+ residual_channels: 32
+ decoder:
+ _target_: text_recognizer.networks.vqvae.decoder.Decoder
+ out_channels: 1
+ hidden_dim: 32
+ channels_multipliers: [8, 4, 1]
+ dropout_rate: 0.0
+ activation: mish
+ use_norm: true
+ num_residuals: 2
+ residual_channels: 32
+
+trainer:
+ max_epochs: 64
+ # limit_train_batches: 0.1
+ # limit_val_batches: 0.1
+ # gradient_clip_val: 100
+
+# tune: false
+# train: true
+# test: false
+summary: [2, 1, 56, 1024]