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-rw-r--r--training/conf/experiment/vq_transformer_lines.yaml149
-rw-r--r--training/conf/experiment/vqgan.yaml98
-rw-r--r--training/conf/experiment/vqgan_htr_char.yaml59
-rw-r--r--training/conf/experiment/vqvae.yaml51
4 files changed, 0 insertions, 357 deletions
diff --git a/training/conf/experiment/vq_transformer_lines.yaml b/training/conf/experiment/vq_transformer_lines.yaml
deleted file mode 100644
index bbe1178..0000000
--- a/training/conf/experiment/vq_transformer_lines.yaml
+++ /dev/null
@@ -1,149 +0,0 @@
-# @package _global_
-
-defaults:
- - override /mapping: null
- - override /criterion: cross_entropy
- - override /callbacks: htr
- - override /datamodule: iam_lines
- - override /network: null
- - override /model: null
- - override /lr_schedulers: null
- - override /optimizers: null
-
-epochs: &epochs 512
-ignore_index: &ignore_index 3
-num_classes: &num_classes 57
-max_output_len: &max_output_len 89
-summary: [[1, 1, 56, 1024], [1, 89]]
-
-criterion:
- ignore_index: *ignore_index
-
-mapping: &mapping
- mapping:
- _target_: text_recognizer.data.mappings.emnist.EmnistMapping
-
-callbacks:
- stochastic_weight_averaging:
- _target_: pytorch_lightning.callbacks.StochasticWeightAveraging
- swa_epoch_start: 0.75
- swa_lrs: 1.0e-5
- annealing_epochs: 10
- annealing_strategy: cos
- device: null
-
-optimizers:
- madgrad:
- _target_: madgrad.MADGRAD
- lr: 3.0e-4
- momentum: 0.9
- weight_decay: 0
- eps: 1.0e-6
- parameters: network
-
-lr_schedulers:
- network:
- _target_: torch.optim.lr_scheduler.CosineAnnealingLR
- T_max: *epochs
- eta_min: 1.0e-5
- last_epoch: -1
- interval: epoch
- monitor: val/loss
-
-datamodule:
- batch_size: 16
- num_workers: 12
- train_fraction: 0.9
- pin_memory: true
- << : *mapping
-
-rotary_embedding: &rotary_embedding
- rotary_embedding:
- _target_: text_recognizer.networks.transformer.embeddings.rotary.RotaryEmbedding
- dim: 64
-
-attn: &attn
- dim: &hidden_dim 512
- num_heads: 4
- dim_head: 64
- dropout_rate: &dropout_rate 0.4
-
-network:
- _target_: text_recognizer.networks.vq_transformer.VqTransformer
- input_dims: [1, 56, 1024]
- hidden_dim: *hidden_dim
- num_classes: *num_classes
- pad_index: *ignore_index
- encoder:
- _target_: text_recognizer.networks.encoders.efficientnet.EfficientNet
- arch: b1
- stochastic_dropout_rate: 0.2
- bn_momentum: 0.99
- bn_eps: 1.0e-3
- decoder:
- depth: 6
- _target_: text_recognizer.networks.transformer.layers.Decoder
- self_attn:
- _target_: text_recognizer.networks.transformer.attention.Attention
- << : *attn
- causal: true
- << : *rotary_embedding
- cross_attn:
- _target_: text_recognizer.networks.transformer.attention.Attention
- << : *attn
- causal: false
- norm:
- _target_: text_recognizer.networks.transformer.norm.ScaleNorm
- normalized_shape: *hidden_dim
- ff:
- _target_: text_recognizer.networks.transformer.mlp.FeedForward
- dim: *hidden_dim
- dim_out: null
- expansion_factor: 4
- glu: true
- dropout_rate: *dropout_rate
- pre_norm: true
- pixel_pos_embedding:
- _target_: text_recognizer.networks.transformer.embeddings.axial.AxialPositionalEmbedding
- dim: *hidden_dim
- shape: [1, 32]
- quantizer:
- _target_: text_recognizer.networks.quantizer.quantizer.VectorQuantizer
- input_dim: 512
- codebook:
- _target_: text_recognizer.networks.quantizer.codebook.CosineSimilarityCodebook
- dim: 16
- codebook_size: 4096
- kmeans_init: true
- kmeans_iters: 10
- decay: 0.8
- eps: 1.0e-5
- threshold_dead: 2
- commitment: 1.0
-
-model:
- _target_: text_recognizer.models.vq_transformer.VqTransformerLitModel
- << : *mapping
- max_output_len: *max_output_len
- start_token: <s>
- end_token: <e>
- pad_token: <p>
-
-trainer:
- _target_: pytorch_lightning.Trainer
- stochastic_weight_avg: true
- auto_scale_batch_size: binsearch
- auto_lr_find: false
- gradient_clip_val: 0.5
- fast_dev_run: false
- gpus: 1
- precision: 16
- max_epochs: *epochs
- terminate_on_nan: true
- weights_summary: null
- limit_train_batches: 1.0
- limit_val_batches: 1.0
- limit_test_batches: 1.0
- resume_from_checkpoint: null
- accumulate_grad_batches: 1
- overfit_batches: 0
diff --git a/training/conf/experiment/vqgan.yaml b/training/conf/experiment/vqgan.yaml
deleted file mode 100644
index 726757f..0000000
--- a/training/conf/experiment/vqgan.yaml
+++ /dev/null
@@ -1,98 +0,0 @@
-# @package _global_
-
-defaults:
- - override /network: vqvae
- - override /criterion: null
- - override /model: lit_vqgan
- - override /callbacks: vae
- - override /optimizers: null
- - override /lr_schedulers: null
-
-epochs: &epochs 100
-ignore_index: &ignore_index 3
-num_classes: &num_classes 58
-max_output_len: &max_output_len 682
-summary: [[1, 1, 576, 640]]
-
-criterion:
- _target_: text_recognizer.criterion.vqgan_loss.VQGANLoss
- reconstruction_loss:
- _target_: torch.nn.BCEWithLogitsLoss
- reduction: mean
- discriminator:
- _target_: text_recognizer.criterion.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: 8.0e4
-
-mapping: &mapping
- mapping:
- _target_: text_recognizer.data.mappings.emnist.EmnistMapping
- extra_symbols: [ "\n" ]
-
-datamodule:
- _target_: text_recognizer.data.iam_extended_paragraphs.IAMExtendedParagraphs
- batch_size: 4
- num_workers: 12
- train_fraction: 0.9
- pin_memory: true
- << : *mapping
-
-lr_schedulers:
- network:
- _target_: torch.optim.lr_scheduler.CosineAnnealingLR
- T_max: *epochs
- eta_min: 1.0e-5
- last_epoch: -1
- interval: epoch
- monitor: val/loss
-
- discriminator:
- _target_: torch.optim.lr_scheduler.CosineAnnealingLR
- T_max: *epochs
- eta_min: 1.0e-5
- 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
-
-trainer:
- _target_: pytorch_lightning.Trainer
- stochastic_weight_avg: false
- auto_scale_batch_size: binsearch
- auto_lr_find: false
- gradient_clip_val: 0
- fast_dev_run: false
- gpus: 1
- precision: 16
- max_epochs: *epochs
- terminate_on_nan: true
- weights_summary: null
- limit_train_batches: 1.0
- limit_val_batches: 1.0
- limit_test_batches: 1.0
- resume_from_checkpoint: null
- accumulate_grad_batches: 2
- overfit_batches: 0
diff --git a/training/conf/experiment/vqgan_htr_char.yaml b/training/conf/experiment/vqgan_htr_char.yaml
deleted file mode 100644
index af3fa40..0000000
--- a/training/conf/experiment/vqgan_htr_char.yaml
+++ /dev/null
@@ -1,59 +0,0 @@
-defaults:
- - override /mapping: null
- - override /network: null
- - override /model: null
-
-mapping:
- _target_: text_recognizer.data.emnist_mapping.EmnistMapping
- extra_symbols: [ "\n" ]
-
-datamodule:
- word_pieces: false
- batch_size: 8
- augment: false
-
-criterion:
- ignore_index: 3
-
-network:
- _target_: text_recognizer.networks.vq_transformer.VqTransformer
- input_dims: [1, 576, 640]
- encoder_dim: 32
- hidden_dim: 256
- dropout_rate: 0.1
- num_classes: 58
- pad_index: 3
- no_grad: true
- decoder:
- _target_: text_recognizer.networks.transformer.Decoder
- dim: 256
- depth: 2
- num_heads: 8
- attn_fn: text_recognizer.networks.transformer.attention.Attention
- attn_kwargs:
- dim_head: 32
- dropout_rate: 0.2
- norm_fn: torch.nn.LayerNorm
- ff_fn: text_recognizer.networks.transformer.mlp.FeedForward
- ff_kwargs:
- dim_out: null
- expansion_factor: 4
- glu: true
- dropout_rate: 0.2
- cross_attend: true
- pre_norm: true
- rotary_emb: null
- pretrained_encoder_path: "training/logs/runs/2021-09-25/23-07-28"
-
-model:
- _target_: text_recognizer.models.vq_transformer.VqTransformerLitModel
- start_token: <s>
- end_token: <e>
- pad_token: <p>
- max_output_len: 682 # 451
- alpha: 1.0
-
-trainer:
- max_epochs: 64
- limit_train_batches: 0.1
- limit_val_batches: 0.1
diff --git a/training/conf/experiment/vqvae.yaml b/training/conf/experiment/vqvae.yaml
deleted file mode 100644
index d069aef..0000000
--- a/training/conf/experiment/vqvae.yaml
+++ /dev/null
@@ -1,51 +0,0 @@
-defaults:
- - override /network: vqvae
- - override /criterion: mse
- - override /model: lit_vqvae
- - override /callbacks: wandb_vae
- - override /optimizers: null
- # - override /lr_schedulers:
- # - cosine_annealing
-
-# lr_schedulers: null
-# network:
-# _target_: torch.optim.lr_scheduler.OneCycleLR
-# max_lr: 1.0e-2
-# total_steps: null
-# epochs: 100
-# steps_per_epoch: 200
-# pct_start: 0.1
-# anneal_strategy: cos
-# cycle_momentum: true
-# base_momentum: 0.85
-# max_momentum: 0.95
-# div_factor: 25
-# final_div_factor: 1.0e4
-# three_phase: true
-# last_epoch: -1
-# verbose: false
-
-# # Non-class arguments
-# interval: step
-# monitor: val/loss
-
-optimizers:
- network:
- _target_: madgrad.MADGRAD
- lr: 1.0e-4
- momentum: 0.9
- weight_decay: 0
- eps: 1.0e-7
-
- parameters: network
-
-trainer:
- max_epochs: 128
- limit_train_batches: 0.1
- limit_val_batches: 0.1
-
-datamodule:
- batch_size: 8
- # resize: [288, 320]
-
-summary: null
generated by cgit v1.2.3-70-g09d2 (git 2.46.0) at 2024-11-10 08:16:38 +0000