Remove unused configs

5 files changed, 0 insertions, 648 deletions

diff --git a/training/conf/experiment/cnn_htr_char_lines.yaml b/training/conf/experiment/cnn_htr_char_lines.yaml
deleted file mode 100644
index 759161c..0000000
--- a/training/conf/experiment/cnn_htr_char_lines.yaml
+++ /dev/null
@@ -1,149 +0,0 @@
-# @package _glbal_
-
-defaults:
-  - override /mapping: null
-  - override /criterion: null
-  - override /datamodule: null
-  - override /network: null
-  - override /model: null
-  - override /lr_schedulers: null
-  - override /optimizers: null
-
-
-epochs: &epochs 200
-ignore_index: &ignore_index 3
-num_classes: &num_classes 58
-max_output_len: &max_output_len 89
-
-criterion:
-  _target_: text_recognizer.criterions.label_smoothing.LabelSmoothingLoss
-  smoothing: 0.1 
-  ignore_index: *ignore_index
-    
-mapping: &mapping
-  mapping: 
-    _target_: text_recognizer.data.emnist_mapping.EmnistMapping
-
-callbacks:
-  stochastic_weight_averaging:
-    _target_: pytorch_lightning.callbacks.StochasticWeightAveraging
-    swa_epoch_start: 0.75
-    swa_lrs: 5.0e-5
-    annealing_epochs: 10
-    annealing_strategy: cos
-    device: null
-
-optimizers:
-  madgrad:
-    _target_: madgrad.MADGRAD
-    lr: 1.0e-4
-    momentum: 0.9
-    weight_decay: 0
-    eps: 1.0e-6
-    parameters: network
-
-lr_schedulers:
-  network:
-    _target_: torch.optim.lr_scheduler.OneCycleLR
-    max_lr: 3.0e-4
-    total_steps: null
-    epochs: *epochs
-    steps_per_epoch: 90
-    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: false
-    last_epoch: -1
-    verbose: false
-    # Non-class arguments
-    interval: step
-    monitor: val/loss
-
-datamodule:
-  _target_: text_recognizer.data.iam_lines.IAMLines
-  num_workers: 12
-  train_fraction: 0.9
-  pin_memory: true
-  transform: transform/iam_lines.yaml
-  test_transform: transform/iam_lines.yaml
-  target_transform: target_transform/word_pieces
-  <<: *mapping
-
-network:
-  _target_: text_recognizer.networks.conv_transformer.ConvTransformer
-  input_dims: [1, 56, 1024]
-  hidden_dim: &hidden_dim 256
-  encoder_dim: 1280
-  dropout_rate: 0.2
-  num_classes: *num_classes
-  pad_index: *ignore_index
-  encoder:
-    _target_: text_recognizer.networks.encoders.efficientnet.EfficientNet
-    arch: b0
-    out_channels: 1280
-    stochastic_dropout_rate: 0.2
-    bn_momentum: 0.99
-    bn_eps: 1.0e-3
-  decoder:
-    _target_: text_recognizer.networks.transformer.Decoder
-    dim: *hidden_dim
-    depth: 3 
-    num_heads: 4
-    attn_fn: text_recognizer.networks.transformer.attention.Attention
-    attn_kwargs:
-      dim_head: 32
-      dropout_rate: 0.2
-    norm_fn: text_recognizer.networks.transformer.norm.ScaleNorm
-    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:
-      _target_: text_recognizer.networks.transformer.positional_encodings.rotary_embedding.RotaryEmbedding
-      dim: 32
-  pixel_pos_embedding:
-    _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding2D
-    hidden_dim: *hidden_dim 
-    max_h: 18
-    max_w: 20
-  token_pos_embedding:
-    _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding
-    hidden_dim: *hidden_dim 
-    dropout_rate: 0.2
-    max_len: *max_output_len
-
-model:
-  _target_: text_recognizer.models.transformer.TransformerLitModel
-  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: 4
-  overfit_batches: 0
-
-summary: [[1, 1, 56, 1024], [1, 89]]
diff --git a/training/conf/experiment/cnn_htr_ctc_char_lines.yaml b/training/conf/experiment/cnn_htr_ctc_char_lines.yaml
deleted file mode 100644
index 965d35f..0000000
--- a/training/conf/experiment/cnn_htr_ctc_char_lines.yaml
+++ /dev/null
@@ -1,149 +0,0 @@
-# @package _global_
-
-defaults:
-  - override /mapping: null
-  - override /callbacks: htr
-  - override /criterion: null
-  - override /datamodule: null
-  - override /network: null
-  - override /model: null
-  - override /lr_schedulers: null
-  - override /optimizers: null
-
-
-epochs: &epochs 200
-ignore_index: &ignore_index 3
-num_classes: &num_classes 58
-max_output_len: &max_output_len 89
-
-criterion:
-  _target_: text_recognizer.criterions.ctc.CTCLoss
-  blank: *ignore_index
-    
-mapping: &mapping
-  mapping: 
-    _target_: text_recognizer.data.mappings.emnist_mapping.EmnistMapping
-
-callbacks:
-  stochastic_weight_averaging:
-    _target_: pytorch_lightning.callbacks.StochasticWeightAveraging
-    swa_epoch_start: 0.75
-    swa_lrs: 5.0e-5
-    annealing_epochs: 10
-    annealing_strategy: cos
-    device: null
-
-optimizers:
-  madgrad:
-    _target_: madgrad.MADGRAD
-    lr: 1.0e-4
-    momentum: 0.9
-    weight_decay: 0
-    eps: 1.0e-6
-    parameters: network
-
-lr_schedulers:
-  network:
-    _target_: torch.optim.lr_scheduler.OneCycleLR
-    max_lr: 3.0e-4
-    total_steps: null
-    epochs: *epochs
-    steps_per_epoch: 90
-    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: false
-    last_epoch: -1
-    verbose: false
-    # Non-class arguments
-    interval: step
-    monitor: val/loss
-
-datamodule:
-  _target_: text_recognizer.data.iam_lines.IAMLines
-  num_workers: 12
-  batch_size: 16
-  train_fraction: 0.9
-  pin_memory: true
-  transform: transform/iam_lines.yaml
-  test_transform: transform/iam_lines.yaml
-  <<: *mapping
-
-network:
-  _target_: text_recognizer.networks.conv_transformer.ConvTransformer
-  input_dims: [1, 56, 1024]
-  hidden_dim: &hidden_dim 256
-  encoder_dim: 1280
-  dropout_rate: 0.2
-  num_classes: *num_classes
-  pad_index: *ignore_index
-  encoder:
-    _target_: text_recognizer.networks.encoders.efficientnet.EfficientNet
-    arch: b0
-    out_channels: 1280
-    stochastic_dropout_rate: 0.2
-    bn_momentum: 0.99
-    bn_eps: 1.0e-3
-  decoder:
-    _target_: text_recognizer.networks.transformer.Decoder
-    dim: *hidden_dim
-    depth: 3 
-    num_heads: 4
-    attn_fn: text_recognizer.networks.transformer.attention.Attention
-    attn_kwargs:
-      dim_head: 32
-      dropout_rate: 0.2
-    norm_fn: text_recognizer.networks.transformer.norm.ScaleNorm
-    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:
-      _target_: text_recognizer.networks.transformer.positional_encodings.rotary_embedding.RotaryEmbedding
-      dim: 32
-  pixel_pos_embedding:
-    _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding2D
-    hidden_dim: *hidden_dim 
-    max_h: 1
-    max_w: 32
-  token_pos_embedding:
-    _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding
-    hidden_dim: *hidden_dim 
-    dropout_rate: 0.2
-    max_len: *max_output_len
-
-model:
-  _target_: text_recognizer.models.transformer.TransformerLitModel
-  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: 4
-  overfit_batches: 0
-
-summary: [[1, 1, 56, 1024], [1, 89]]
diff --git a/training/conf/experiment/cnn_htr_wp_lines.yaml b/training/conf/experiment/cnn_htr_wp_lines.yaml
deleted file mode 100644
index 9f1164a..0000000
--- a/training/conf/experiment/cnn_htr_wp_lines.yaml
+++ /dev/null
@@ -1,159 +0,0 @@
-# @package _global_
-
-defaults:
-  - override /mapping: null
-  - override /callbacks: htr
-  - override /criterion: null
-  - override /datamodule: null
-  - override /network: null
-  - override /model: null
-  - override /lr_schedulers: null
-  - override /optimizers: null
-
-epochs: &epochs 512
-ignore_index: &ignore_index 1000
-num_classes: &num_classes 1006
-max_output_len: &max_output_len 72
-
-criterion:
-  # _target_: torch.nn.CrossEntropyLoss
-  # ignore_index: *ignore_index
-  _target_: text_recognizer.criterions.label_smoothing.LabelSmoothingLoss
-  smoothing: 0.1
-  ignore_index: *ignore_index
-    
-mapping: &mapping
-  mapping:
-    _target_: text_recognizer.data.mappings.word_piece_mapping.WordPieceMapping
-    num_features: 1000
-    tokens: iamdb_1kwp_tokens_1000.txt
-    lexicon: iamdb_1kwp_lex_1000.txt
-    use_words: false
-    prepend_wordsep: false
-    special_tokens: [ <s>, <e>, <p> ]
-
-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: 1.0e-4
-    momentum: 0.9
-    weight_decay: 0
-    eps: 1.0e-6
-
-    parameters: network
-
-lr_schedulers:
-  network:
-    _target_: torch.optim.lr_scheduler.OneCycleLR
-    max_lr: 1.0e-4
-    total_steps: null
-    epochs: *epochs
-    steps_per_epoch: 179
-    pct_start: 0.03
-    anneal_strategy: cos
-    cycle_momentum: true
-    base_momentum: 0.85
-    max_momentum: 0.95
-    div_factor: 25
-    final_div_factor: 1.0e4
-    three_phase: false
-    last_epoch: -1
-    verbose: false
-    # Non-class arguments
-    interval: step
-    monitor: val/loss
-
-datamodule:
-  _target_: text_recognizer.data.iam_lines.IAMLines
-  num_workers: 12
-  batch_size: 16
-  train_fraction: 0.9
-  pin_memory: true
-  transform: transform/iam_lines.yaml
-  test_transform: transform/iam_lines.yaml
-  target_transform: target_transform/word_piece_iam.yaml
-  <<: *mapping
-
-network:
-  _target_: text_recognizer.networks.conv_transformer.ConvTransformer
-  input_dims: [1, 56, 1024]
-  hidden_dim: &hidden_dim 256
-  encoder_dim: 1280
-  dropout_rate: 0.2
-  num_classes: *num_classes
-  pad_index: *ignore_index
-  encoder:
-    _target_: text_recognizer.networks.encoders.efficientnet.EfficientNet
-    arch: b0
-    out_channels: 1280
-    stochastic_dropout_rate: 0.2
-    bn_momentum: 0.99
-    bn_eps: 1.0e-3
-  decoder:
-    _target_: text_recognizer.networks.transformer.Decoder
-    dim: *hidden_dim
-    depth: 3 
-    num_heads: 4
-    attn_fn: text_recognizer.networks.transformer.attention.Attention
-    attn_kwargs:
-      dim_head: 32
-      dropout_rate: 0.2
-    norm_fn: text_recognizer.networks.transformer.norm.ScaleNorm
-    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:
-      _target_: text_recognizer.networks.transformer.positional_encodings.rotary.RotaryEmbedding
-      dim: 32
-  pixel_pos_embedding:
-    _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding2D
-    hidden_dim: *hidden_dim 
-    max_h: 1
-    max_w: 32
-  token_pos_embedding:
-    _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding
-    hidden_dim: *hidden_dim 
-    dropout_rate: 0.2
-    max_len: *max_output_len
-
-model:
-  _target_: text_recognizer.models.transformer.TransformerLitModel
-  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: 4
-  overfit_batches: 0
-
-summary: [[1, 1, 56, 1024], [1, 89]]
diff --git a/training/conf/experiment/vqgan_htr_char_iam_lines.yaml b/training/conf/experiment/vqgan_htr_char_iam_lines.yaml
deleted file mode 100644
index 27fdfda..0000000
--- a/training/conf/experiment/vqgan_htr_char_iam_lines.yaml
+++ /dev/null
@@ -1,88 +0,0 @@
-defaults:
-  - override /mapping: null
-  - override /criterion: null
-  - override /datamodule: null
-  - override /network: null
-  - override /model: null
-  - override /lr_schedulers: null
-  # - override /optimizers: null
-
-
-criterion:
-  _target_: text_recognizer.criterions.label_smoothing.LabelSmoothingLoss
-  smoothing: 0.1 
-  ignore_index: 3
-    
-mapping:
-  _target_: text_recognizer.data.emnist_mapping.EmnistMapping
-  # extra_symbols: [ "\n" ]
-
-lr_schedulers:
-  network:
-    _target_: torch.optim.lr_scheduler.CosineAnnealingLR
-    T_max: 512
-    eta_min: 4.5e-6
-    last_epoch: -1
-    interval: epoch
-    monitor: val/loss
-
-datamodule:
-  _target_: text_recognizer.data.iam_lines.IAMLines
-  batch_size: 4
-  num_workers: 12
-  train_fraction: 0.8
-  augment: false
-  pin_memory: false
-
-
-# optimizers:
-#   - _target_: madgrad.MADGRAD
-#     lr: 2.0e-4
-#     momentum: 0.9
-#     weight_decay: 0
-#     eps: 1.0e-7
-#     parameters: network
-
-network:
-  _target_: text_recognizer.networks.vq_transformer.VqTransformer
-  input_dims: [1, 56, 1024]
-  encoder_dim: 32
-  hidden_dim: 32
-  dropout_rate: 0.1
-  num_classes: 58
-  pad_index: 3
-  no_grad: true
-  decoder:
-    _target_: text_recognizer.networks.transformer.Decoder
-    dim: 32
-    depth: 4
-    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/2021-09-26/23-27-57"
-
-model:
-  _target_: text_recognizer.models.vq_transformer.VqTransformerLitModel
-  start_token: <s>
-  end_token: <e>
-  pad_token: <p>
-  max_output_len: 89  # 451
-  alpha: 0.0
-
-trainer:
-  max_epochs: 512
-  # limit_train_batches: 0.1
-  # limit_val_batches: 0.1
-  # gradient_clip_val: 0.5
diff --git a/training/conf/experiment/vqgan_iam_lines.yaml b/training/conf/experiment/vqgan_iam_lines.yaml
deleted file mode 100644
index 890948c..0000000
--- a/training/conf/experiment/vqgan_iam_lines.yaml
+++ /dev/null
@@ -1,103 +0,0 @@
-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]