Update training stuff

3 files changed, 143 insertions, 30 deletions

diff --git a/training/conf/experiment/conv_transformer_lines.yaml b/training/conf/experiment/conv_transformer_lines.yaml
index 948968a..12fe701 100644
--- a/training/conf/experiment/conv_transformer_lines.yaml
+++ b/training/conf/experiment/conv_transformer_lines.yaml
@@ -56,70 +56,70 @@ datamodule:
   train_fraction: 0.95
 
 network:
-  _target_: text_recognizer.networks.ConvTransformer
+  _target_: text_recognizer.network.ConvTransformer
   encoder:
-    _target_: text_recognizer.networks.image_encoder.ImageEncoder
+    _target_: text_recognizer.network.image_encoder.ImageEncoder
     encoder:
-      _target_: text_recognizer.networks.convnext.ConvNext
+      _target_: text_recognizer.network.convnext.ConvNext
       dim: 16
       dim_mults: [2, 4, 32]
       depths: [3, 3, 6]
       downsampling_factors: [[2, 2], [2, 2], [2, 2]]
       attn:
-        _target_: text_recognizer.networks.convnext.TransformerBlock
+        _target_: text_recognizer.network.convnext.TransformerBlock
         attn:
-          _target_: text_recognizer.networks.convnext.Attention
+          _target_: text_recognizer.network.convnext.Attention
           dim: &dim 512
           heads: 4
           dim_head: 64
           scale: 8
         ff:
-          _target_: text_recognizer.networks.convnext.FeedForward
+          _target_: text_recognizer.network.convnext.FeedForward
           dim: *dim
           mult: 2
     pixel_embedding:
-      _target_: "text_recognizer.networks.transformer.embeddings.axial.\
+      _target_: "text_recognizer.network.transformer.embeddings.axial.\
         AxialPositionalEmbeddingImage"
       dim: *dim
       axial_shape: [7, 128]
   decoder:
-    _target_: text_recognizer.networks.text_decoder.TextDecoder
+    _target_: text_recognizer.network.text_decoder.TextDecoder
     dim: *dim
     num_classes: 58
     pad_index: *ignore_index
     decoder:
-      _target_: text_recognizer.networks.transformer.Decoder
+      _target_: text_recognizer.network.transformer.Decoder
       dim: *dim
       depth: 6
       block:
-        _target_: "text_recognizer.networks.transformer.decoder_block.\
+        _target_: "text_recognizer.network.transformer.decoder_block.\
           DecoderBlock"
         self_attn:
-          _target_: text_recognizer.networks.transformer.Attention
+          _target_: text_recognizer.network.transformer.Attention
           dim: *dim
           num_heads: 8
           dim_head: &dim_head 64
           dropout_rate: &dropout_rate 0.2
           causal: true
         cross_attn:
-          _target_: text_recognizer.networks.transformer.Attention
+          _target_: text_recognizer.network.transformer.Attention
           dim: *dim
           num_heads: 8
           dim_head: *dim_head
           dropout_rate: *dropout_rate
           causal: false
         norm:
-          _target_: text_recognizer.networks.transformer.RMSNorm
+          _target_: text_recognizer.network.transformer.RMSNorm
           dim: *dim
         ff:
-          _target_: text_recognizer.networks.transformer.FeedForward
+          _target_: text_recognizer.network.transformer.FeedForward
           dim: *dim
           dim_out: null
           expansion_factor: 2
           glu: true
           dropout_rate: *dropout_rate
       rotary_embedding:
-        _target_: text_recognizer.networks.transformer.RotaryEmbedding
+        _target_: text_recognizer.network.transformer.RotaryEmbedding
         dim: *dim_head
 
 model:
diff --git a/training/conf/experiment/conv_transformer_paragraphs.yaml b/training/conf/experiment/conv_transformer_paragraphs.yaml
index ff931cc..9df2ea9 100644
--- a/training/conf/experiment/conv_transformer_paragraphs.yaml
+++ b/training/conf/experiment/conv_transformer_paragraphs.yaml
@@ -57,70 +57,70 @@ datamodule:
   train_fraction: 0.95
 
 network:
-  _target_: text_recognizer.networks.ConvTransformer
+  _target_: text_recognizer.network.ConvTransformer
   encoder:
-    _target_: text_recognizer.networks.image_encoder.ImageEncoder
+    _target_: text_recognizer.network.image_encoder.ImageEncoder
     encoder:
-      _target_: text_recognizer.networks.convnext.ConvNext
+      _target_: text_recognizer.network.convnext.ConvNext
       dim: 16
       dim_mults: [1, 2, 4, 8, 32]
       depths: [2, 3, 3, 3, 6]
       downsampling_factors: [[2, 2], [2, 2], [2, 2], [2, 1], [2, 1]]
       attn:
-        _target_: text_recognizer.networks.convnext.TransformerBlock
+        _target_: text_recognizer.network.convnext.TransformerBlock
         attn:
-          _target_: text_recognizer.networks.convnext.Attention
+          _target_: text_recognizer.network.convnext.Attention
           dim: &dim 512
           heads: 4
           dim_head: 64
           scale: 8
         ff:
-          _target_: text_recognizer.networks.convnext.FeedForward
+          _target_: text_recognizer.network.convnext.FeedForward
           dim: *dim
           mult: 2
     pixel_embedding:
-      _target_: "text_recognizer.networks.transformer.embeddings.axial.\
+      _target_: "text_recognizer.network.transformer.embeddings.axial.\
         AxialPositionalEmbeddingImage"
       dim: *dim
       axial_shape: [18, 80]
   decoder:
-    _target_: text_recognizer.networks.text_decoder.TextDecoder
+    _target_: text_recognizer.network.text_decoder.TextDecoder
     dim: *dim
     num_classes: 58
     pad_index: *ignore_index
     decoder:
-      _target_: text_recognizer.networks.transformer.Decoder
+      _target_: text_recognizer.network.transformer.Decoder
       dim: *dim
       depth: 6
       block:
-        _target_: "text_recognizer.networks.transformer.decoder_block.\
+        _target_: "text_recognizer.network.transformer.decoder_block.\
           DecoderBlock"
         self_attn:
-          _target_: text_recognizer.networks.transformer.Attention
+          _target_: text_recognizer.network.transformer.Attention
           dim: *dim
           num_heads: 8
           dim_head: &dim_head 64
           dropout_rate: &dropout_rate 0.2
           causal: true
         cross_attn:
-          _target_: text_recognizer.networks.transformer.Attention
+          _target_: text_recognizer.network.transformer.Attention
           dim: *dim
           num_heads: 8
           dim_head: *dim_head
           dropout_rate: *dropout_rate
           causal: false
         norm:
-          _target_: text_recognizer.networks.transformer.RMSNorm
+          _target_: text_recognizer.network.transformer.RMSNorm
           dim: *dim
         ff:
-          _target_: text_recognizer.networks.transformer.FeedForward
+          _target_: text_recognizer.network.transformer.FeedForward
           dim: *dim
           dim_out: null
           expansion_factor: 2
           glu: true
           dropout_rate: *dropout_rate
       rotary_embedding:
-        _target_: text_recognizer.networks.transformer.RotaryEmbedding
+        _target_: text_recognizer.network.transformer.RotaryEmbedding
         dim: *dim_head
 
 trainer:
diff --git a/training/conf/experiment/vit_lines.yaml b/training/conf/experiment/vit_lines.yaml
new file mode 100644
index 0000000..e2ddebf
--- /dev/null
+++ b/training/conf/experiment/vit_lines.yaml
@@ -0,0 +1,113 @@
+# @package _global_
+
+defaults:
+  - override /criterion: cross_entropy
+  - override /callbacks: htr
+  - override /datamodule: iam_lines
+  - override /network: null
+  - override /model: lit_transformer
+  - override /lr_scheduler: null
+  - override /optimizer: null
+
+tags: [lines, vit]
+epochs: &epochs 64
+ignore_index: &ignore_index 3
+# summary: [[1, 1, 56, 1024], [1, 89]]
+
+logger:
+  wandb:
+    tags: ${tags}
+
+criterion:
+  ignore_index: *ignore_index
+  # label_smoothing: 0.05
+
+
+decoder:
+  max_output_len: 89
+
+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
+
+optimizer:
+  _target_: adan_pytorch.Adan
+  lr: 3.0e-4
+  betas: [0.02, 0.08, 0.01]
+  weight_decay: 0.02
+
+lr_scheduler:
+  _target_: torch.optim.lr_scheduler.ReduceLROnPlateau
+  mode: min
+  factor: 0.8
+  patience: 10
+  threshold: 1.0e-4
+  threshold_mode: rel
+  cooldown: 0
+  min_lr: 1.0e-5
+  eps: 1.0e-8
+  verbose: false
+  interval: epoch
+  monitor: val/cer
+
+datamodule:
+  batch_size: 8
+  train_fraction: 0.95
+
+network:
+  _target_: text_recognizer.network.vit.VisionTransformer
+  image_height: 56
+  image_width: 1024
+  patch_height: 28
+  patch_width: 32
+  dim: &dim 1024
+  num_classes: &num_classes 58
+  encoder:
+    _target_: text_recognizer.network.transformer.encoder.Encoder
+    dim: *dim
+    inner_dim: 2048
+    heads: 16
+    dim_head: 64
+    depth: 4
+    dropout_rate: 0.0
+  decoder:
+    _target_: text_recognizer.network.transformer.decoder.Decoder
+    dim: *dim
+    inner_dim: 2048
+    heads: 16
+    dim_head: 64
+    depth: 4
+    dropout_rate: 0.0
+  token_embedding:
+    _target_: "text_recognizer.network.transformer.embedding.token.\
+      TokenEmbedding"
+    num_tokens: *num_classes
+    dim: *dim
+    use_l2: true
+  pos_embedding:
+    _target_: "text_recognizer.network.transformer.embedding.absolute.\
+      AbsolutePositionalEmbedding"
+    dim: *dim
+    max_length: 89
+    use_l2: true
+  tie_embeddings: false
+  pad_index: 3
+
+model:
+  max_output_len: 89
+
+trainer:
+  fast_dev_run: false
+  gradient_clip_val: 1.0
+  max_epochs: *epochs
+  accumulate_grad_batches: 1
+  limit_val_batches: .02
+  limit_test_batches: .02
+  limit_train_batches: 1.0
+  # limit_val_batches: 1.0
+  # limit_test_batches: 1.0