From 41c3e99fe57874ba1855c893bf47087d474ec6b8 Mon Sep 17 00:00:00 2001
From: Gustaf Rydholm <gustaf.rydholm@gmail.com>
Date: Mon, 25 Oct 2021 22:32:10 +0200
Subject: Updates to configs

---
 .../conf/experiment/cnn_htr_ctc_char_lines.yaml    | 149 +++++++++++++++++++++
 1 file changed, 149 insertions(+)
 create mode 100644 training/conf/experiment/cnn_htr_ctc_char_lines.yaml

(limited to 'training/conf/experiment/cnn_htr_ctc_char_lines.yaml')

diff --git a/training/conf/experiment/cnn_htr_ctc_char_lines.yaml b/training/conf/experiment/cnn_htr_ctc_char_lines.yaml
new file mode 100644
index 0000000..965d35f
--- /dev/null
+++ b/training/conf/experiment/cnn_htr_ctc_char_lines.yaml
@@ -0,0 +1,149 @@
+# @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]]
-- 
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