From 80de5c023cb7740022a9b13b5f09b71d9e85f8e7 Mon Sep 17 00:00:00 2001
From: Gustaf Rydholm <gustaf.rydholm@gmail.com>
Date: Wed, 8 Jun 2022 08:41:40 +0200
Subject: Add conformer lines experiment

---
 training/conf/experiment/conformer_lines.yaml | 123 ++++++++++++++++++++++++++
 1 file changed, 123 insertions(+)
 create mode 100644 training/conf/experiment/conformer_lines.yaml

(limited to 'training/conf')

diff --git a/training/conf/experiment/conformer_lines.yaml b/training/conf/experiment/conformer_lines.yaml
new file mode 100644
index 0000000..c3f4ea5
--- /dev/null
+++ b/training/conf/experiment/conformer_lines.yaml
@@ -0,0 +1,123 @@
+# @package _global_
+
+defaults:
+  - override /mapping: null
+  - override /criterion: ctc
+  - override /callbacks: htr
+  - override /datamodule: iam_lines
+  - override /network: null
+  - override /model: null
+  - override /lr_schedulers: null
+  - override /optimizers: null
+
+epochs: &epochs 200
+num_classes: &num_classes 57
+max_output_len: &max_output_len 762
+summary: [[1, 57, 1024]]
+
+mapping: &mapping
+  mapping:
+    _target_: text_recognizer.data.mappings.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:
+  radam:
+    _target_: torch.optim.RAdam
+    lr: 3.0e-4
+    betas: [0.9, 0.999]
+    weight_decay: 0
+    eps: 1.0e-8
+    parameters: network
+
+lr_schedulers:
+  network:
+    _target_: torch.optim.lr_scheduler.ReduceLROnPlateau
+    mode: min
+    factor: 0.5
+    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/loss
+
+datamodule:
+  batch_size: 8
+  num_workers: 12
+  train_fraction: 0.9
+  pin_memory: true
+  << : *mapping
+
+network:
+  _target_: text_recognizer.networks.conformer.Conformer
+  depth: 16
+  num_classes: *num_classes
+  dim: &dim 128
+  block:
+    _target_: text_recognizer.networks.conformer.ConformerBlock
+    dim: *dim
+    attn:
+      _target_: text_recognizer.networks.conformer.Attention
+      dim: *dim
+      heads: 8
+      dim_head: 64
+      mult: 4
+    ff:
+      _target_: text_recognizer.networks.conformer.Feedforward
+      dim: *dim
+      expansion_factor: 4
+      dropout: 0.1
+    conv:
+      _target_: text_recognizer.networks.conformer.ConformerConv
+      dim: *dim
+      expansion_factor: 2
+      kernel_size: 31
+      dropout: 0.1
+  subsampler:
+    _target_: text_recognizer.networks.conformer.Subsampler
+    pixel_pos_embedding:
+      _target_: text_recognizer.networks.transformer.AxialPositionalEmbedding
+      dim: *dim
+      shape: [6, 127]
+    channels: *dim
+    depth: 3
+    dropout: 0.1
+
+model:
+  _target_: text_recognizer.models.conformer.LitConformer
+  <<: *mapping
+  max_output_len: *max_output_len
+  start_token: <s>
+  end_token: <e>
+  pad_token: <p>
+  blank_token: <b>
+
+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
-- 
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