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authorGustaf Rydholm <gustaf.rydholm@gmail.com>2021-11-17 22:42:58 +0100
committerGustaf Rydholm <gustaf.rydholm@gmail.com>2021-11-17 22:42:58 +0100
commit2417288c9fe96264da708ce8d13ac7bc2faf83e3 (patch)
treea74fb7a8502b1642b71240608706efda14dee3f9 /training/conf/experiment
parent2cb2c5b38f0711267fecfe9c5e10940f4b4f79fc (diff)
Add new quantizer
Diffstat (limited to 'training/conf/experiment')
-rw-r--r--training/conf/experiment/vq_transformer_lines.yaml149
1 files changed, 149 insertions, 0 deletions
diff --git a/training/conf/experiment/vq_transformer_lines.yaml b/training/conf/experiment/vq_transformer_lines.yaml
new file mode 100644
index 0000000..bbe1178
--- /dev/null
+++ b/training/conf/experiment/vq_transformer_lines.yaml
@@ -0,0 +1,149 @@
+# @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