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-rw-r--r--training/callbacks/wandb_callbacks.py23
-rw-r--r--training/conf/callbacks/wandb/watch.yaml2
-rw-r--r--training/conf/config.yaml2
-rw-r--r--training/conf/decoder/greedy.yaml2
-rw-r--r--training/conf/experiment/conv_transformer_lines.yaml30
-rw-r--r--training/conf/experiment/conv_transformer_paragraphs.yaml30
-rw-r--r--training/conf/experiment/vit_lines.yaml113
-rw-r--r--training/conf/logger/csv.yaml4
-rw-r--r--training/conf/logger/wandb.yaml2
-rw-r--r--training/conf/model/lit_transformer.yaml2
-rw-r--r--training/conf/network/conv_transformer.yaml26
-rw-r--r--training/conf/network/convnext.yaml8
-rw-r--r--training/conf/network/vit_lines.yaml37
-rw-r--r--training/conf/trainer/default.yaml6
-rw-r--r--training/main.py4
-rw-r--r--training/run.py4
-rw-r--r--training/utils.py8
17 files changed, 227 insertions, 76 deletions
diff --git a/training/callbacks/wandb_callbacks.py b/training/callbacks/wandb_callbacks.py
index 7d4f48e..1c7955c 100644
--- a/training/callbacks/wandb_callbacks.py
+++ b/training/callbacks/wandb_callbacks.py
@@ -3,23 +3,17 @@ from pathlib import Path
import wandb
from pytorch_lightning import Callback, LightningModule, Trainer
-from pytorch_lightning.loggers import LoggerCollection, WandbLogger
+from pytorch_lightning.loggers import Logger, WandbLogger
from pytorch_lightning.utilities import rank_zero_only
-from torch import nn
from torch.utils.data import DataLoader
-from torchvision.utils import make_grid
def get_wandb_logger(trainer: Trainer) -> WandbLogger:
"""Safely get W&B logger from Trainer."""
- if isinstance(trainer.logger, WandbLogger):
- return trainer.logger
-
- if isinstance(trainer.logger, LoggerCollection):
- for logger in trainer.logger:
- if isinstance(logger, WandbLogger):
- return logger
+ for logger in trainer.loggers:
+ if isinstance(logger, WandbLogger):
+ return logger
raise Exception("Weight and Biases logger not found for some reason...")
@@ -28,9 +22,12 @@ class WatchModel(Callback):
"""Make W&B watch the model at the beginning of the run."""
def __init__(
- self, log: str = "gradients", log_freq: int = 100, log_graph: bool = False
+ self,
+ log_params: str = "gradients",
+ log_freq: int = 100,
+ log_graph: bool = False,
) -> None:
- self.log = log
+ self.log_params = log_params
self.log_freq = log_freq
self.log_graph = log_graph
@@ -40,7 +37,7 @@ class WatchModel(Callback):
logger = get_wandb_logger(trainer)
logger.watch(
model=trainer.model,
- log=self.log,
+ log=self.log_params,
log_freq=self.log_freq,
log_graph=self.log_graph,
)
diff --git a/training/conf/callbacks/wandb/watch.yaml b/training/conf/callbacks/wandb/watch.yaml
index bada03b..660ae47 100644
--- a/training/conf/callbacks/wandb/watch.yaml
+++ b/training/conf/callbacks/wandb/watch.yaml
@@ -1,5 +1,5 @@
watch_model:
_target_: callbacks.wandb_callbacks.WatchModel
- log: gradients
+ log_params: gradients
log_freq: 100
log_graph: true
diff --git a/training/conf/config.yaml b/training/conf/config.yaml
index e57a8a8..8a1317c 100644
--- a/training/conf/config.yaml
+++ b/training/conf/config.yaml
@@ -13,7 +13,7 @@ defaults:
- network: conv_transformer
- optimizer: radam
- trainer: default
- - experiment: null
+ - experiment: vit_lines
seed: 4711
tune: false
diff --git a/training/conf/decoder/greedy.yaml b/training/conf/decoder/greedy.yaml
index 1d1a131..a88b5a6 100644
--- a/training/conf/decoder/greedy.yaml
+++ b/training/conf/decoder/greedy.yaml
@@ -1,2 +1,2 @@
-_target_: text_recognizer.models.greedy_decoder.GreedyDecoder
+_target_: text_recognizer.model.greedy_decoder.GreedyDecoder
max_output_len: 682
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
diff --git a/training/conf/logger/csv.yaml b/training/conf/logger/csv.yaml
new file mode 100644
index 0000000..9fa6cad
--- /dev/null
+++ b/training/conf/logger/csv.yaml
@@ -0,0 +1,4 @@
+csv:
+ _target_: pytorch_lightning.loggers.CSVLogger
+ name: null
+ save_dir: "."
diff --git a/training/conf/logger/wandb.yaml b/training/conf/logger/wandb.yaml
index 081ebeb..ba3218a 100644
--- a/training/conf/logger/wandb.yaml
+++ b/training/conf/logger/wandb.yaml
@@ -1,5 +1,5 @@
wandb:
- _target_: pytorch_lightning.loggers.wandb.WandbLogger
+ _target_: pytorch_lightning.loggers.WandbLogger
project: text-recognizer
name: null
save_dir: "."
diff --git a/training/conf/model/lit_transformer.yaml b/training/conf/model/lit_transformer.yaml
index e6af035..533f8f3 100644
--- a/training/conf/model/lit_transformer.yaml
+++ b/training/conf/model/lit_transformer.yaml
@@ -1,2 +1,2 @@
-_target_: text_recognizer.models.LitTransformer
+_target_: text_recognizer.model.transformer.LitTransformer
max_output_len: 682
diff --git a/training/conf/network/conv_transformer.yaml b/training/conf/network/conv_transformer.yaml
index 016adbb..1e03946 100644
--- a/training/conf/network/conv_transformer.yaml
+++ b/training/conf/network/conv_transformer.yaml
@@ -1,58 +1,58 @@
-_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, 8]
depths: [3, 3, 6]
downsampling_factors: [[2, 2], [2, 2], [2, 2]]
pixel_embedding:
- _target_: "text_recognizer.networks.transformer.embeddings.axial.\
+ _target_: "text_recognizer.network.transformer.embeddings.axial.\
AxialPositionalEmbeddingImage"
dim: &hidden_dim 128
axial_shape: [7, 128]
axial_dims: [64, 64]
decoder:
- _target_: text_recognizer.networks.text_decoder.TextDecoder
+ _target_: text_recognizer.network.text_decoder.TextDecoder
hidden_dim: *hidden_dim
num_classes: 58
pad_index: 3
decoder:
- _target_: text_recognizer.networks.transformer.Decoder
+ _target_: text_recognizer.network.transformer.Decoder
dim: *hidden_dim
depth: 10
block:
- _target_: text_recognizer.networks.transformer.decoder_block.DecoderBlock
+ _target_: text_recognizer.network.transformer.decoder_block.DecoderBlock
self_attn:
- _target_: text_recognizer.networks.transformer.Attention
+ _target_: text_recognizer.network.transformer.Attention
dim: *hidden_dim
num_heads: 12
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: *hidden_dim
num_heads: 12
dim_head: 64
dropout_rate: *dropout_rate
causal: false
norm:
- _target_: text_recognizer.networks.transformer.RMSNorm
+ _target_: text_recognizer.network.transformer.RMSNorm
dim: *hidden_dim
ff:
- _target_: text_recognizer.networks.transformer.FeedForward
+ _target_: text_recognizer.network.transformer.FeedForward
dim: *hidden_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: 64
token_pos_embedding:
- _target_: "text_recognizer.networks.transformer.embeddings.fourier.\
+ _target_: "text_recognizer.network.transformer.embeddings.fourier.\
PositionalEncoding"
dim: *hidden_dim
dropout_rate: 0.1
diff --git a/training/conf/network/convnext.yaml b/training/conf/network/convnext.yaml
index 63ad424..904bd56 100644
--- a/training/conf/network/convnext.yaml
+++ b/training/conf/network/convnext.yaml
@@ -1,17 +1,17 @@
-_target_: text_recognizer.networks.convnext.ConvNext
+_target_: text_recognizer.network.convnext.ConvNext
dim: 16
dim_mults: [2, 4, 8]
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: 128
heads: 4
dim_head: 64
scale: 8
ff:
- _target_: text_recognizer.networks.convnext.FeedForward
+ _target_: text_recognizer.network.convnext.FeedForward
dim: 128
mult: 4
diff --git a/training/conf/network/vit_lines.yaml b/training/conf/network/vit_lines.yaml
new file mode 100644
index 0000000..35f83c3
--- /dev/null
+++ b/training/conf/network/vit_lines.yaml
@@ -0,0 +1,37 @@
+_target_: text_recognizer.network.vit.VisionTransformer
+image_height: 56
+image_width: 1024
+patch_height: 28
+patch_width: 32
+dim: &dim 256
+num_classes: &num_classes 57
+encoder:
+ _target_: text_recognizer.network.transformer.encoder.Encoder
+ dim: *dim
+ inner_dim: 1024
+ heads: 8
+ dim_head: 64
+ depth: 6
+ dropout_rate: 0.0
+decoder:
+ _target_: text_recognizer.network.transformer.decoder.Decoder
+ dim: *dim
+ inner_dim: 1024
+ heads: 8
+ dim_head: 64
+ depth: 6
+ 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: true
+pad_index: 3
diff --git a/training/conf/trainer/default.yaml b/training/conf/trainer/default.yaml
index 6112cd8..2e593e8 100644
--- a/training/conf/trainer/default.yaml
+++ b/training/conf/trainer/default.yaml
@@ -1,14 +1,12 @@
_target_: pytorch_lightning.Trainer
-auto_scale_batch_size: binsearch
-auto_lr_find: false
gradient_clip_val: 0.5
fast_dev_run: false
-gpus: 1
+accelerator: gpu
+devices: 1
precision: 16
max_epochs: 256
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
diff --git a/training/main.py b/training/main.py
index 6e54a23..73adda0 100644
--- a/training/main.py
+++ b/training/main.py
@@ -4,7 +4,9 @@ from omegaconf import DictConfig
from training.metadata import TRAINING_DIR
-@hydra.main(version_base="1.2", config_path=TRAINING_DIR / "conf", config_name="config")
+@hydra.main(
+ version_base="1.2", config_path=str(TRAINING_DIR / "conf"), config_name="config"
+)
def main(config: DictConfig) -> None:
"""Loads config with hydra and runs the experiment."""
import utils
diff --git a/training/run.py b/training/run.py
index 288a1ef..cffc3ae 100644
--- a/training/run.py
+++ b/training/run.py
@@ -11,7 +11,7 @@ from pytorch_lightning import (
seed_everything,
Trainer,
)
-from pytorch_lightning.loggers import LightningLoggerBase
+from pytorch_lightning.loggers import Logger
from torch import nn
from torchinfo import summary
import utils
@@ -55,7 +55,7 @@ def run(config: DictConfig) -> Optional[float]:
# Load callback and logger.
callbacks: List[Type[Callback]] = utils.configure_callbacks(config)
- logger: List[Type[LightningLoggerBase]] = utils.configure_logger(config)
+ logger: List[Type[Logger]] = utils.configure_logger(config)
log.info(f"Instantiating trainer <{config.trainer._target_}>")
trainer: Trainer = hydra.utils.instantiate(
diff --git a/training/utils.py b/training/utils.py
index c8ea1be..d1801a7 100644
--- a/training/utils.py
+++ b/training/utils.py
@@ -10,7 +10,7 @@ from pytorch_lightning import (
LightningModule,
Trainer,
)
-from pytorch_lightning.loggers import LightningLoggerBase
+from pytorch_lightning.loggers import Logger
from pytorch_lightning.loggers.wandb import WandbLogger
from pytorch_lightning.utilities import rank_zero_only
from tqdm import tqdm
@@ -59,10 +59,10 @@ def configure_callbacks(
return callbacks
-def configure_logger(config: DictConfig) -> List[Type[LightningLoggerBase]]:
+def configure_logger(config: DictConfig) -> List[Type[Logger]]:
"""Configures Lightning loggers."""
- def load_logger(logger_config: DictConfig) -> Type[LightningLoggerBase]:
+ def load_logger(logger_config: DictConfig) -> Type[Logger]:
log.info(f"Instantiating logger <{logger_config._target_}>")
return hydra.utils.instantiate(logger_config)
@@ -137,7 +137,7 @@ def log_hyperparameters(
def finish(
- logger: List[Type[LightningLoggerBase]],
+ logger: List[Type[Logger]],
) -> None:
"""Makes sure everything closed properly."""
for lg in logger:
generated by cgit v1.2.3-70-g09d2 (git 2.46.0) at 2024-12-25 16:42:13 +0000