summaryrefslogtreecommitdiff
path: root/training
diff options
context:
space:
mode:
Diffstat (limited to 'training')
-rw-r--r--training/experiments/image_transformer.yaml13
-rw-r--r--training/run_experiment.py50
2 files changed, 46 insertions, 17 deletions
diff --git a/training/experiments/image_transformer.yaml b/training/experiments/image_transformer.yaml
index 9e8f9fc..bedcbb5 100644
--- a/training/experiments/image_transformer.yaml
+++ b/training/experiments/image_transformer.yaml
@@ -1,9 +1,12 @@
+seed: 4711
+
network:
+ desc: null
type: ImageTransformer
args:
encoder:
- type: None
- args: None
+ type: null
+ args: null
num_decoder_layers: 4
hidden_dim: 256
num_heads: 4
@@ -12,6 +15,7 @@ network:
transformer_activation: glu
model:
+ desc: null
type: LitTransformerModel
args:
optimizer:
@@ -31,11 +35,11 @@ model:
weight: None
ignore_index: -100
reduction: mean
-
monitor: val_loss
mapping: sentence_piece
data:
+ desc: null
type: IAMExtendedParagraphs
args:
batch_size: 16
@@ -55,6 +59,7 @@ callbacks:
patience: 10
trainer:
+ desc: null
args:
stochastic_weight_avg: true
auto_scale_batch_size: binsearch
@@ -62,6 +67,6 @@ trainer:
fast_dev_run: false
gpus: 1
precision: 16
- max_epocs: 512
+ max_epochs: 512
terminate_on_nan: true
weights_summary: true
diff --git a/training/run_experiment.py b/training/run_experiment.py
index 289866e..1fb4bc2 100644
--- a/training/run_experiment.py
+++ b/training/run_experiment.py
@@ -6,7 +6,7 @@ from typing import Dict, List, NamedTuple, Optional, Union, Type
import click
from loguru import logger
-from omegaconf import OmegaConf
+from omegaconf import DictConfig, OmegaConf
import pytorch_lightning as pl
import torch
from torch import nn
@@ -42,6 +42,14 @@ def _configure_logging(log_dir: Optional[Path], verbose: int = 0) -> None:
)
+def _load_config(file_path: Path) -> DictConfig:
+ """Return experiment config."""
+ logger.info(f"Loading config from: {file_path}")
+ if not file_path.exists():
+ raise FileNotFoundError(f"Experiment config not found at: {file_path}")
+ return OmegaConf.load(file_path)
+
+
def _import_class(module_and_class_name: str) -> type:
"""Import class from module."""
module_name, class_name = module_and_class_name.rsplit(".", 1)
@@ -50,26 +58,25 @@ def _import_class(module_and_class_name: str) -> type:
def _configure_callbacks(
- args: List[Union[OmegaConf, NamedTuple]]
+ callbacks: List[DictConfig],
) -> List[Type[pl.callbacks.Callback]]:
"""Configures lightning callbacks."""
pl_callbacks = [
- getattr(pl.callbacks, callback.type)(**callback.args) for callback in args
+ getattr(pl.callbacks, callback.type)(**callback.args) for callback in callbacks
]
return pl_callbacks
def _configure_logger(
- network: Type[nn.Module], args: Dict, use_wandb: bool
+ network: Type[nn.Module], args: Dict, use_wandb: bool
) -> pl.loggers.WandbLogger:
"""Configures lightning logger."""
if use_wandb:
pl_logger = pl.loggers.WandbLogger()
pl_logger.watch(network)
pl_logger.log_hyperparams(vars(args))
- else:
- pl_logger = pl.logger.TensorBoardLogger("training/logs")
- return pl_logger
+ return pl_logger
+ return pl.logger.TensorBoardLogger("training/logs")
def _save_best_weights(
@@ -89,7 +96,9 @@ def _save_best_weights(
wandb.save(best_model_path)
-def _load_lit_model(lit_model_class: type, network: Type[nn.Module], config: OmegaConf) -> Type[pl.LightningModule]:
+def _load_lit_model(
+ lit_model_class: type, network: Type[nn.Module], config: DictConfig
+) -> Type[pl.LightningModule]:
"""Load lightning model."""
if config.load_checkpoint is not None:
logger.info(
@@ -101,8 +110,17 @@ def _load_lit_model(lit_model_class: type, network: Type[nn.Module], config: Ome
return lit_model_class(network=network, **config.model.args)
-def run(path: str, train: bool, test: bool, tune: bool, use_wandb: bool) -> None:
+def run(
+ filename: str,
+ train: bool,
+ test: bool,
+ tune: bool,
+ use_wandb: bool,
+ verbose: int = 0,
+) -> None:
"""Runs experiment."""
+
+ _configure_logging(None, verbose=verbose)
logger.info("Starting experiment...")
# Seed everything in the experiment.
@@ -110,8 +128,8 @@ def run(path: str, train: bool, test: bool, tune: bool, use_wandb: bool) -> None
pl.utilities.seed.seed_everything(SEED)
# Load config.
- logger.info(f"Loading config from: {path}")
- config = OmegaConf.load(path)
+ file_path = EXPERIMENTS_DIRNAME / filename
+ config = _load_config(file_path)
# Load classes.
data_module_class = _import_class(f"text_recognizer.data.{config.data.type}")
@@ -169,8 +187,14 @@ def cli(
verbose: int,
) -> None:
"""Run experiment."""
- _configure_logging(None, verbose=verbose)
- run(path=experiment_config, train=train, test=test, tune=tune, use_wandb=use_wandb)
+ run(
+ filename=experiment_config,
+ train=train,
+ test=test,
+ tune=tune,
+ use_wandb=use_wandb,
+ verbose=verbose,
+ )
if __name__ == "__main__":