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shahules786 2022-09-30 10:10:51 +05:30
parent c717e7c38c
commit 610c23a0eb
1 changed files with 2 additions and 4 deletions
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6
cli/train.py
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@ -4,14 +4,12 @@ from hydra.utils import instantiate
from omegaconf import DictConfig from omegaconf import DictConfig
from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping
from pytorch_lightning.loggers import MLFlowLogger from pytorch_lightning.loggers import MLFlowLogger
from pytorch_lightning.callbacks import TQDMProgressBar
@hydra.main(config_path="train_config",config_name="config") @hydra.main(config_path="train_config",config_name="config")
def main(config: DictConfig): def main(config: DictConfig):
callbacks = [] callbacks = []
callbacks.append(TQDMProgressBar(refresh_rate=10))
logger = MLFlowLogger(experiment_name=config.mlflow.experiment_name, logger = MLFlowLogger(experiment_name=config.mlflow.experiment_name,
run_name=config.mlflow.run_name, tags={"JOB_ID":os.environ.get("SLURM_JOBID")}) run_name=config.mlflow.run_name, tags={"JOB_ID":os.environ.get("SLURM_JOBID")})
@ -23,12 +21,12 @@ def main(config: DictConfig):
loss=parameters.get("loss"), metric = parameters.get("metric")) loss=parameters.get("loss"), metric = parameters.get("metric"))
checkpoint = ModelCheckpoint( checkpoint = ModelCheckpoint(
dirpath="",filename="model",monitor=parameters.get("loss"),verbose=False, dirpath="",filename="model",monitor="valid_loss",verbose=False,
mode="min",every_n_epochs=1 mode="min",every_n_epochs=1
) )
callbacks.append(checkpoint) callbacks.append(checkpoint)
early_stopping = EarlyStopping( early_stopping = EarlyStopping(
monitor=parameters.get("loss"), monitor="valid_loss",
mode="min", mode="min",
min_delta=0.0, min_delta=0.0,
patience=100, patience=100,