From c2c4286d6168fb3bd6baeb00c624ea8b2a83a8ce Mon Sep 17 00:00:00 2001
From: dcarron <daniel.carron@idiap.ch>
Date: Wed, 12 Apr 2023 11:28:26 +0200
Subject: [PATCH] Removed unused arguments
---
src/ptbench/engine/trainer.py | 6 ++----
src/ptbench/scripts/train.py | 10 ----------
2 files changed, 2 insertions(+), 14 deletions(-)
diff --git a/src/ptbench/engine/trainer.py b/src/ptbench/engine/trainer.py
index cf8fc101..bb7fedab 100644
--- a/src/ptbench/engine/trainer.py
+++ b/src/ptbench/engine/trainer.py
@@ -153,7 +153,6 @@ def run(
data_loader,
valid_loader,
extra_valid_loaders,
- optimizer,
checkpoint_period,
device,
arguments,
@@ -187,8 +186,6 @@ def run(
an extra column with the loss of every dataset in this list is kept on
the final training log.
- optimizer : :py:mod:`torch.optim`
-
checkpoint_period : int
save a checkpoint every ``n`` epochs. If set to ``0`` (zero), then do
not save intermediary checkpoints
@@ -227,7 +224,7 @@ def run(
tensorboard_logger = TensorBoardLogger(output_folder, "logs_tensorboard")
resource_monitor = ResourceMonitor(
- interval=5.0,
+ interval=monitoring_interval,
has_gpu=(device.type == "cuda"),
main_pid=os.getpid(),
logging_level=logging.ERROR,
@@ -254,6 +251,7 @@ def run(
accelerator="auto",
devices="auto",
max_epochs=max_epoch,
+ accumulate_grad_batches=batch_chunk_count,
logger=[csv_logger, tensorboard_logger],
check_val_every_n_epoch=1,
callbacks=[LoggingCallback(resource_monitor), checkpoint_callback],
diff --git a/src/ptbench/scripts/train.py b/src/ptbench/scripts/train.py
index ea82f5a7..64f66a6a 100644
--- a/src/ptbench/scripts/train.py
+++ b/src/ptbench/scripts/train.py
@@ -125,12 +125,6 @@ def set_reproducible_cuda():
required=True,
cls=ResourceOption,
)
-@click.option(
- "--optimizer",
- help="A torch.optim.Optimizer that will be used to train the network",
- required=True,
- cls=ResourceOption,
-)
@click.option(
"--criterion",
help="A loss function to compute the CNN error for every sample "
@@ -291,7 +285,6 @@ def set_reproducible_cuda():
@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
def train(
model,
- optimizer,
output_folder,
epochs,
batch_size,
@@ -481,7 +474,6 @@ def train(
logger.info(f"Z-normalization with mean {mean} and std {std}")
arguments = {}
- arguments["epoch"] = 0
arguments["max_epoch"] = epochs
last_checkpoint_path = os.path.join(output_folder, "model_final_epoch.ckpt")
@@ -518,14 +510,12 @@ def train(
raise FileNotFoundError(f"Could not find checkpoint {resume_from}")
logger.info("Training for {} epochs".format(arguments["max_epoch"]))
- logger.info("Continuing from epoch {}".format(arguments["epoch"]))
run(
model=model,
data_loader=data_loader,
valid_loader=valid_loader,
extra_valid_loaders=extra_valid_loaders,
- optimizer=optimizer,
checkpoint_period=checkpoint_period,
device=device,
arguments=arguments,
--
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