From d667b698b477cb6eca0474afc05898c4609e0f9f Mon Sep 17 00:00:00 2001
From: Schneider Leo <leo.schneider@etu.ec-lyon.fr>
Date: Tue, 15 Apr 2025 13:20:05 +0200
Subject: [PATCH] fix : checkpoint path fix : cpu per task
---
image_ref/config.py | 2 +-
image_ref/main_ray.py | 6 +++---
2 files changed, 4 insertions(+), 4 deletions(-)
diff --git a/image_ref/config.py b/image_ref/config.py
index 7137615..ae97ea3 100644
--- a/image_ref/config.py
+++ b/image_ref/config.py
@@ -17,7 +17,7 @@ def load_args_contrastive():
parser.add_argument('--dataset_val_dir', type=str, default='data/processed_data/npy_image/data_test_contrastive')
parser.add_argument('--dataset_test_dir', type=str, default=None)
parser.add_argument('--base_out', type=str, default='output/baseline')
- parser.add_argument('--dataset_ref_dir', type=str, default='image_ref/img_ref')
+ parser.add_argument('-- ', type=str, default='image_ref/img_ref')
parser.add_argument('--output', type=str, default='output/out_contrastive.csv')
parser.add_argument('--save_path', type=str, default='output/best_model_constrastive.pt')
parser.add_argument('--pretrain_path', type=str, default=None)
diff --git a/image_ref/main_ray.py b/image_ref/main_ray.py
index 90f4558..8ebb066 100644
--- a/image_ref/main_ray.py
+++ b/image_ref/main_ray.py
@@ -133,7 +133,7 @@ def train_model(config,args):
# Note to save a file like checkpoint, you still need to put it under a directory
# to construct a checkpoint.
with tempfile.TemporaryDirectory(
- dir='lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/checkpoints') as temp_checkpoint_dir:
+ dir='/lustre/fswork/projects/rech/bun/ucg81ws/these/pseudo_image/checkpoints') as temp_checkpoint_dir:
path = os.path.join(temp_checkpoint_dir, "checkpoint.pt")
torch.save(
@@ -212,7 +212,7 @@ def test_model(best_result, args):
def main(args, gpus_per_trial=1):
config = {
"lr": tune.loguniform(1e-4, 1e-2),
- "noise": tune.loguniform(1e-7, 500),
+ "noise": tune.loguniform(1, 1000),
"positive_prop": tune.uniform(0, 100),
"optimizer": tune.choice(['Adam', 'SGD']),
"sampler": tune.choice(['random', 'balanced']),
@@ -228,7 +228,7 @@ def main(args, gpus_per_trial=1):
tuner = tune.Tuner(
tune.with_resources(
tune.with_parameters(train_model, args=args),
- resources={"cpu": 80, "gpu": gpus_per_trial}
+ resources={"cpu": 20, "gpu": gpus_per_trial}
),
tune_config=tune.TuneConfig(
time_budget_s=3600 * 23.5,
--
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