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update the gpu id

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mhz 2024-07-03 15:25:46 +02:00
parent 0c3cfb195a
commit 73324083ce
2 changed files with 5 additions and 3 deletions
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5
configs/config.yaml
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@ -2,6 +2,7 @@ general:
name: 'graph_dit' name: 'graph_dit'
wandb: 'disabled' wandb: 'disabled'
gpus: 1 gpus: 1
gpu_number: 3
resume: null resume: null
test_only: null test_only: null
sample_every_val: 2500 sample_every_val: 2500
@ -10,7 +11,7 @@ general:
chains_to_save: 1 chains_to_save: 1
log_every_steps: 50 log_every_steps: 50
number_chain_steps: 8 number_chain_steps: 8
final_model_samples_to_generate: 10000 final_model_samples_to_generate: 100
final_model_samples_to_save: 20 final_model_samples_to_save: 20
final_model_chains_to_save: 1 final_model_chains_to_save: 1
enable_progress_bar: False enable_progress_bar: False
@ -30,7 +31,7 @@ model:
lambda_train: [1, 10] # node and edge training weight lambda_train: [1, 10] # node and edge training weight
ensure_connected: True ensure_connected: True
train: train:
n_epochs: 10000 n_epochs: 5000
batch_size: 1200 batch_size: 1200
lr: 0.0002 lr: 0.0002
clip_grad: null clip_grad: null

3
graph_dit/main.py
View File

@ -175,6 +175,7 @@ def test(cfg: DictConfig):
elif cfg.general.resume is not None: elif cfg.general.resume is not None:
cfg, _ = get_resume_adaptive(cfg, model_kwargs) cfg, _ = get_resume_adaptive(cfg, model_kwargs)
os.chdir(cfg.general.resume.split("checkpoints")[0]) os.chdir(cfg.general.resume.split("checkpoints")[0])
# os.environ["CUDA_VISIBLE_DEVICES"] = cfg.general.gpu_number
model = Graph_DiT(cfg=cfg, **model_kwargs) model = Graph_DiT(cfg=cfg, **model_kwargs)
trainer = Trainer( trainer = Trainer(
gradient_clip_val=cfg.train.clip_grad, gradient_clip_val=cfg.train.clip_grad,
@ -182,7 +183,7 @@ def test(cfg: DictConfig):
accelerator="gpu" accelerator="gpu"
if torch.cuda.is_available() and cfg.general.gpus > 0 if torch.cuda.is_available() and cfg.general.gpus > 0
else "cpu", else "cpu",
devices=cfg.general.gpus devices=[cfg.general.gpu_number]
if torch.cuda.is_available() and cfg.general.gpus > 0 if torch.cuda.is_available() and cfg.general.gpus > 0
else None, else None,
max_epochs=cfg.train.n_epochs, max_epochs=cfg.train.n_epochs,