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Fix bug: model.eval() is back now

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xie_x1
2026-06-10 11:18:21 +02:00
parent e99942c7c3
commit 346845f6ea
1 changed files with 2 additions and 2 deletions
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Infer_2Photon.py
+2 -2
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@@ -152,7 +152,7 @@ if __name__ == "__main__":
model_version = conf.model.experiment_name.split('_v')[-1][:6] model_version = conf.model.experiment_name.split('_v')[-1][:6]
model = get_double_photon_model_class(model_version)().cuda() model = get_double_photon_model_class(model_version)().cuda()
model.load_state_dict(torch.load(f'{conf.model.base_dir}/{conf.model.experiment_name}/Models/{conf.model.name}', weights_only=True)) model.load_state_dict(torch.load(f'{conf.model.base_dir}/{conf.model.experiment_name}/Models/{conf.model.name}', weights_only=True))
# model.eval() model.eval()
### data loading ### data loading
files_list = get_files_list(conf) files_list = get_files_list(conf)
@@ -160,7 +160,7 @@ if __name__ == "__main__":
BinningFactor = conf.inference.binning_factor BinningFactor = conf.inference.binning_factor
numberOfAugOps = conf.inference.num_aug_ops numberOfAugOps = conf.inference.num_aug_ops
flag_normalize = conf.data.normalize flag_normalize = conf.data.normalize
nChunks = np.ceil(len(files_list) / 16).astype(int) nChunks = np.ceil(len(files_list) / conf.inference.chunk_size).astype(int)
ml_super_frame = np.zeros((NY*BinningFactor, NX*BinningFactor), dtype=np.int32) ml_super_frame = np.zeros((NY*BinningFactor, NX*BinningFactor), dtype=np.int32)
count_frame = np.zeros((NY, NX), dtype=np.int32) count_frame = np.zeros((NY, NX), dtype=np.int32)