PermissionError: [Errno 13] Permission denied:

[sunsunshark]

When I started training using my data，such an error occurred data: centered: false dataset: AAPM image_size: 256 is_complex: false is_multi: false num_channels: 1 random_flip: true root: /media/sun/tomo/AAPM_data/256 uniform_dequantization: false device: !!python/object/apply:torch.device

• cuda
• 0 eval: batch_size: 8 begin_ckpt: 50 bpd_dataset: test enable_bpd: false enable_loss: true enable_sampling: true end_ckpt: 96 num_samples: 50000 model: attention_type: ddpm attn_resolutions: !!python/tuple
  • 16 beta_max: 20.0 beta_min: 0.1 ch_mult: !!python/tuple
  • 1
  • 2
  • 2
  • 2 conditional: true conv_size: 3 dropout: 0.0 ema_rate: 0.999 embedding_type: fourier fir: true fir_kernel:
  • 1
  • 3
  • 3
  • 1 fourier_scale: 16 init_scale: 0.0 name: ncsnpp nf: 128 nonlinearity: swish normalization: GroupNorm num_res_blocks: 4 num_scales: 2000 progressive: none progressive_combine: sum progressive_input: residual resamp_with_conv: true resblock_type: biggan scale_by_sigma: true sigma_max: 378 sigma_min: 0.01 skip_rescale: true optim: beta1: 0.9 eps: 1.0e-08 grad_clip: 1.0 lr: 0.0002 optimizer: Adam warmup: 5000 weight_decay: 0 sampling: corrector: langevin method: pc n_steps_each: 1 noise_removal: true predictor: reverse_diffusion probability_flow: false snr: 0.075 seed: 42 training: batch_size: 1 continuous: true epochs: 1000 eval_freq: 100 likelihood_weighting: false log_freq: 25 reduce_mean: false sde: vesde snapshot_freq: 50000 snapshot_freq_for_preemption: 5000 snapshot_sampling: true

Traceback (most recent call last): File "E:\py2\DiffusionMBIR-main\main.py", line 71, in app.run(main) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\absl\app.py", line 312, in run _run_main(main, args) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\absl\app.py", line 258, in _run_main sys.exit(main(argv)) File "E:\py2\DiffusionMBIR-main\main.py", line 62, in main run_lib.train(FLAGS.config, FLAGS.workdir) File "E:\py2\DiffusionMBIR-main\run_lib.py", line 82, in train state = restore_checkpoint(checkpoint_meta_dir, state, config.device) File "E:\py2\DiffusionMBIR-main\utils.py", line 38, in restore_checkpoint loaded_state = torch.load(ckpt_dir, map_location=device) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\torch\serialization.py", line 594, in load with _open_file_like(f, 'rb') as opened_file: File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\torch\serialization.py", line 230, in _open_file_like return _open_file(name_or_buffer, mode) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\torch\serialization.py", line 211, in init super(_open_file, self).init(open(name, mode)) PermissionError: [Errno 13] Permission denied: 'workdir\AAPM256\checkpoints-meta'

Process finished with exit code 1

How can I solve the problem?

[JoanNig]

When I started training using my data，such an error occurred data: centered: false dataset: AAPM image_size: 256 is_complex: false is_multi: false num_channels: 1 random_flip: true root: /media/sun/tomo/AAPM_data/256 uniform_dequantization: false device: !!python/object/apply:torch.device

• cuda

• 0 eval: batch_size: 8 begin_ckpt: 50 bpd_dataset: test enable_bpd: false enable_loss: true enable_sampling: true end_ckpt: 96 num_samples: 50000 model: attention_type: ddpm attn_resolutions: !!python/tuple

  • 16 beta_max: 20.0 beta_min: 0.1 ch_mult: !!python/tuple
  • 1
  • 2
  • 2
  • 2 conditional: true conv_size: 3 dropout: 0.0 ema_rate: 0.999 embedding_type: fourier fir: true fir_kernel:
  • 1
  • 3
  • 3
  • 1 fourier_scale: 16 init_scale: 0.0 name: ncsnpp nf: 128 nonlinearity: swish normalization: GroupNorm num_res_blocks: 4 num_scales: 2000 progressive: none progressive_combine: sum progressive_input: residual resamp_with_conv: true resblock_type: biggan scale_by_sigma: true sigma_max: 378 sigma_min: 0.01 skip_rescale: true optim: beta1: 0.9 eps: 1.0e-08 grad_clip: 1.0 lr: 0.0002 optimizer: Adam warmup: 5000 weight_decay: 0 sampling: corrector: langevin method: pc n_steps_each: 1 noise_removal: true predictor: reverse_diffusion probability_flow: false snr: 0.075 seed: 42 training: batch_size: 1 continuous: true epochs: 1000 eval_freq: 100 likelihood_weighting: false log_freq: 25 reduce_mean: false sde: vesde snapshot_freq: 50000 snapshot_freq_for_preemption: 5000 snapshot_sampling: true

Traceback (most recent call last): File "E:\py2\DiffusionMBIR-main\main.py", line 71, in app.run(main) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\absl\app.py", line 312, in run _run_main(main, args) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\absl\app.py", line 258, in _run_main sys.exit(main(argv)) File "E:\py2\DiffusionMBIR-main\main.py", line 62, in main run_lib.train(FLAGS.config, FLAGS.workdir) File "E:\py2\DiffusionMBIR-main\run_lib.py", line 82, in train state = restore_checkpoint(checkpoint_meta_dir, state, config.device) File "E:\py2\DiffusionMBIR-main\utils.py", line 38, in restore_checkpoint loaded_state = torch.load(ckpt_dir, map_location=device) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\torch\serialization.py", line 594, in load with _open_file_like(f, 'rb') as opened_file: File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\torch\serialization.py", line 230, in _open_file_like return _open_file(name_or_buffer, mode) File "D:\Anaconda\envs\diffusion-mbir\lib\site-packages\torch\serialization.py", line 211, in init super(_open_file, self).init(open(name, mode)) PermissionError: [Errno 13] Permission denied: 'workdir\AAPM256\checkpoints-meta'

Process finished with exit code 1

How can I solve the problem?

Hello Sunshark, I have also encountered the same problem as you. Have you solved this problem? May I ask for your advice on a solution?