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Params ... will not be optimized. Training error? #23

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ioctl-user opened this issue Jan 22, 2024 · 8 comments
Open

Params ... will not be optimized. Training error? #23

ioctl-user opened this issue Jan 22, 2024 · 8 comments
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@Srameo

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@ioctl-user
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I'm trying to train model using two pairs of RAW photos prepared according to https://github.com/Srameo/LED/blob/main/docs/demo.md

After training I'm running LED with the following command:

python scripts/image_process.py -p /ICCV23-LED/experiments/v0/models/net_g_latest.pth --data_path /input/ --save_path /output/

Resulting pictures looks clear from noise, with normal colors but very blurred.
May the problem be in a lot of warnings about parameters that will not be optimized?
If not, what should be changed?

Here is training log:

# python3 ./scripts/cutomized_denoiser.py -t "v0" -p pretrained/LED_Pretrain_None_None_CVPR20_Setting_Ratio1-200.pth --dataroot /input/Calibration/ --data_pair_list /input/Calibration/list
Disable distributed.
Path already exists. Rename it to /ICCV23-LED/tb_logger/v0_archived_20240122_130426
2024-01-22 13:04:26,952 INFO: 
     ______                   __   __                 __      __
    / ____/____   ____   ____/ /  / /   __  __ _____ / /__   / /
   / / __ / __ \ / __ \ / __  /  / /   / / / // ___// //_/  / /
  / /_/ // /_/ // /_/ // /_/ /  / /___/ /_/ // /__ / /<    /_/
  \____/ \____/ \____/ \____/  /_____/\____/ \___//_/|_|  (_)
    
Version Information: 
        LED: 0.1.1
        PyTorch: 1.13.1+cu117
        TorchVision: 0.14.1+cu117
2024-01-22 13:04:26,952 INFO: 
  val:[
    val_freq: 99999.0
    save_img: False
    suffix: None
    calculate_metric_in_batch: True
    illumination_correct: True
    metric_in_srgb: False
    metrics:[
      psnr:[
        type: calculate_psnr
        crop_border: 2
        test_y_channel: False
      ]
      ssim:[
        type: calculate_ssim
        crop_border: 2
        test_y_channel: False
      ]
    ]
  ]
  logger:[
    print_freq: 200
    save_checkpoint_freq: 99999.0
    use_tb_logger: True
    wandb: None
  ]
  datasets:[
    train:[
      num_worker_per_gpu: 8
      batch_size_per_gpu: 1
      dataset_enlarge_ratio: 99999
      prefetch_mode: None
      name: DemoFinetuneDataset
      type: FewshotPairedRAWDataset
      dataroot: /input/Calibration/
      which_meta: gt
      data_pair_list: /input/Calibration/list
      zero_clip: False
      use_hflip: True
      use_rot: True
      crop_size: 1024
      phase: train
      scale: 1
    ]
  ]
  train:[
    generalize_first: True
    pixel_opt:[
      type: L1Loss
      loss_weight: 1.0
      reduction: mean
    ]
    total_iter: 1500
    align_iter: 1000
    oomn_iter: 500
    warmup_iter: -1
    align_opt:[
      optim_g:[
        type: Adam
        lr: 0.0001
        weight_decay: 0
        betas: [0.9, 0.999]
      ]
      scheduler:[
        type: HandieLR
        milestones: [999999]
        lrs: [0]
      ]
    ]
    oomn_opt:[
      optim_g:[
        type: Adam
        lr: 1e-05
        weight_decay: 0
        betas: [0.9, 0.999]
      ]
      scheduler:[
        type: HandieLR
        milestones: [999999]
        lrs: [0]
      ]
    ]
  ]
  repnr_opt:[
    dont_convert_module: ['conv10_1']
    branch_num: 5
    align_opts:[
      init_weight: 1.0
      init_bias: 0.0
    ]
    aux_conv_opts:[
      bias: True
      init: zero_init_
    ]
  ]
  network_g:[
    type: UNetArch
    inchannels: 4
    outchannels: 4
    channels: 32
  ]
  base: ['options/base/network_g/repnr_unet.yaml', 'options/base/finetune/CVPR20_ELD.yaml', 'options/base/val_and_logger.yaml']
  name: v0
  model_type: LEDFinetuneModel
  scale: 1
  num_gpu: 1
  manual_seed: 2022
  path:[
    pretrain_network_g: pretrained/LED_Pretrain_None_None_CVPR20_Setting_Ratio1-200.pth
    strict_load_g: False
    resume_state: None
    experiments_root: /ICCV23-LED/experiments/v0
    models: /ICCV23-LED/experiments/v0/models
    training_states: /ICCV23-LED/experiments/v0/training_states
    log: /ICCV23-LED/experiments/v0
    visualization: /ICCV23-LED/experiments/v0/visualization
  ]
  dist: False
  rank: 0
  world_size: 1
  auto_resume: False
  is_train: True
  root_path: /ICCV23-LED

load lq metas in mem...: 100%|███████████████████████████████████████████████████| 2/2 [00:00<00:00,  2.29it/s]
load gt metas in mem...: 100%|███████████████████████████████████████████████████| 2/2 [00:00<00:00,  2.47it/s]
2024-01-22 13:04:28,777 INFO: Dataset [FewshotPairedRAWDataset] - DemoFinetuneDataset is built.
/opt/conda/envs/LED-ICCV23/lib/python3.8/site-packages/torch/utils/data/dataloader.py:554: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 4, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
  warnings.warn(_create_warning_msg(
2024-01-22 13:04:28,777 INFO: Training statistics:
        Number of train images: 2
        Dataset enlarge ratio: 99999
        Batch size per gpu: 1
        World size (gpu number): 1
        Require iter number per epoch: 199998
        Total epochs: 1; iters: 1500.
2024-01-22 13:04:28,836 INFO: Network [UNetArch] is created.
2024-01-22 13:04:28,836 INFO: Convert UNetArch into RepNRBase using kwargs:
OrderedDict([('dont_convert_module', ['conv10_1']), ('branch_num', 5), ('align_opts', OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])), ('aux_conv_opts', OrderedDict([('bias', True), ('init', 'zero_init_')]))])
2024-01-22 13:04:29,626 INFO: Network: RepNRBase, with parameters: 22,619,512
2024-01-22 13:04:29,626 INFO: RepNRBase: UNetArch(
  (conv1_1): RepNRConv2d(
    4, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv1_2): RepNRConv2d(
    32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (pool1): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv2_1): RepNRConv2d(
    32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv2_2): RepNRConv2d(
    64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (pool2): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv3_1): RepNRConv2d(
    64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv3_2): RepNRConv2d(
    128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (pool3): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv4_1): RepNRConv2d(
    128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv4_2): RepNRConv2d(
    256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (pool4): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv5_1): RepNRConv2d(
    256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv5_2): RepNRConv2d(
    512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (upv6): ConvTranspose2d(512, 256, kernel_size=(2, 2), stride=(2, 2))
  (conv6_1): RepNRConv2d(
    512, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv6_2): RepNRConv2d(
    256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (upv7): ConvTranspose2d(256, 128, kernel_size=(2, 2), stride=(2, 2))
  (conv7_1): RepNRConv2d(
    256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv7_2): RepNRConv2d(
    128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (upv8): ConvTranspose2d(128, 64, kernel_size=(2, 2), stride=(2, 2))
  (conv8_1): RepNRConv2d(
    128, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv8_2): RepNRConv2d(
    64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (upv9): ConvTranspose2d(64, 32, kernel_size=(2, 2), stride=(2, 2))
  (conv9_1): RepNRConv2d(
    64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv9_2): RepNRConv2d(
    32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1, 1, 1), padding_mode=constant,
    branch_num=5, align_opts=OrderedDict([('init_weight', 1.0), ('init_bias', 0.0)])
    forward_type=reparameterize, aux_conv_opts=OrderedDict([('bias', True), ('init', 'zero_init_')])
  )
  (conv10_1): Conv2d(32, 4, kernel_size=(1, 1), stride=(1, 1))
)
2024-01-22 13:04:29,642 INFO: Loading RepNRBase model from pretrained/LED_Pretrain_None_None_CVPR20_Setting_Ratio1-200.pth, with param key: [params].
2024-01-22 13:04:29,660 WARNING: Current net - loaded net:
2024-01-22 13:04:29,660 WARNING:   conv1_1.aux_bias
2024-01-22 13:04:29,660 WARNING:   conv1_1.aux_weight
2024-01-22 13:04:29,660 WARNING:   conv1_2.aux_bias
2024-01-22 13:04:29,660 WARNING:   conv1_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv2_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv2_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv2_2.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv2_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv3_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv3_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv3_2.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv3_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv4_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv4_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv4_2.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv4_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv5_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv5_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv5_2.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv5_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv6_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv6_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv6_2.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv6_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv7_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv7_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv7_2.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv7_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv8_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv8_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv8_2.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv8_2.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv9_1.aux_bias
2024-01-22 13:04:29,661 WARNING:   conv9_1.aux_weight
2024-01-22 13:04:29,661 WARNING:   conv9_2.aux_bias
2024-01-22 13:04:29,662 WARNING:   conv9_2.aux_weight
2024-01-22 13:04:29,662 WARNING: Loaded net - current net:
2024-01-22 13:04:29,683 INFO: Loss [L1Loss] is created.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv1_1.weight will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv1_1.bias will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv1_2.weight will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv1_2.bias will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv2_1.weight will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv2_1.bias will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv2_2.weight will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv2_2.bias will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv3_1.weight will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv3_1.bias will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv3_2.weight will not be optimized.
2024-01-22 13:04:29,683 WARNING: Params base_module.conv3_2.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv4_1.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv4_1.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv4_2.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv4_2.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv5_1.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv5_1.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv5_2.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv5_2.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.upv6.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.upv6.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv6_1.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv6_1.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv6_2.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv6_2.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.upv7.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.upv7.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv7_1.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv7_1.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv7_2.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv7_2.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.upv8.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.upv8.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv8_1.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv8_1.bias will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv8_2.weight will not be optimized.
2024-01-22 13:04:29,684 WARNING: Params base_module.conv8_2.bias will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.upv9.weight will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.upv9.bias will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.conv9_1.weight will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.conv9_1.bias will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.conv9_2.weight will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.conv9_2.bias will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.conv10_1.weight will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params base_module.conv10_1.bias will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.main_weight will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.main_bias will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_2.main_weight will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_2.main_bias will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,685 WARNING: Params repnr_module.conv1_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv1_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv1_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv1_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv1_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv1_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv1_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.main_weight will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.main_bias will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.main_weight will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.main_bias will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,686 WARNING: Params repnr_module.conv2_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv2_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv2_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv2_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.main_weight will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.main_bias will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.main_weight will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.main_bias will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,687 WARNING: Params repnr_module.conv3_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.main_weight will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.main_bias will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.main_weight will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.main_bias will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv4_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv5_1.main_weight will not be optimized.
2024-01-22 13:04:29,688 WARNING: Params repnr_module.conv5_1.main_bias will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.main_weight will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.main_bias will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv5_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.upv6.weight will not be optimized, though it requires grad!
2024-01-22 13:04:29,689 WARNING: Params repnr_module.upv6.bias will not be optimized, though it requires grad!
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv6_1.main_weight will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv6_1.main_bias will not be optimized.
2024-01-22 13:04:29,689 WARNING: Params repnr_module.conv6_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.main_weight will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.main_bias will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv6_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.upv7.weight will not be optimized, though it requires grad!
2024-01-22 13:04:29,690 WARNING: Params repnr_module.upv7.bias will not be optimized, though it requires grad!
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv7_1.main_weight will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv7_1.main_bias will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv7_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,690 WARNING: Params repnr_module.conv7_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.main_weight will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.main_bias will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv7_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.upv8.weight will not be optimized, though it requires grad!
2024-01-22 13:04:29,691 WARNING: Params repnr_module.upv8.bias will not be optimized, though it requires grad!
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv8_1.main_weight will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv8_1.main_bias will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv8_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv8_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,691 WARNING: Params repnr_module.conv8_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.main_weight will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.main_bias will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv8_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.upv9.weight will not be optimized, though it requires grad!
2024-01-22 13:04:29,692 WARNING: Params repnr_module.upv9.bias will not be optimized, though it requires grad!
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv9_1.main_weight will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv9_1.main_bias will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv9_1.align_weights.0 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv9_1.align_weights.1 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv9_1.align_weights.2 will not be optimized.
2024-01-22 13:04:29,692 WARNING: Params repnr_module.conv9_1.align_weights.3 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_1.align_weights.4 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_1.align_biases.0 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_1.align_biases.1 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_1.align_biases.2 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_1.align_biases.3 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_1.align_biases.4 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.main_weight will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.main_bias will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_weights.0 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_weights.1 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_weights.2 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_weights.3 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_weights.4 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_biases.0 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_biases.1 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_biases.2 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_biases.3 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv9_2.align_biases.4 will not be optimized.
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv10_1.weight will not be optimized, though it requires grad!
2024-01-22 13:04:29,693 WARNING: Params repnr_module.conv10_1.bias will not be optimized, though it requires grad!
2024-01-22 13:04:29,694 INFO: Model [LEDFinetuneModel] is created.
2024-01-22 13:04:29,879 INFO: Start training from epoch: 0, iter: 0
2024-01-22 13:05:38,652 INFO: [v0..][epoch:  0, iter:     200, lr:(1.000e-04,)] [eta: 0:06:33, time (data): 0.344 (0.010)] l_pix: 1.1457e-02 
2024-01-22 13:06:40,049 INFO: [v0..][epoch:  0, iter:     400, lr:(1.000e-04,)] [eta: 0:05:34, time (data): 0.307 (0.007)] l_pix: 1.3481e-02 
2024-01-22 13:07:41,510 INFO: [v0..][epoch:  0, iter:     600, lr:(1.000e-04,)] [eta: 0:04:34, time (data): 0.307 (0.007)] l_pix: 9.3888e-03 
2024-01-22 13:08:42,970 INFO: [v0..][epoch:  0, iter:     800, lr:(1.000e-04,)] [eta: 0:03:33, time (data): 0.307 (0.006)] l_pix: 1.1264e-02 
2024-01-22 13:09:44,459 INFO: [v0..][epoch:  0, iter:   1,000, lr:(1.000e-04,)] [eta: 0:02:32, time (data): 0.307 (0.006)] l_pix: 1.2119e-02 
2024-01-22 13:09:44,475 INFO: Switch to optimize oomn branch....
2024-01-22 13:10:46,266 INFO: [v0..][epoch:  0, iter:   1,200, lr:(1.000e-05,)] [eta: 0:01:31, time (data): 0.309 (0.006)] l_pix: 1.0544e-02 
2024-01-22 13:11:48,080 INFO: [v0..][epoch:  0, iter:   1,400, lr:(1.000e-05,)] [eta: 0:00:30, time (data): 0.309 (0.006)] l_pix: 7.9759e-03 
2024-01-22 13:12:19,472 INFO: End of training. Time consumed: 0:07:49
2024-01-22 13:12:19,473 INFO: Save the latest model.
@Srameo
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Srameo commented Jan 22, 2024

Please refer to #13 (comment)

@ioctl-user
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ioctl-user commented Jan 22, 2024 •
edited

Question about Warning is gone. May you also note this Warning-feature in the training instruction to prevent the same further question?

Anyway, what another reasons could lead to the image blurring?

@Srameo
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Srameo commented Jan 22, 2024

There are many reasons that can cause blur, but the most likely is that your GT and Input are not aligned.

If you can provide an example, we should be able to offer further assistance.

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I have used remote mouse control for phone to make "GT" and noisy images to avoid unalignment...

Do you mean example of training pairs, or example of input RAW before denoise and it's output?

@Srameo
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Srameo commented Jan 22, 2024

The example of the input (after amplified by the ratio) and the output, or maybe both?

It would be better if these RAW images are postprocessed into sRGB images.

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ioctl-user commented Jan 22, 2024 •
edited

I made a photo of paper with CUPS default print page. In input the tux, circle and bar consists of points, in output it's gradient.

Github doesn't allow files bigger than 10Mb, so, sending a crop.
Please, let me know if I need sending another kind of photo.

in
out

@Srameo
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Srameo commented Jan 22, 2024

The blur might be caused by over denoise.

Is the pretrain ratio matches the testing ratio?

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ioctl-user commented Jan 22, 2024 •
edited

Do you mean ratio as 'Exposure level Noisy' / 'Exposure level GT' ?
If so, how can I calculate single testing image ratio?

In my case all training Noisy images has ISO 4799 and Exp 0.01 sec. All my training "GT" images has ISO 100 and Exp 0.4 sec.

Input image has ISO 793 and Exp 0.02 sec.

@Srameo Srameo self-assigned this Mar 11, 2024
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