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Markfryazino / wav2lip-hq

Extension of Wav2Lip repository for processing high-quality videos.
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RuntimeError: storage has wrong size: expected -4754300013468754645 got 32 #4

Open Yathish27 opened 3 years ago

Yathish27 commented 3 years ago

Disable distributed. 2021-07-26 08:47:50,661 INFO: 

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          / __  |/ __ `// ___// // ___/\__ \ / /_/ /
         / /_/ // /_/ /(__  )/ // /__ ___/ // _, _/
        /_____/ \__,_//____//_/ \___//____//_/ |_|
 ______                   __   __                 __      __
/ ____/____   ____   ____/ /  / /   __  __ _____ / /__   / /

/ / / \ / \ / / / / / / / // // /// / / / // // // // // // // / / /__/ // // / / /< // __/ __/ __/ __/ /____/_/ \///|| (_)

Version Information: BasicSR: 1.3.3.10 PyTorch: 1.9.0+cu102 TorchVision: 0.10.0+cu102 2021-07-26 08:47:50,661 INFO: name: 001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb model_type: ESRGANModel scale: 4 num_gpu: 1 manual_seed: 0 datasets:[ train:[ name: face_dataset type: PairedImageDataset dataroot_gt: data/hq dataroot_lq: data/lq filename_tmpl: {} io_backend:[ type: disk ] gt_size: 384 use_flip: True use_rot: True use_shuffle: True num_worker_per_gpu: 1 batch_size_per_gpu: 4 dataset_enlarge_ratio: 1 prefetch_mode: None phase: train scale: 4 ] ] network_g:[ type: RRDBNet num_in_ch: 3 num_out_ch: 3 num_feat: 64 num_block: 23 ] network_d:[ type: VGGStyleDiscriminator128 num_in_ch: 3 num_feat: 64 ] path:[ pretrain_network_g: None strict_load_g: True resume_state: checkpoints/pretrained.state experiments_root: /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb models: /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb/models training_states: /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb/training_states log: /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb visualization: /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb/visualization ] train:[ optim_g:[ type: Adam lr: 0.0001 weight_decay: 0 betas: [0.9, 0.99] ] optim_d:[ type: Adam lr: 0.0001 weight_decay: 0 betas: [0.9, 0.99] ] scheduler:[ type: MultiStepLR milestones: [50000, 100000, 200000, 300000] gamma: 0.5 ] total_iter: 150000 warmup_iter: -1 pixel_opt:[ type: L1Loss loss_weight: 0.01 reduction: mean ] perceptual_opt:[ type: PerceptualLoss layer_weights:[ conv5_4: 1 ] vgg_type: vgg19 use_input_norm: True range_norm: False perceptual_weight: 1.0 style_weight: 0 criterion: l1 ] gan_opt:[ type: GANLoss gan_type: vanilla real_label_val: 1.0 fake_label_val: 0.0 loss_weight: 0.005 ] net_d_iters: 1 net_d_init_iters: 0 ] val:[ val_freq: 2500.0 save_img: True metrics:[ psnr:[ type: calculate_psnr crop_border: 4 test_y_channel: False ] ] ] logger:[ print_freq: 100 save_checkpoint_freq: 2500.0 use_tb_logger: True wandb:[ project: None resume_id: None ] ] dist_params:[ backend: nccl port: 29500 ] is_train: True dist: False rank: 0 world_size: 1

2021-07-26 08:47:50.932429: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0 2021-07-26 08:47:52,184 INFO: Dataset [PairedImageDataset] - face_dataset is built. 2021-07-26 08:47:52,184 INFO: Training statistics: Number of train images: 1730 Dataset enlarge ratio: 1 Batch size per gpu: 4 World size (gpu number): 1 Require iter number per epoch: 433 Total epochs: 346; iters: 150000. Set pretrain_network_g to /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb/models/net_g_67500.pth Set pretrain_network_d to /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb/models/net_d_67500.pth 2021-07-26 08:47:52,497 INFO: Network [RRDBNet] is created. 2021-07-26 08:47:52,553 INFO: Network: RRDBNet, with parameters: 16,697,987 2021-07-26 08:47:52,553 INFO: RRDBNet( (conv_first): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (body): Sequential( (0): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (1): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (2): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (3): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (4): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (5): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (6): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (7): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (8): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (9): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (10): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (11): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (12): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (13): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (14): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (15): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (16): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (17): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (18): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (19): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (20): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (21): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) (22): RRDB( (rdb1): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb2): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) (rdb3): ResidualDenseBlock( (conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv2): Conv2d(96, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv3): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv4): Conv2d(160, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv5): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) ) ) (conv_body): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv_up1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv_up2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv_hr): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (conv_last): Conv2d(64, 3, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (lrelu): LeakyReLU(negative_slope=0.2, inplace=True) ) 2021-07-26 08:47:52,616 INFO: Loading RRDBNet model from /content/wav2lip-hq/experiments/001_ESRGAN_x4_f64b23_custom16k_500k_B16G1_wandb/models/net_g_67500.pth. Traceback (most recent call last): File "basicsr/train.py", line 221, in train_pipeline(root_path) File "basicsr/train.py", line 138, in train_pipeline model = build_model(opt) File "/usr/local/lib/python3.7/dist-packages/basicsr/models/init.py", line 27, in build_model model = MODEL_REGISTRY.get(opt['model_type'])(opt) File "/usr/local/lib/python3.7/dist-packages/basicsr/models/sr_model.py", line 29, in init self.load_network(self.net_g, load_path, self.opt['path'].get('strict_load_g', True)) File "/usr/local/lib/python3.7/dist-packages/basicsr/models/base_model.py", line 265, in load_network load_net = torch.load(load_path, map_location=lambda storage, loc: storage) File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 608, in load return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args) File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 794, in _legacy_load deserialized_objects[key]._set_from_file(f, offset, f_should_read_directly) RuntimeError: storage has wrong size: expected -4754300013468754645 got 32