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@@ -1976,3 +1976,18 @@ baseline/DF2K/4xDF2K_plksr_tiny_fp16_patch64/training_states/200000.state filter
 baseline/DF2K/4xDF2K_plksr_tiny_fp16/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
 baseline/DF2K/4xDF2K_plksr_tiny_fp16/training_states/200000.state filter=lfs diff=lfs merge=lfs -text
 baseline/DF2K/4xDF2K_plksr_tiny/training_states/500000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/bhi/4ximagenet_bhi_span_fp16/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/default/4ximagenet_span_fp16/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa02/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa03/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa04/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa05/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa06/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
+imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa07/training_states/90000.state filter=lfs diff=lfs merge=lfs -text
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+imagenet/models/ic9600/4ximagenet_span_fp16_ic9600_04/training_states/100000.state filter=lfs diff=lfs merge=lfs -text
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imagenet/models/bhi/4ximagenet_bhi_span_fp16/4ximagenet_bhi_span_fp16.toml

@@ -0,0 +1,60 @@
+# GENERATE TIME: Sun Oct 27 00:57:15 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_bhi_span_fp16.toml
+
+name = "4ximagenet_bhi_span_fp16"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/imagenet_tiled_bhi/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/imagenet_tiled_bhi_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/bhi/4ximagenet_bhi_span_fp16/models/net_g_100000.pth

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imagenet/models/bhi/4ximagenet_bhi_span_fp16/training_states/100000.state

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imagenet/models/default/4ximagenet_span_fp16/4ximagenet_span_fp16.toml

@@ -0,0 +1,60 @@
+# GENERATE TIME: Mon Oct 21 22:53:34 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16.toml
+
+name = "4ximagenet_span_fp16"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/imagenet_tiled/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/imagenet_tiled_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/default/4ximagenet_span_fp16/models/net_g_100000.pth

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa02/4ximagenet_span_fp16_hyperiqa02.toml

@@ -0,0 +1,60 @@
+# GENERATE TIME: Tue Oct 22 00:39:44 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_hyperiqa02.toml
+
+name = "4ximagenet_span_fp16_hyperiqa02"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_02/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_02_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa02/models/net_g_100000.pth

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa02/training_states/100000.state

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa03/4ximagenet_span_fp16_hyperiqa03.toml

@@ -0,0 +1,60 @@
+# GENERATE TIME: Tue Oct 22 02:25:22 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_hyperiqa03.toml
+
+name = "4ximagenet_span_fp16_hyperiqa03"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_03/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_03_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa03/models/net_g_100000.pth

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa03/training_states/100000.state

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa04/4ximagenet_span_fp16_hyperiqa04.toml

@@ -0,0 +1,61 @@
+# GENERATE TIME: Thu Oct 24 19:59:58 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_hyperiqa04.toml
+
+name = "4ximagenet_span_fp16_hyperiqa04"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_04/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_04_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa04/models/net_g_100000.pth

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa04/training_states/100000.state

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa05/4ximagenet_span_fp16_hyperiqa05.toml

@@ -0,0 +1,61 @@
+# GENERATE TIME: Thu Oct 24 21:42:33 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_hyperiqa05.toml
+
+name = "4ximagenet_span_fp16_hyperiqa05"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_05/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_05_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa05/models/net_g_100000.pth

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa05/training_states/100000.state

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa06/4ximagenet_span_fp16_hyperiqa06.toml

@@ -0,0 +1,61 @@
+# GENERATE TIME: Thu Oct 24 23:23:55 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_hyperiqa06.toml
+
+name = "4ximagenet_span_fp16_hyperiqa06"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_06/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_06_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa06/models/net_g_100000.pth

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa07/4ximagenet_span_fp16_hyperiqa07.toml

@@ -0,0 +1,61 @@
+# GENERATE TIME: Fri Oct 25 01:03:23 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_hyperiqa07.toml
+
+name = "4ximagenet_span_fp16_hyperiqa07"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_07/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/hyperiqa_07_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa07/models/net_g_90000.pth

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imagenet/models/hyperiqa/4ximagenet_span_fp16_hyperiqa07/models/net_g_latest.pth

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imagenet/models/ic9600/4ximagenet_span_fp16_ic9600_01/4ximagenet_span_fp16_ic9600_01.toml

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+# GENERATE TIME: Fri Oct 25 02:53:07 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_ic9600_01.toml
+
+name = "4ximagenet_span_fp16_ic9600_01"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_01/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_01_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/ic9600/4ximagenet_span_fp16_ic9600_01/models/net_g_100000.pth

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imagenet/models/ic9600/4ximagenet_span_fp16_ic9600_02/4ximagenet_span_fp16_ic9600_02.toml

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+# GENERATE TIME: Fri Oct 25 04:38:31 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_ic9600_02.toml
+
+name = "4ximagenet_span_fp16_ic9600_02"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_02/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_02_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

imagenet/models/ic9600/4ximagenet_span_fp16_ic9600_02/models/net_g_100000.pth

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imagenet/models/ic9600/4ximagenet_span_fp16_ic9600_03/4ximagenet_span_fp16_ic9600_03.toml

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+# GENERATE TIME: Fri Oct 25 06:22:44 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_ic9600_03.toml
+
+name = "4ximagenet_span_fp16_ic9600_03"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_03/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_03_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

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imagenet/models/ic9600/4ximagenet_span_fp16_ic9600_04/4ximagenet_span_fp16_ic9600_04.toml

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+# GENERATE TIME: Fri Oct 25 08:04:03 2024
+# CMD:
+# train.py -opt options/span/4ximagenet_span_fp16_ic9600_04.toml
+
+name = "4ximagenet_span_fp16_ic9600_04"
+model_type = "image"
+scale = 4
+use_amp = true
+manual_seed = 1024
+
+[datasets.train]
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_04/'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/imagenet/ic9600_04_lr/'
+patch_size = 32
+batch_size = 16
+
+[datasets.val]
+name = "val"
+type = "paired"
+dataroot_gt = '/home/phips/Documents/Datasets/wip/testsets/Urban100/hr'
+dataroot_lq = '/home/phips/Documents/Datasets/wip/testsets/Urban100/lr_x4/'
+[val]
+val_freq = 10000
+save_img = false
+[val.metrics.psnr]
+type = "calculate_psnr"
+[val.metrics.ssim]
+type = "calculate_ssim"
+[val.metrics.dists]
+type = "calculate_dists"
+better = "lower"
+
+[path]
+
+[network_g]
+type = "span"
+
+[train]
+ema = 0.999
+
+[train.optim_g]
+type = "adamw"
+lr = 1e-4
+betas = [ 0.9, 0.99 ]
+weight_decay = 0
+
+[train.scheduler]
+type = "multisteplr"
+milestones = [ 50000 ]
+gamma = 0.5
+
+[train.pixel_opt]
+type = "L1Loss"
+loss_weight = 1.0
+reduction = "mean"
+
+[logger]
+total_iter = 100000
+save_checkpoint_freq = 10000
+use_tb_logger = true

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