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clip_large_pretrain_4x256_IF_lr1e-4/20230606_050006/vis_data/config.py

@@ -0,0 +1,251 @@
+optim_wrapper = dict(
+    optimizer=dict(
+        type='AdamW', lr=0.0001, weight_decay=0.3, _scope_='mmpretrain'),
+    paramwise_cfg=dict(
+        custom_keys=dict({
+            '.cls_token': dict(decay_mult=0.0),
+            '.pos_embed': dict(decay_mult=0.0)
+        })),
+    type='AmpOptimWrapper',
+    dtype='bfloat16',
+    clip_grad=None)
+param_scheduler = [
+    dict(type='CosineAnnealingLR', eta_min=1e-05, by_epoch=False, begin=0)
+]
+train_cfg = dict(by_epoch=True, max_epochs=10, val_interval=1)
+val_cfg = dict()
+test_cfg = dict()
+auto_scale_lr = dict(base_batch_size=4096)
+model = dict(
+    type='ImageClassifier',
+    backbone=dict(
+        frozen_stages=24,
+        type='VisionTransformer',
+        arch='l',
+        img_size=224,
+        patch_size=14,
+        drop_rate=0.1,
+        pre_norm=True,
+        final_norm=False,
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='ckpt/openclip-ViT-L-14.pth',
+            prefix='backbone')),
+    neck=dict(
+        type='CLIPProjection',
+        in_channels=1024,
+        out_channels=768,
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='ckpt/openclip-ViT-L-14.pth',
+            prefix='backbone')),
+    head=dict(
+        type='LinearClsHead',
+        num_classes=2,
+        in_channels=768,
+        loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
+        init_cfg=None),
+    init_cfg=dict(
+        type='TruncNormal', layer=['Conv2d', 'Linear'], std=0.02, bias=0.0),
+    train_cfg=None)
+dataset_type = 'CustomDataset'
+data_preprocessor = dict(
+    num_classes=2,
+    mean=[123.675, 116.28, 103.53],
+    std=[58.395, 57.12, 57.375],
+    to_rgb=True)
+bgr_mean = [103.53, 116.28, 123.675]
+bgr_std = [57.375, 57.12, 58.395]
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='RandomResizedCrop',
+        scale=224,
+        backend='pillow',
+        interpolation='bicubic'),
+    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+    dict(type='PackInputs')
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='ResizeEdge',
+        scale=256,
+        edge='short',
+        backend='pillow',
+        interpolation='bicubic'),
+    dict(type='CenterCrop', crop_size=224),
+    dict(type='PackInputs')
+]
+train_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/IF80w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/if-dpmsolver++-50-20w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/cc1m.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=True))
+val_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/if-dpmsolver++-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/cc1w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=False))
+val_evaluator = [
+    dict(type='Accuracy', topk=1),
+    dict(type='SingleLabelMetric', average=None)
+]
+test_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/if-dpmsolver++-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/cc1w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=False))
+test_evaluator = [
+    dict(type='Accuracy', topk=1),
+    dict(type='SingleLabelMetric', average=None)
+]
+custom_hooks = [dict(type='EMAHook', momentum=0.0001, priority='ABOVE_NORMAL')]
+default_scope = 'mmpretrain'
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=100),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', interval=1),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='VisualizationHook', enable=True))
+env_cfg = dict(
+    cudnn_benchmark=True,
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
+    dist_cfg=dict(backend='nccl'))
+vis_backends = [dict(type='LocalVisBackend')]
+visualizer = dict(
+    type='UniversalVisualizer',
+    vis_backends=[
+        dict(type='LocalVisBackend'),
+        dict(type='TensorboardVisBackend')
+    ])
+log_level = 'INFO'
+load_from = None
+resume = False
+randomness = dict(seed=None, deterministic=False)
+launcher = 'slurm'
+work_dir = 'workdir/clip_large_pretrain_4x256_IF_lr1e-4'

clip_large_pretrain_4x256_IF_lr1e-4/20230606_050006/vis_data/events.out.tfevents.1685998820.SH-IDC1-10-140-24-119.202894.0

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+size 1930259

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clip_large_pretrain_4x256_IF_lr1e-4/clip_large_pretrain_4x256_IF_lr1e-4.py

@@ -0,0 +1,251 @@
+optim_wrapper = dict(
+    optimizer=dict(
+        type='AdamW', lr=0.0001, weight_decay=0.3, _scope_='mmpretrain'),
+    paramwise_cfg=dict(
+        custom_keys=dict({
+            '.cls_token': dict(decay_mult=0.0),
+            '.pos_embed': dict(decay_mult=0.0)
+        })),
+    type='AmpOptimWrapper',
+    dtype='bfloat16',
+    clip_grad=None)
+param_scheduler = [
+    dict(type='CosineAnnealingLR', eta_min=1e-05, by_epoch=False, begin=0)
+]
+train_cfg = dict(by_epoch=True, max_epochs=10, val_interval=1)
+val_cfg = dict()
+test_cfg = dict()
+auto_scale_lr = dict(base_batch_size=4096)
+model = dict(
+    type='ImageClassifier',
+    backbone=dict(
+        frozen_stages=24,
+        type='VisionTransformer',
+        arch='l',
+        img_size=224,
+        patch_size=14,
+        drop_rate=0.1,
+        pre_norm=True,
+        final_norm=False,
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='ckpt/openclip-ViT-L-14.pth',
+            prefix='backbone')),
+    neck=dict(
+        type='CLIPProjection',
+        in_channels=1024,
+        out_channels=768,
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='ckpt/openclip-ViT-L-14.pth',
+            prefix='backbone')),
+    head=dict(
+        type='LinearClsHead',
+        num_classes=2,
+        in_channels=768,
+        loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
+        init_cfg=None),
+    init_cfg=dict(
+        type='TruncNormal', layer=['Conv2d', 'Linear'], std=0.02, bias=0.0),
+    train_cfg=None)
+dataset_type = 'CustomDataset'
+data_preprocessor = dict(
+    num_classes=2,
+    mean=[123.675, 116.28, 103.53],
+    std=[58.395, 57.12, 57.375],
+    to_rgb=True)
+bgr_mean = [103.53, 116.28, 123.675]
+bgr_std = [57.375, 57.12, 58.395]
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='RandomResizedCrop',
+        scale=224,
+        backend='pillow',
+        interpolation='bicubic'),
+    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+    dict(type='PackInputs')
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='ResizeEdge',
+        scale=256,
+        edge='short',
+        backend='pillow',
+        interpolation='bicubic'),
+    dict(type='CenterCrop', crop_size=224),
+    dict(type='PackInputs')
+]
+train_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/IF80w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/if-dpmsolver++-50-20w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/cc1m.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=True))
+val_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/if-dpmsolver++-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/cc1w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=False))
+val_evaluator = [
+    dict(type='Accuracy', topk=1),
+    dict(type='SingleLabelMetric', average=None)
+]
+test_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/if-dpmsolver++-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/cc1w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=False))
+test_evaluator = [
+    dict(type='Accuracy', topk=1),
+    dict(type='SingleLabelMetric', average=None)
+]
+custom_hooks = [dict(type='EMAHook', momentum=0.0001, priority='ABOVE_NORMAL')]
+default_scope = 'mmpretrain'
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=100),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', interval=1),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='VisualizationHook', enable=True))
+env_cfg = dict(
+    cudnn_benchmark=True,
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
+    dist_cfg=dict(backend='nccl'))
+vis_backends = [dict(type='LocalVisBackend')]
+visualizer = dict(
+    type='UniversalVisualizer',
+    vis_backends=[
+        dict(type='LocalVisBackend'),
+        dict(type='TensorboardVisBackend')
+    ])
+log_level = 'INFO'
+load_from = None
+resume = False
+randomness = dict(seed=None, deterministic=False)
+launcher = 'slurm'
+work_dir = 'workdir/clip_large_pretrain_4x256_IF_lr1e-4'

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clip_large_pretrain_4x256_IF_lr1e-4/last_checkpoint

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clip_large_pretrain_4x256_all2_lr1e-4/20230606_005614/vis_data/20230606_005614.json

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+{"lr": 1.0001147030762536e-05, "data_time": 0.0014252185821533204, "loss": 0.4472906470298767, "time": 0.634446668624878, "epoch": 10, "memory": 44140, "step": 40828}
+{"accuracy/top1": 84.35033416748047, "data_time": 0.017048033078511556, "time": 1.2856839835643767, "step": 10}

clip_large_pretrain_4x256_all2_lr1e-4/20230606_005614/vis_data/config.py

@@ -0,0 +1,341 @@
+optim_wrapper = dict(
+    optimizer=dict(
+        type='AdamW', lr=0.0001, weight_decay=0.3, _scope_='mmpretrain'),
+    paramwise_cfg=dict(
+        custom_keys=dict({
+            '.cls_token': dict(decay_mult=0.0),
+            '.pos_embed': dict(decay_mult=0.0)
+        })),
+    type='AmpOptimWrapper',
+    dtype='bfloat16',
+    clip_grad=None)
+param_scheduler = [
+    dict(type='CosineAnnealingLR', eta_min=1e-05, by_epoch=False, begin=0)
+]
+train_cfg = dict(by_epoch=True, max_epochs=10, val_interval=1)
+val_cfg = dict()
+test_cfg = dict()
+auto_scale_lr = dict(base_batch_size=4096)
+model = dict(
+    type='ImageClassifier',
+    backbone=dict(
+        frozen_stages=24,
+        type='VisionTransformer',
+        arch='l',
+        img_size=224,
+        patch_size=14,
+        drop_rate=0.1,
+        pre_norm=True,
+        final_norm=False,
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='ckpt/openclip-ViT-L-14.pth',
+            prefix='backbone')),
+    neck=dict(
+        type='CLIPProjection',
+        in_channels=1024,
+        out_channels=768,
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='ckpt/openclip-ViT-L-14.pth',
+            prefix='backbone')),
+    head=dict(
+        type='LinearClsHead',
+        num_classes=2,
+        in_channels=768,
+        loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
+        init_cfg=None),
+    init_cfg=dict(
+        type='TruncNormal', layer=['Conv2d', 'Linear'], std=0.02, bias=0.0),
+    train_cfg=None)
+dataset_type = 'CustomDataset'
+data_preprocessor = dict(
+    num_classes=2,
+    mean=[123.675, 116.28, 103.53],
+    std=[58.395, 57.12, 57.375],
+    to_rgb=True)
+bgr_mean = [103.53, 116.28, 123.675]
+bgr_std = [57.375, 57.12, 58.395]
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='RandomResizedCrop',
+        scale=224,
+        backend='pillow',
+        interpolation='bicubic'),
+    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+    dict(type='PackInputs')
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='ResizeEdge',
+        scale=256,
+        edge='short',
+        backend='pillow',
+        interpolation='bicubic'),
+    dict(type='CenterCrop', crop_size=224),
+    dict(type='PackInputs')
+]
+train_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/all_0.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/all_1.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3fake8w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/cc1m.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3real8w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=True))
+val_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/stablediffusionV2-1-dpmsolver-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/stablediffusionV1-5R2-dpmsolver-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/if-dpmsolver++-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/cc1w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=False))
+val_evaluator = [
+    dict(type='Accuracy', topk=1),
+    dict(type='SingleLabelMetric', average=None)
+]
+test_dataloader = dict(
+    pin_memory=True,
+    persistent_workers=True,
+    collate_fn=dict(type='default_collate'),
+    batch_size=128,
+    num_workers=10,
+    dataset=dict(
+        type='ConcatDataset',
+        datasets=[
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/stablediffusionV2-1-dpmsolver-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/stablediffusionV1-5R2-dpmsolver-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/if-dpmsolver++-25-1w.tsv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ]),
+            dict(
+                type='CustomDataset',
+                data_root='',
+                ann_file=
+                '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/val/cc1w.csv',
+                pipeline=[
+                    dict(type='LoadImageFromFile'),
+                    dict(
+                        type='RandomResizedCrop',
+                        scale=224,
+                        backend='pillow',
+                        interpolation='bicubic'),
+                    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
+                    dict(type='PackInputs')
+                ])
+        ]),
+    sampler=dict(type='DefaultSampler', shuffle=False))
+test_evaluator = [
+    dict(type='Accuracy', topk=1),
+    dict(type='SingleLabelMetric', average=None)
+]
+custom_hooks = [dict(type='EMAHook', momentum=0.0001, priority='ABOVE_NORMAL')]
+default_scope = 'mmpretrain'
+default_hooks = dict(
+    timer=dict(type='IterTimerHook'),
+    logger=dict(type='LoggerHook', interval=100),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    checkpoint=dict(type='CheckpointHook', interval=1),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    visualization=dict(type='VisualizationHook', enable=True))
+env_cfg = dict(
+    cudnn_benchmark=True,
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
+    dist_cfg=dict(backend='nccl'))
+vis_backends = [dict(type='LocalVisBackend')]
+visualizer = dict(
+    type='UniversalVisualizer',
+    vis_backends=[
+        dict(type='LocalVisBackend'),
+        dict(type='TensorboardVisBackend')
+    ])
+log_level = 'INFO'
+load_from = None
+resume = False
+randomness = dict(seed=None, deterministic=False)
+launcher = 'slurm'
+work_dir = 'workdir/clip_large_pretrain_4x256_all2_lr1e-4'

clip_large_pretrain_4x256_all2_lr1e-4/20230606_005614/vis_data/events.out.tfevents.1685984187.SH-IDC1-10-140-24-114.130857.0

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+oid sha256:7611490e0714f9acc8d9118a294eef07c8ca6aff260ef41ffd6f3d0ee56ba018
+size 3137033

clip_large_pretrain_4x256_all2_lr1e-4/20230606_005614/vis_data/scalars.json

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