add ep800 ckpt

epoch_800.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ff99b4495a8f6d96bcfef0a38737792748a98353f2fb90edaef5d9508bee6e4a
+size 3404723238

mae_lama-base-p16_8xb512-amp-coslr-800e_in1k.py

@@ -0,0 +1,134 @@
+auto_scale_lr = dict(base_batch_size=4096)
+data_preprocessor = dict(
+    mean=[
+        123.675,
+        116.28,
+        103.53,
+    ],
+    non_blocking=True,
+    std=[
+        58.395,
+        57.12,
+        57.375,
+    ],
+    to_rgb=True,
+    type='SelfSupDataPreprocessor')
+data_root = '/workdir/ILSVRC2012/'
+dataset_type = 'ImageNet'
+default_hooks = dict(
+    checkpoint=dict(interval=1, max_keep_ckpts=3, type='CheckpointHook'),
+    logger=dict(interval=20, type='LoggerHook'),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    timer=dict(type='IterTimerHook'),
+    visualization=dict(enable=False, type='VisualizationHook'))
+default_scope = 'mmpretrain'
+env_cfg = dict(
+    cudnn_benchmark=True,
+    dist_cfg=dict(backend='nccl'),
+    mp_cfg=dict(mp_start_method='spawn', opencv_num_threads=0))
+launcher = 'pytorch'
+load_from = None
+log_level = 'INFO'
+model = dict(
+    backbone=dict(arch='b', mask_ratio=0.75, patch_size=16, type='MAELLaMA'),
+    head=dict(
+        loss=dict(criterion='L2', type='PixelReconstructionLoss'),
+        norm_pix=True,
+        patch_size=16,
+        type='MAEPretrainHead'),
+    init_cfg=[
+        dict(distribution='uniform', layer='Linear', type='Xavier'),
+        dict(bias=0.0, layer='LayerNorm', type='Constant', val=1.0),
+    ],
+    neck=dict(
+        decoder_depth=8,
+        decoder_embed_dim=512,
+        decoder_num_heads=16,
+        embed_dim=768,
+        in_chans=3,
+        mlp_ratio=4.0,
+        patch_size=16,
+        type='MAEPretrainDecoder'),
+    type='MAE')
+optim_wrapper = dict(
+    loss_scale='dynamic',
+    optimizer=dict(
+        betas=(
+            0.9,
+            0.95,
+        ), lr=0.0024, type='AdamW', weight_decay=0.05),
+    paramwise_cfg=dict(
+        custom_keys=dict(
+            bias=dict(decay_mult=0.0),
+            cls_token=dict(decay_mult=0.0),
+            ln=dict(decay_mult=0.0),
+            mask_token=dict(decay_mult=0.0),
+            pos_embed=dict(decay_mult=0.0))),
+    type='AmpOptimWrapper')
+param_scheduler = [
+    dict(
+        begin=0,
+        by_epoch=True,
+        convert_to_iter_based=True,
+        end=40,
+        start_factor=1e-09,
+        type='LinearLR'),
+    dict(
+        T_max=760,
+        begin=40,
+        by_epoch=True,
+        convert_to_iter_based=True,
+        end=800,
+        type='CosineAnnealingLR'),
+]
+randomness = dict(deterministic=False, diff_rank_seed=True, seed=0)
+resume = True
+train_cfg = dict(max_epochs=800, type='EpochBasedTrainLoop')
+train_dataloader = dict(
+    batch_size=512,
+    collate_fn=dict(type='default_collate'),
+    dataset=dict(
+        data_root='/workdir/ILSVRC2012/',
+        pipeline=[
+            dict(type='LoadImageFromFile'),
+            dict(
+                backend='pillow',
+                crop_ratio_range=(
+                    0.2,
+                    1.0,
+                ),
+                interpolation='bicubic',
+                scale=224,
+                type='RandomResizedCrop'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(type='PackInputs'),
+        ],
+        split='train',
+        type='ImageNet'),
+    num_workers=8,
+    persistent_workers=True,
+    pin_memory=True,
+    sampler=dict(shuffle=True, type='DefaultSampler'))
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        backend='pillow',
+        crop_ratio_range=(
+            0.2,
+            1.0,
+        ),
+        interpolation='bicubic',
+        scale=224,
+        type='RandomResizedCrop'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(type='PackInputs'),
+]
+vis_backends = [
+    dict(type='LocalVisBackend'),
+]
+visualizer = dict(
+    type='UniversalVisualizer', vis_backends=[
+        dict(type='LocalVisBackend'),
+    ])
+work_dir = './work_dirs/mae_lama-base-p16_8xb512-amp-coslr-800e_in1k'