[Feature]: Add SimMIM 192 pt 224 ft

configs/benchmarks/classification/imagenet/swin-base_ft-8xb256-coslr-100e_in1k-224.py

@@ -0,0 +1,34 @@
+_base_ = 'swin-base_ft-8xb256-coslr-100e_in1k.py'
+
+# model
+model = dict(
+    backbone=dict(
+        img_size=224, stage_cfgs=dict(block_cfgs=dict(window_size=7))))
+
+# dataset
+img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
+train_pipeline = [
+    dict(
+        type='RandomAug',
+        input_size=224,
+        color_jitter=0.4,
+        auto_augment='rand-m9-mstd0.5-inc1',
+        interpolation='bicubic',
+        re_prob=0.25,
+        re_mode='pixel',
+        re_count=1,
+        mean=(0.485, 0.456, 0.406),
+        std=(0.229, 0.224, 0.225))
+]
+test_pipeline = [
+    dict(type='Resize', size=256, interpolation=3),
+    dict(type='CenterCrop', size=224),
+    dict(type='ToTensor'),
+    dict(type='Normalize', **img_norm_cfg)
+]
+data = dict(
+    samples_per_gpu=256,
+    drop_last=False,
+    workers_per_gpu=32,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline))