[Feature] Add BigNAS algorithm

configs/_base_/nas_backbones/attentive_mobilenetv3_supernet.py

@@ -0,0 +1,53 @@
+# search space
+arch_setting = dict(
+    kernel_size=[  # [min_kernel_size, max_kernel_size, step]
+        [3, 5, 2],
+        [3, 5, 2],
+        [3, 5, 2],
+        [3, 5, 2],
+        [3, 5, 2],
+        [3, 5, 2],
+        [3, 5, 2],
+    ],
+    num_blocks=[  # [min_num_blocks, max_num_blocks, step]
+        [1, 2, 1],
+        [3, 5, 1],
+        [3, 6, 1],
+        [3, 6, 1],
+        [3, 8, 1],
+        [3, 8, 1],
+        [1, 2, 1],
+    ],
+    expand_ratio=[  # [min_expand_ratio, max_expand_ratio, step]
+        [1, 1, 1],
+        [4, 6, 1],
+        [4, 6, 1],
+        [4, 6, 1],
+        [4, 6, 1],
+        [6, 6, 1],
+        [6, 6, 1],
+        [6, 6, 1],  # last layer
+    ],
+    num_out_channels=[  # [min_channel, max_channel, step]
+        [16, 24, 8],  # first layer
+        [16, 24, 8],
+        [24, 32, 8],
+        [32, 40, 8],
+        [64, 72, 8],
+        [112, 128, 8],
+        [192, 216, 8],
+        [216, 224, 8],
+        [1792, 1984, 1984 - 1792],  # last layer
+    ])
+
+_INPUT_MUTABLE = dict(
+    input_resizer=dict(type='DynamicInputResizer'),
+    mutable_shape=dict(
+        type='OneShotMutableValue',
+        value_list=[[192, 192], [224, 224], [256, 256], [288, 288]],
+        default_value=[224, 224]))
+
+nas_backbone = dict(
+    type='AttentiveMobileNetV3',
+    arch_setting=arch_setting,
+    norm_cfg=dict(type='DynamicBatchNorm2d', momentum=0.0))

configs/_base_/nas_backbones/ofa_mobilenetv3_supernet.py

@@ -0,0 +1,48 @@
+# search space
+arch_setting = dict(
+    kernel_size=[  # [min_kernel_size, max_kernel_size, step]
+        [3, 3, 1],
+        [3, 7, 2],
+        [3, 7, 2],
+        [3, 7, 2],
+        [3, 7, 2],
+        [3, 7, 2],
+    ],
+    num_blocks=[  # [min_num_blocks, max_num_blocks, step]
+        [1, 1, 1],
+        [2, 4, 1],
+        [2, 4, 1],
+        [2, 4, 1],
+        [2, 4, 1],
+        [2, 4, 1],
+    ],
+    expand_ratio=[  # [min_expand_ratio, max_expand_ratio, step]
+        [1, 1, 1],
+        [3, 6, 1],
+        [3, 6, 1],
+        [3, 6, 1],
+        [3, 6, 1],
+        [3, 6, 1],
+        [6, 6, 1],  # last layer
+    ],
+    # [16, 16, 24, 40, 80, 112, 160, 960, 1280]
+    num_out_channels=[  # [min_channel, max_channel, step]
+        [16, 16, 8],  # first layer
+        [16, 16, 8],
+        [16, 24, 8],
+        [24, 40, 8],
+        [40, 80, 8],
+        [80, 112, 8],
+        [112, 160, 8],
+        [1024, 1280, 1280 - 1024],  # last layer
+    ])
+
+nas_backbone = dict(
+    type='mmrazor.AttentiveMobileNetV3',
+    arch_setting=arch_setting,
+    out_indices=(6, ),
+    stride_list=[1, 2, 2, 2, 1, 2],
+    with_se_list=[False, False, True, False, True, True],
+    conv_cfg=dict(type='OFAConv2d'),
+    norm_cfg=dict(type='mmrazor.DynamicBatchNorm2d', momentum=0.0),
+    with_attentive_shortcut=False)

configs/_base_/nas_backbones/spos_mobilenet_supernet.py

@@ -46,7 +46,7 @@
 
 arch_setting = [
     # Parameters to build layers. 3 parameters are needed to construct a
-    # layer, from left to right: channel, num_blocks, mutable_cfg.
+    # layer, from left to right: channel, num_blocks, stride, mutable_cfg.
     [24, 1, 1, _FIRST_MUTABLE],
     [32, 4, 2, _STAGE_MUTABLE],
     [56, 4, 2, _STAGE_MUTABLE],
@@ -58,7 +58,7 @@
 
 nas_backbone = dict(
     _scope_='mmrazor',
-    type='SearchableMobileNet',
+    type='SearchableMobileNetV2',
     first_channels=40,
     last_channels=1728,
     widen_factor=1.0,

configs/_base_/settings/imagenet_bs1024_spos.py

@@ -61,13 +61,13 @@
     bias_decay_mult=0.0, norm_decay_mult=0.0, dwconv_decay_mult=0.0)
 
 optim_wrapper = dict(
-    optimizer=dict(type='mmcls.SGD', lr=0.5, momentum=0.9, weight_decay=4e-5),
+    optimizer=dict(type='SGD', lr=0.5, momentum=0.9, weight_decay=4e-5),
     paramwise_cfg=paramwise_cfg,
     clip_grad=None)
 
 # leanring policy
 param_scheduler = dict(
-    type='mmcls.PolyLR',
+    type='PolyLR',
     power=1.0,
     eta_min=0.0,
     by_epoch=True,