RCNN study notes - efficientnet source code analysis

Enterprise 2023-07-30 03:44:43 views: null 
/Users/zhangguowen/opt/anaconda3/envs/py37/bin/python "/Users/zhangguowen/Library/Mobile Documents/com~apple~CloudDocs/pythonProject2/PiLiBaLa_Code/Test9_efficientnet_v2/model.py"
EfficientNetV2(
  (stem): ConvBNAct(
    (conv): Conv2d(3, 24, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
    (bn): BatchNorm2d(24, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
    (act): SiLU()
  )
  (blocks): Sequential(
    (0): FusedMBConv(
      (project_conv): ConvBNAct(
        (conv): Conv2d(24, 24, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(24, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
    )
    (1): FusedMBConv(
      (project_conv): ConvBNAct(
        (conv): Conv2d(24, 24, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(24, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dropout): DropPath()
    )
    (2): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(24, 96, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(96, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
    )
    (3): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(48, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(192, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (4): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(48, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(192, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (5): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(48, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(192, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (6): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(48, 192, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
    )
    (7): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(64, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (8): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(64, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (9): FusedMBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(64, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (10): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=256, bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(256, 16, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(16, 256, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
    )
    (11): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512, bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(512, 32, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(32, 512, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (12): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512, bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(512, 32, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(32, 512, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (13): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512, bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(512, 32, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(32, 512, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (14): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512, bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(512, 32, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(32, 512, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (15): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512, bias=False)
        (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(512, 32, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(32, 512, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (16): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(768, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(768, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=768, bias=False)
        (bn): BatchNorm2d(768, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(768, 32, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(32, 768, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
    )
    (17): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (18): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (19): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (20): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (21): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (22): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (23): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (24): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (25): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(960, 960, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=960, bias=False)
        (bn): BatchNorm2d(960, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(960, 40, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(40, 960, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(960, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
    )
    (26): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (27): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (28): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (29): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (30): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (31): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (32): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (33): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (34): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (35): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (36): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (37): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (38): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
    (39): MBConv(
      (expand_conv): ConvBNAct(
        (conv): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (dwconv): ConvBNAct(
        (conv): Conv2d(1536, 1536, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1536, bias=False)
        (bn): BatchNorm2d(1536, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): SiLU()
      )
      (se): SqueezeExcite(
        (conv_reduce): Conv2d(1536, 64, kernel_size=(1, 1), stride=(1, 1))
        (act1): SiLU()
        (conv_expand): Conv2d(64, 1536, kernel_size=(1, 1), stride=(1, 1))
        (act2): Sigmoid()
      )
      (project_conv): ConvBNAct(
        (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
        (act): Identity()
      )
      (dropout): DropPath()
    )
  )
  (head): Sequential(
    (project_conv): ConvBNAct(
      (conv): Conv2d(256, 1280, kernel_size=(1, 1), stride=(1, 1), bias=False)
      (bn): BatchNorm2d(1280, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
      (act): SiLU()
    )
    (avgpool): AdaptiveAvgPool2d(output_size=1)
    (flatten): Flatten(start_dim=1, end_dim=-1)
    (dropout): Dropout(p=0.2, inplace=True)
    (classifier): Linear(in_features=1280, out_features=1000, bias=True)
  )
)

Process finished with exit code 0

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