zoo/mobilenet/mobilenet_v3_c.py
def group(self, x, **metaparameters):
        """ Construct an Attention Residual Group
            x         : input to the group
            blocks    : expansion per block
            strides   : whether first block uses strided convolution in project shortcut
        """   
        blocks  = metaparameters['blocks']
        strides   = metaparameters['strides']
        del metaparameters['strides']

        # In first block, the attention residual block maybe strided - feature map size reduction
        x = self.attention_block(x, strides=strides, expansion=blocks.pop(0), **metaparameters)
    
        # Remaining blocks
        for block in blocks:
            x = self.attention_block(x, strides=(1, 1), expansion=block, **metaparameters)
        return x
 Construct an Attention Residual Group
            x         : input to the group
            blocks    : expansion per block
            strides   : whether first block uses strided convolution in project shortcut
        
Construct an Attention Residual Group
x         : input to the group
blocks    : expansion per block
strides   : whether first block uses strided convolution in project shortcut
Construct an Attention Residual Group x : input to the group blocks : expansion per block strides : whether first block uses strided convolution in project shortcut
def group(self, x, **metaparameters):
        blocks  = metaparameters['blocks']
        strides   = metaparameters['strides']
        del metaparameters['strides']
        x = self.attention_block(x, strides=strides, expansion=blocks.pop(0), **metaparameters)
        for block in blocks:
            x = self.attention_block(x, strides=(1, 1), expansion=block, **metaparameters)
        return x
def group ( self , x , ** metaparameters ) : blocks = metaparameters [ 'blocks' ] strides = metaparameters [ 'strides' ] del metaparameters [ 'strides' ] x = self . attention_block ( x , strides = strides , expansion = blocks . pop ( 0 ) , ** metaparameters ) for block in blocks : x = self . attention_block ( x , strides = ( 1 , 1 ) , expansion = block , ** metaparameters ) return x
Construct an Attention Residual Group
x         : input to the group
blocks    : expansion per block
strides   : whether first block uses strided convolution in project shortcut
Construct an Attention Residual Group x : input to the group blocks : expansion per block strides : whether first block uses strided convolution in project shortcut
""" Construct an Attention Residual Group
            x         : input to the group
            blocks    : expansion per block
            strides   : whether first block uses strided convolution in project shortcut
        """ # In first block, the attention residual block maybe strided - feature map size reduction # Remaining blocks
self
x