private
efficientnet
— function
efficientnet(scalings, block_config;
inchannels = 3, nclasses = 1000, max_width = 1280)
Create an EfficientNet model (reference).
Arguments
scalings
: global width and depth scaling (given as a tuple)block_config
: configuration for each inverted residual block, given as a vector of tuples with elements:n
: number of block repetitions (will be scaled by global depth scaling)k
: kernel sizes
: kernel stridee
: expansion ratioi
: block input channels (will be scaled by global width scaling)o
: block output channels (will be scaled by global width scaling)
inchannels
: number of input channelsnclasses
: number of output classesmax_width
: maximum number of output channels before the fully connected classification blocks