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API Reference

private efficientnetfunction

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 size
    • s: kernel stride
    • e: expansion ratio
    • i: 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 channels
  • nclasses: number of output classes
  • max_width: maximum number of output channels before the fully connected classification blocks