class_docstr: Wrap the original efficientnet to an encoder for flexible-unet.
class_docstr_tok: ["Wrap","the","original","efficientnet","to","an","encoder","for","flexible-unet","."]
docstr: Get number of efficientnet backbone output feature maps' channel.
docstr_tok: ["Get","number","of","efficientnet","backbone","output","feature","maps","'","channel","."]
code: def num_channels_per_output(cls) -> list[tuple[int, ...]]:
      """
      Get number of efficientnet backbone output feature maps' channel.
      """
      return [
          (16, 24, 40, 112, 320),
          (16, 24, 40, 112, 320),
          (16, 24, 48, 120, 352),
          (24, 32, 48, 136, 384),
          (24, 32, 56, 160, 448),
          (24, 40, 64, 176, 512),
          (32, 40, 72, 200, 576),
          (32, 48, 80, 224, 640),
          (32, 56, 88, 248, 704),
          (72, 104, 176, 480, 1376),
      ]
  
imports: from __future__ import annotations
  import math
  import operator
  import re
  from functools import reduce
  from typing import NamedTuple
  import torch
  from torch import nn
  from torch.utils import model_zoo
  from monai.networks.blocks import BaseEncoder
  from monai.networks.layers.factories import Act, Conv, Pad, Pool
  from monai.networks.layers.utils import get_norm_layer
  from monai.utils.module import look_up_option
label_desc: Use image node_id 2 for calling the EfficientNetEncoder obj's underlying member method code with example usage: obj.num_channels_per_output(cls) and returns: list