code: def __init__(
      self,
      pretrained=True,
      layers=[1, 2, 3, 4],
      activation: str = ACT_SILU,
      first_conv_stride_one: bool = False,
      drop_path_rate=0.1,
  ):
      from timm.models.efficientnet import tf_efficientnet_b3_ns
  
      act_layer = get_activation_block(activation)
      encoder = tf_efficientnet_b3_ns(
          pretrained=pretrained,
          features_only=True,
          act_layer=act_layer,
          drop_path_rate=drop_path_rate,
      )
      super().__init__(
          encoder,
          [24, 32, 48, 136, 384],
          layers=layers,
          first_conv_stride_one=first_conv_stride_one,
      )
  
imports: import math
  import warnings
  import torch
  from torch import nn
  from ..common import EncoderModule, _take
  from ...activations import ACT_SILU, get_activation_block
label_desc: Use image node_id 1 to create a new TimmB3Encoder object from inherited base classes: TimmBaseEfficientNetEncoder with example: obj = TimmB3Encoder(pretrained, layers, activation, first_conv_stride_one, drop_path_rate)