class_docstr: DLA Basic
class_docstr_tok: ["DLA","Basic"]
code: def __init__(self, inplanes, planes, stride=1, dilation=1, **_):
      super(DlaBasic, self).__init__()
      self.conv1 = nn.Conv2d(
          inplanes,
          planes,
          kernel_size=3,
          stride=stride,
          padding=dilation,
          bias=False,
          dilation=dilation,
      )
      self.bn1 = nn.BatchNorm2d(planes)
      self.relu = nn.ReLU(inplace=True)
      self.conv2 = nn.Conv2d(
          planes,
          planes,
          kernel_size=3,
          stride=1,
          padding=dilation,
          bias=False,
          dilation=dilation,
      )
      self.bn2 = nn.BatchNorm2d(planes)
      self.stride = stride
  
imports: import math
  from typing import List, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 to create a new DlaBasic object from inherited base classes: nn with example: obj = DlaBasic(inplanes, planes, stride, dilation)