class_docstr: Implementation of `PVTv2: Improved Baselines with Pyramid Vision
  Transformer <https://arxiv.org/pdf/2106.13797.pdf>`_.
class_docstr_tok: ["Implementation","of","`","PVTv2",":","Improved","Baselines","with","Pyramid","Vision","Transformer","<","https",":","\/\/arxiv.org\/pdf\/2106.13797.pdf",">","`","_","."]
code: def __init__(self, **kwargs):
      super(PyramidVisionTransformerV2, self).__init__(
          patch_sizes=[7, 3, 3, 3],
          paddings=[3, 1, 1, 1],
          use_abs_pos_embed=False,
          norm_after_stage=True,
          use_conv_ffn=True,
          **kwargs,
      )
  
imports: import math
  import warnings
  from collections import OrderedDict
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import Conv2d, build_activation_layer, build_norm_layer
  from mmcv.cnn.bricks.drop import build_dropout
  from mmcv.cnn.bricks.transformer import MultiheadAttention
  from mmengine.logging import MMLogger
  from mmengine.model import BaseModule, ModuleList, Sequential, constant_init, normal_init, trunc_normal_init
  from mmengine.model.weight_init import trunc_normal_
  from mmengine.runner.checkpoint import CheckpointLoader, load_state_dict
  from torch.nn.modules.utils import _pair
  from mmdet.registry import MODELS
  from ..layers import PatchEmbed, nchw_to_nlc, nlc_to_nchw
label_desc: Use image node_id 1 to create a new PyramidVisionTransformerV2 object from inherited base classes: PyramidVisionTransformer with example: obj = PyramidVisionTransformerV2()