class_docstr: This layers applies global pooling over a 4D or 5D input tensor
  
  Args:
      pool_type (Optional[str]): Pooling type. It can be mean, rms, or abs. Default: `mean`
      keep_dim (Optional[bool]): Do not squeeze the dimensions of a tensor. Default: `False`
  
  Shape:
      - Input: :math:`(N, C, H, W)` or :math:`(N, C, D, H, W)`
      - Output: :math:`(N, C, 1, 1)` or :math:`(N, C, 1, 1, 1)` if keep_dim else :math:`(N, C)`
class_docstr_tok: ["This","layers","applies","global","pooling","over","a","4D","or","5D","input","tensor","Args",":","pool_type","(","Optional","[","str","]",")",":","Pooling","type",".","It","can","be","mean",",","rms",",","or","abs",".","Default",":","`","mean","`","keep_dim","(","Optional","[","bool","]",")",":","Do","not","squeeze","the","dimensions","of","a","tensor",".","Default",":","`","False","`","Shape",":","-","Input",":",":","math",":","`","(","N",",","C",",","H",",","W",")","`","or",":","math",":","`","(","N",",","C",",","D",",","H",",","W",")","`","-","Output",":",":","math",":","`","(","N",",","C",",","1",",","1",")","`","or",":","math",":","`","(","N",",","C",",","1",",","1",",","1",")","`","if","keep_dim","else",":","math",":","`","(","N",",","C",")","`"]
code: def __repr__(self):
      return "{}(type={})".format(
          self.__class__.__name__, self.pool_type
      )
  
file_path: ml-cvnets/cvnets/layers/global_pool.py
imports: import argparse
  from typing import List, Optional
  import torch
  from torch import Tensor
  from cvnets.layers.base_layer import BaseLayer
  from utils import logger
label_desc: Use image node_id 5 for calling the GlobalPool obj's underlying member method code with example usage: obj.__repr__() and returns: str