class_docstr: Bottleneck Block from `"Aggregated Residual Transformations for Deep Neural Networks"
  <http://arxiv.org/abs/1611.05431>`_ paper.
  
  Parameters
  ----------
  cardinality: int
      Number of groups
  bottleneck_width: int
      Width of bottleneck block
  stride : int
      Stride size.
  downsample : bool, default False
      Whether to downsample the input.
  norm_layer : object
      Normalization layer used (default: :class:`mxnet.gluon.nn.BatchNorm`)
      Can be :class:`mxnet.gluon.nn.BatchNorm` or :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
  norm_kwargs : dict
      Additional `norm_layer` arguments, for example `num_devices=4`
      for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
class_docstr_tok: ["Bottleneck","Block","from","`","``","Aggregated","Residual","Transformations","for","Deep","Neural","Networks","''","<","http",":","\/\/arxiv.org\/abs\/1611.05431",">","`","_","paper",".","Parameters","--","--","--","--","--","cardinality",":","int","Number","of","groups","bottleneck_width",":","int","Width","of","bottleneck","block","stride",":","int","Stride","size",".","downsample",":","bool",",","default","False","Whether","to","downsample","the","input",".","norm_layer",":","object","Normalization","layer","used","(","default",":",":","class",":","`","mxnet.gluon.nn.BatchNorm","`",")","Can","be",":","class",":","`","mxnet.gluon.nn.BatchNorm","`","or",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`",".","norm_kwargs",":","dict","Additional","`","norm_layer","`","arguments",",","for","example","`","num_devices=4","`","for",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`","."]
docstr: Hybrid forward
docstr_tok: ["Hybrid","forward"]
code: def hybrid_forward(self, F, x):
      """Hybrid forward"""
      residual = x
  
      x = self.body(x)
  
      if self.downsample:
          residual = self.downsample(residual)
  
      x = F.Activation(residual + x, act_type="relu")
  
      return x
  
file_path: gluon-cv/gluoncv/model_zoo/cifarresnext.py
imports: from __future__ import division
  import os
  import math
  from mxnet import cpu
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
  from mxnet.gluon.block import HybridBlock
label_desc: Use image node_id 2 for calling the CIFARBlock obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: x