code: def conv_params(fsize, nfm, stride=1, relu=True, batch_norm=True):
      return dict(
          fshape=(fsize, fsize, nfm),
          strides=stride,
          padding=(1 if fsize > 1 else 0),
          activation=(Rectlin() if relu else None),
          init=Kaiming(local=True),
          batch_norm=batch_norm,
      )
  
file_path: neon/examples/cifar10_msra/network.py
imports: from neon.initializers import Kaiming
  from neon.layers import Conv, Pooling, GeneralizedCost, Activation, Affine
  from neon.layers import MergeSum, SkipNode, BatchNorm
  from neon.models import Model
  from neon.transforms import Rectlin, Softmax, CrossEntropyMulti
label_desc: Use image node_id 1 for calling a global function with example usage: conv_params(fsize, nfm, stride, relu, batch_norm) and returns: dict