code: def conv_block(
      data,
      name,
      channels,
      kernel_size=(3, 3),
      strides=(1, 1),
      padding=(1, 1),
      epsilon=1e-5,
      layout="NCHW",
  ):
      """Helper function to construct conv_bn-relu"""
      # convolution + bn + relu
      conv = layers.conv2d(
          data=data,
          channels=channels,
          kernel_size=kernel_size,
          strides=strides,
          padding=padding,
          data_layout=layout,
          kernel_layout=layers.conv_kernel_layout(layout),
          name=name + "_conv",
      )
      bn = layers.batch_norm_infer(
          data=conv, epsilon=epsilon, name=name + "_bn"
      )
      act = relay.nn.relu(data=bn)
      return act
  
imports: from tvm import relay
  from .None import layers
  from .init import create_workload
label_desc: Use image node_id 1 for calling a global function with example usage: conv_block(data, name, channels, kernel_size, strides, padding, epsilon, layout) and returns: act