class_docstr: Block of dropout->conv->batch_norm->relu6
code: def __init__(self, inputs, filter_count, name):
      self.dropout = neoml.Dnn.Dropout(
          inputs,
          rate=0.1,
          spatial=True,
          batchwise=True,
          name=name + "_dropout",
      )
      self.conv = neoml.Dnn.Conv(
          self.dropout,
          filter_count=filter_count,
          filter_size=(3, 3),
          stride_size=(2, 2),
          padding_size=(1, 1),
          name=name + "_conv",
      )
      self.bn = neoml.Dnn.BatchNormalization(
          self.conv, channel_based=True, name=name + "_bn"
      )
      self.output = neoml.Dnn.ReLU(
          self.bn, threshold=6.0, name=name + "_relu6"
      )
  
file_path: neoml/NeoML/samples/python/cifar10.py
imports: import neoml
  import numpy
  import os
  import time
  import tarfile
label_desc: Use image node_id 1 to create a new ConvBlock object  with example: obj = ConvBlock(inputs, filter_count, name)