code: def test_print_summary():
      data = mx.sym.Variable("data")
      bias = mx.sym.Variable("fc1_bias", lr_mult=1.0)
      emb1 = mx.symbol.Embedding(
          data=data, name="emb1", input_dim=100, output_dim=28
      )
      conv1 = mx.symbol.Convolution(
          data=emb1,
          name="conv1",
          num_filter=32,
          kernel=(3, 3),
          stride=(2, 2),
      )
      bn1 = mx.symbol.BatchNorm(data=conv1, name="bn1")
      act1 = mx.symbol.Activation(
          data=bn1, name="relu1", act_type="relu"
      )
      mp1 = mx.symbol.Pooling(
          data=act1,
          name="mp1",
          kernel=(2, 2),
          stride=(2, 2),
          pool_type="max",
      )
      fc1 = mx.sym.FullyConnected(
          data=mp1, bias=bias, name="fc1", num_hidden=10, lr_mult=0
      )
      fc2 = mx.sym.FullyConnected(
          data=fc1, name="fc2", num_hidden=10, wd_mult=0.5
      )
      sc1 = mx.symbol.SliceChannel(
          data=fc2, num_outputs=10, name="slice_1", squeeze_axis=0
      )
      mx.viz.print_summary(sc1)
      shape = {}
      shape["data"] = (1, 3, 28)
      mx.viz.print_summary(sc1, shape)
  
imports: import warnings
  import mxnet
  import numpy
  import pytest
label_desc: Use image node_id 1 for calling a global function with example usage: test_print_summary() without return types