code: def BuildSmallModel():
      """Build a small forward conv model."""
      image = array_ops.zeros([2, 6, 6, 3])
      _ = variable_scope.get_variable(
          "ScalarW",
          [],
          dtypes.float32,
          initializer=init_ops.random_normal_initializer(stddev=0.001),
      )
      kernel = variable_scope.get_variable(
          "DW",
          [3, 3, 3, 6],
          dtypes.float32,
          initializer=init_ops.random_normal_initializer(stddev=0.001),
      )
      x = nn_ops.conv2d(image, kernel, [1, 2, 2, 1], padding="SAME")
      kernel = variable_scope.get_variable(
          "DW2",
          [2, 2, 6, 12],
          dtypes.float32,
          initializer=init_ops.random_normal_initializer(stddev=0.001),
      )
      x = nn_ops.conv2d(x, kernel, [1, 2, 2, 1], padding="SAME")
      return x
  
imports: import contextlib
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_grad
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import rnn
  from tensorflow.python.ops import rnn_cell
  from tensorflow.python.ops import tensor_array_grad
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.profiler import model_analyzer
  from tensorflow.python.training import gradient_descent
  from tensorflow.python.util import _pywrap_tfprof
  from tensorflow.python.util import compat
label_desc: Use image node_id 1 for calling a global function with example usage: BuildSmallModel() and returns: x