code: def BuildFullModel():
      """Build the full model with conv,rnn,opt."""
      seq = []
      for i in range(4):
          with variable_scope.variable_scope("inp_%d" % i):
              seq.append(
                  array_ops.reshape(BuildSmallModel(), [2, 1, -1])
              )
  
      cell = rnn_cell.BasicRNNCell(16)
      out = rnn.dynamic_rnn(
          cell, array_ops.concat(seq, axis=1), dtype=dtypes.float32
      )[0]
  
      target = array_ops.ones_like(out)
      loss = nn_ops.l2_loss(math_ops.reduce_mean(target - out))
      sgd_op = gradient_descent.GradientDescentOptimizer(1e-2)
      return sgd_op.minimize(loss)
  
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 2 for calling a global function with example usage: BuildFullModel() and returns: sgd_op