code: def generate_params_inputs_targets(num_examples=1000):
      params = (
          tf_np.asarray(tf.constant(5.0)),
          tf_np.asarray(tf.constant(0.0)),
      )
  
      params_true = (
          tf_np.asarray(tf.constant(3.0)),
          tf_np.asarray(tf.constant(2.0)),
      )
  
      inputs = tf_np.asarray(tf.random.normal(shape=[num_examples]))
      noise = tf_np.asarray(tf.random.normal(shape=[num_examples]))
      targets = inputs * params_true[0] + params_true[1] + noise
  
      return params, params_true, inputs, targets
  
imports: import functools
  import itertools
  from absl import flags
  from absl.testing import parameterized
  from jax import lax
  import numpy
  import tensorflow.compat.v2
  from trax.tf_numpy import extensions
  import trax.tf_numpy.numpy
label_desc: Use image node_id 1 for calling a global function with example usage: generate_params_inputs_targets(num_examples) and returns: params,  params_true,  inputs,  targets