code: def tf_linear_sum_assignment(cost_matrix):
      return tf.numpy_function(
          func=linear_sum_assignment,
          inp=[cost_matrix],
          Tout=[tf.int64, tf.int64],
      )
  
imports: import math
  import functools
  import tensorflow
  from tensorflow_addons.text.crf import crf_log_likelihood
  from scipy.optimize import linear_sum_assignment
  from finetune.base_models.gpt.featurizer import attn, dropout, norm
  from finetune.util.shapes import shape_list, merge_leading_dims
  from finetune.optimizers.recompute_grads import recompute_grad
  from finetune.errors import FinetuneError
  from finetune.nn.activations import act_fns
  from finetune.nn.nn_utils import norm
  from finetune.nn.target_blocks import sequence_labeler
  from tensorflow.python.framework import function
  from finetune.nn.target_blocks import class_reweighted_grad
  from finetune.base_models.bert.modeling import attention_layer, dropout, create_initializer, layer_norm, gelu
label_desc: Use image node_id 5 for calling a global function with example usage: tf_linear_sum_assignment(cost_matrix) and returns: tf