code: def pearson_correlation_coefficient(
      predictions, labels, weights_fn=None
  ):
      """Calculate pearson correlation coefficient.
  
      Args:
        predictions: The raw predictions.
        labels: The actual labels.
        weights_fn: Weighting function.
  
      Returns:
        The pearson correlation coefficient.
      """
      del weights_fn
      _, pearson = contrib.metrics().streaming_pearson_correlation(
          predictions, labels
      )
      return pearson, tf.constant(1.0)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import six
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import bleu_hook
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import rouge
  from tensor2tensor.utils import sari_hook
  import tensorflow.compat.v1
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 37 for calling a global function with example usage: pearson_correlation_coefficient(predictions, labels, weights_fn) and returns: pearson,  tf