code: def convert_dense_coreml_to_tf(dense_weights):
      """
      The Dense layer weights from CoreML are [C_out, C_in, 1, 1] and need to be
      converted to [C_in, C_out] for TensorFlow.
  
      Parameters
      ----------
      dense_weights: 4d numpy array of shape
         [outputChannels, inChannels, 1, 1]
  
      Returns
      -------
      return: 2d numpy array of shape
         [outputChannels, kernelChannels, kernelHeight, kernelWidth]
  
      """
      dense_weights = np.transpose(dense_weights, (1, 0, 2, 3))
      return np.reshape(
          dense_weights,
          (dense_weights.shape[0], dense_weights.shape[1]),
      )
  
file_path: turicreate/src/python/turicreate/toolkits/_tf_utils.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
  from turicreate._deps.minimal_package import _minimal_package_import_check
label_desc: Use image node_id 6 for calling a global function with example usage: convert_dense_coreml_to_tf(dense_weights) and returns: np