code: def convert_conv1d_tf_to_coreml(conv_weights):
      """
      Convolutional weights from TensorFlow in the format [kernelWidth, kernelChannels, outputChannels]
      are converted back in CoreML specifications [outputChannels, kernelChannels, kernelHeight, kernelWidth].
  
      Parameters
      ----------
      conv_weights: 3d numpy array of shape
         [kernelWidth, kernelChannels, outputChannels]
         since kernelHeight = 1 for conv1d
  
      Returns
      -------
      return: 4d numpy array of shape
         [outputChannels, kernelChannels, kernelHeight, kernelWidth]
  
      """
      conv_weights = np.expand_dims(conv_weights, axis=2)
      conv_weights = np.transpose(conv_weights, (3, 1, 2, 0))
      return conv_weights
  
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 7 for calling a global function with example usage: convert_conv1d_tf_to_coreml(conv_weights) and returns: conv_weights