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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def serialize_example(transformed_json_data, features, feature_indices, target_name):
 """Makes an instance of data in libsvm format. Args: transformed_json_data: dict of transformed data. features: features config. feature_indices: output of feature_transforms.get_transformed_feature_indices() Returns: The text line representation of an instance in libsvm format. """

  import six
  import tensorflow as tf
  from trainer import feature_transforms

  line = str(transformed_json_data[target_name][0])
  for name, info in feature_indices:
    if features[name]['transform'] in [feature_transforms.IDENTITY_TRANSFORM,
                                       feature_transforms.SCALE_TRANSFORM]:
      line += ' %d:%s' % (info['index_start'], str(transformed_json_data[name][0]))
    elif features[name]['transform'] in [feature_transforms.ONE_HOT_TRANSFORM,
                                         feature_transforms.MULTI_HOT_TRANSFORM]:
      for i in range(info['size']):
        if i in transformed_json_data[name]:
          line += ' %d:1' % (info['index_start'] + i)
    elif features[name]['transform'] in [feature_transforms.IMAGE_TRANSFORM]:
      for i in range(info['size']):
        line += ' %d:%s' % (info['index_start'] + i, str(transformed_json_data[name][i]))

  return line