def preprocess_fn()

in text-semantic-search/embeddings_extraction/etl/pipeline.py [0:0]

• 8 lines of code
• 1 McCabe index (conditional complexity)

def preprocess_fn(input_features):
  import tensorflow_transform as tft
  embedding = tft.apply_function(embed_text, input_features['text'])
  output_features = {
    'id': input_features['id'],
    'embedding': embedding
  }
  return output_features