create_bert_model_definition_yaml.py

template="""
input_features:
    -
        name: tokens
        type: text
        encoder: bert
        config_path: uncased_L-12_H-768_A-12/bert_config.json
        checkpoint_path: uncased_L-12_H-768_A-12/bert_model.ckpt
        reduce_output: null
        preprocessing:
          word_tokenizer: bert
          word_vocab_file: uncased_L-12_H-768_A-12/vocab.txt
          padding_symbol: '[PAD]'
          unknown_symbol: '[UNK]'

output_features:
    -
        name: intent
        type: category
        reduce_input: sum
        num_fc_layers: 1
        fc_size: 64
    -
        name: slots
        type: sequence
        decoder: tagger

text:
        word_sequence_length_limit: 128
training:
        batch_size: 32
        learning_rate: 0.00002
"""

with open("model_definition.yaml", "w") as f:
  f.write(template)