[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:def decoding_layer_infer(encoder_state, dec_cell, dec_embeddings, start_of_sequence_id, end_of_sequence_id,\nmaximum_length, vocab_size, decoding_scope, output_fn, keep_prob):\n"""\nCreate a decoding layer for inference\n:param encoder_state: Encoder state\n:param dec_cell: Decoder RNN Cell\n:param dec_embeddings: Decoder embeddings\n:param start_of_sequence_id: GO ID\n:param end_of_sequence_id: EOS Id\n:param maximum_length: Maximum length of\n:param vocab_size: Size of vocabulary\n:param decoding_scope: TensorFlow Variable Scope for decoding\n:param output_fn: Function to apply the output layer\n:param keep_prob: Dropout keep probability\n:return: Inference Logits\n"""\ninfer_decoder_fn = tf.contrib.seq2seq.simple_decoder_fn_inference(\noutput_fn, encoder_state, dec_embeddings, start_of_sequence_id, end_of_sequence_id,\nmaximum_length, vocab_size)\ninference_logits, _, _ = tf.contrib.seq2seq.dynamic_rnn_decoder(dec_cell, infer_decoder_fn, scope=decoding_scope)\nreturn inference_logits\n"""\nDON\'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE\n"""\ntests.test_decoding_layer_infer(decoding_layer_infer)'}, {'role': 'assistant', 'content': 'modelling'}]