[{'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_train(encoder_state, dec_cell, dec_embed_input, sequence_length, decoding_scope,\noutput_fn, keep_prob):\n"""\nCreate a decoding layer for training\n:param encoder_state: Encoder State\n:param dec_cell: Decoder RNN Cell\n:param dec_embed_input: Decoder embedded input\n:param sequence_length: Sequence Length\n:param decoding_scope: TenorFlow Variable Scope for decoding\n:param output_fn: Function to apply the output layer\n:param keep_prob: Dropout keep probability\n:return: Train Logits\n"""\ntrain_decoder_fn = tf.contrib.seq2seq.simple_decoder_fn_train(encoder_state)\ntrain_pred, _, _ = tf.contrib.seq2seq.dynamic_rnn_decoder(\ndec_cell, train_decoder_fn, dec_embed_input, sequence_length, scope=decoding_scope)\ntrain_logits =  output_fn(train_pred)\nreturn train_logits\n"""\nDON\'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE\n"""\ntests.test_decoding_layer_train(decoding_layer_train)'}, {'role': 'assistant', 'content': 'modelling'}]