Created
February 5, 2019 07:16
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| ###Decoding Training Set | |
| def decode_training_set(encoder_state,decoder_cell,decoder_embedded_input,sequence_length,decoding_scope,output_function,keep_prob,batch_size): | |
| attention_states=tf_zeros([batch_size,1,decoder_cell.output_size]) | |
| attention_keys,attention_values,attention_score_function,attention_construct_function=tf.contrib.seq2seq.prepare_attention(attention_states, | |
| attention_option="bahdanau", | |
| num_units=decoder_cell.output_size) | |
| training_decoder_function=tf.contrib.seq2seq.attention_decoder_fn_train(encoder_state[0], | |
| attention_keys, | |
| attention_values, | |
| attention_score_function, | |
| attention_construct_function, | |
| name="attn_dec_train") | |
| decoder_ouput,_,_=tf.contrib.seq2seq.dynamic_rnn_decoder(decoder_cell, | |
| training_decoder_function, | |
| decoder_embedded_input, | |
| sequence_length, | |
| scope=decoding_scope) | |
| decoder_output_dropout=tf.nn.dropout(decoder_output,keep_prob) | |
| return output_function(decoder_output_dropout) |
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