Open nashid opened 4 years ago
I trained the model with:
python -m nmt.nmt \ --attention=scaled_luong \ --src=vi --tgt=en \ --vocab_prefix=/tmp/data/token \ --train_prefix=/tmp/data/train \ --dev_prefix=/tmp/data/valid \ --test_prefix=/tmp/data/test \ --out_dir=/tmp/model-top-k \ --num_train_steps=10000 \ --steps_per_stats=100 \ --num_layers=2 \ --num_units=1024 \ --dropout=0.2 \ --metrics=bleu \ --optimizer=sgd \ --learning_rate=1.0 \ --start_decay_step=5000 \ --decay_steps=10 \ --encoder_type=bi \ --beam_width=10
Followed to that used the inference engine with the following:
python -m nmt.nmt \ --out_dir=./model \ --inference_input_file=./data/test.buggy.beam.search \ --inference_output_file=./data/testing-beam-search/model.output \ --beam_width=10 \ --num_translations_per_input=1
I see in the log:
decoder: infer_mode=greedybeam_width=10, length_penalty=0.000000, coverage_penalty=0.000000 ..... ..... ..... dynamic_seq2seq/decoder/attention/multi_rnn_cell/cell_3/basic_lstm_cell/bias:0, (512,), /device:GPU:0 dynamic_seq2seq/decoder/attention/luong_attention/attention_g:0, (), /device:GPU:0 dynamic_seq2seq/decoder/attention/attention_layer/kernel:0, (256, 128), /device:GPU:0 dynamic_seq2seq/decoder/output_projection/kernel:0, (128, 10003), loaded infer model parameters from ./code_model/translate.ckpt-20000, time 0.29s # Start decoding decoding to output ./data/testing-beam-search/model.output done, num sentences 1, num translations per input 1, time 0s, Thu Jun 11 21:20:29 2020.
However, only one prediction is generated. Any ideas?
I trained the model with:
Followed to that used the inference engine with the following:
I see in the log:
However, only one prediction is generated. Any ideas?