Apply the attention mask in all decoding steps (LM inference) #1304
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| name: Lint & Tests | |
| on: [push, pull_request] | |
| jobs: | |
| lint-and-tests: | |
| runs-on: ubuntu-latest | |
| strategy: | |
| matrix: | |
| python-version: [3.8] # build only for 3.8 for now | |
| steps: | |
| - uses: actions/checkout@v2 | |
| - name: Set up Python ${{ matrix.python-version }} | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| - name: Install dependencies | |
| run: | | |
| python -m pip install --upgrade pip | |
| pip install --upgrade setuptools | |
| pip install -e . | |
| pip install -r requirements.opt.txt | |
| pip install sacrebleu | |
| pip install flake8 | |
| python -m pip install black==22.* flake8==3.8.* | |
| if [ -f requirements.txt ]; then pip install -r requirements.txt; fi | |
| - name: Check code with Black | |
| run: | | |
| black --check . | |
| - name: Lint with flake8 | |
| run: | | |
| flake8 . | |
| - name: Unit tests | |
| run: | | |
| python -m unittest discover | |
| - name: Test vocabulary build | |
| run: | | |
| python onmt/bin/build_vocab.py \ | |
| -config data/data.yaml \ | |
| -save_data /tmp/onmt \ | |
| -n_sample 5000 \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| && rm -rf /tmp/sample | |
| - name: Test vocabulary build with features | |
| run: | | |
| python onmt/bin/build_vocab.py \ | |
| -config data/features_data.yaml \ | |
| -save_data /tmp/onmt_feat \ | |
| -src_vocab /tmp/onmt_feat.vocab.src \ | |
| -tgt_vocab /tmp/onmt_feat.vocab.tgt \ | |
| -n_sample -1 \ | |
| && rm -rf /tmp/sample | |
| - name: Test field/transform dump | |
| run: | | |
| # The dumped fields are used later when testing tools | |
| python train.py \ | |
| -config data/data.yaml \ | |
| -save_data /tmp/onmt.train.check \ | |
| -dump_fields \ | |
| -dump_transforms \ | |
| -n_sample 30 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 | |
| - name: Test RNN training | |
| run: | | |
| python train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -hidden_size 2 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -batch_size 10 \ | |
| -word_vec_size 5 \ | |
| -report_every 5\ | |
| -hidden_size 10 \ | |
| -train_steps 10 \ | |
| -tensorboard "true" \ | |
| -tensorboard_log_dir /tmp/logs_train | |
| python onmt/tests/test_events.py --logdir /tmp/logs_train -tensorboard_checks train | |
| - name: Test RNN training and validation with copy | |
| run: | | |
| python train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -hidden_size 2 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -batch_size 10 \ | |
| -word_vec_size 5 \ | |
| -report_every 5 \ | |
| -hidden_size 10 \ | |
| -train_steps 10 -valid_steps 5 \ | |
| -tensorboard "true" \ | |
| -tensorboard_log_dir /tmp/logs_train_and_valid \ | |
| -copy_attn | |
| python onmt/tests/test_events.py --logdir /tmp/logs_train_and_valid -tensorboard_checks train | |
| python onmt/tests/test_events.py --logdir /tmp/logs_train_and_valid -tensorboard_checks valid | |
| - name: Test RNN training with coverage | |
| run: | | |
| python train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -hidden_size 2 -batch_size 10 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -word_vec_size 5 -report_every 5 \ | |
| -coverage_attn true -lambda_coverage 0.1 \ | |
| -hidden_size 10 -train_steps 10 | |
| - name: Test Transformer training with align | |
| run: | | |
| python train.py \ | |
| -config data/align_data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -encoder_type transformer \ | |
| -decoder_type transformer \ | |
| -layers 4 \ | |
| -word_vec_size 16 \ | |
| -hidden_size 16 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -heads 2 \ | |
| -transformer_ff 64 \ | |
| -lambda_align 0.05 \ | |
| -alignment_layer 2 \ | |
| -alignment_heads 0 \ | |
| -dropout_steps 0 3 7 \ | |
| -dropout 0.3 0.2 0.1 \ | |
| -attention_dropout 0.2 0.1 0.1 \ | |
| -report_every 5 \ | |
| -train_steps 10 | |
| - name : Test Transformer training and validation with dynamic scoring and copy | |
| run: | | |
| python3 train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -encoder_type transformer \ | |
| -decoder_type transformer \ | |
| -layers 4 \ | |
| -word_vec_size 16 \ | |
| -hidden_size 16 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -heads 2 \ | |
| -transformer_ff 64 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -accum_count 2 4 8 \ | |
| -accum_steps 0 15000 30000 \ | |
| -save_model /tmp/onmt.model \ | |
| -train_steps 10 -valid_steps 5 \ | |
| -report_every 2 \ | |
| -valid_metrics "BLEU" "TER" \ | |
| -tensorboard "true" \ | |
| -scoring_debug "true" \ | |
| -tensorboard_log_dir /tmp/logs_dynamic-scoring_and_copy \ | |
| -dump_preds /tmp/dump_preds \ | |
| -position_encoding \ | |
| -copy_attn | |
| python onmt/tests/test_events.py --logdir /tmp/logs_dynamic-scoring_and_copy -tensorboard_checks valid_metrics | |
| - name : Test Transformer training and validation with dynamic scoring and maxrelative | |
| run: | | |
| python3 train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -encoder_type transformer \ | |
| -decoder_type transformer \ | |
| -layers 4 \ | |
| -word_vec_size 16 \ | |
| -hidden_size 16 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -heads 2 \ | |
| -transformer_ff 64 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -accum_count 2 4 8 \ | |
| -accum_steps 0 15000 30000 \ | |
| -save_model /tmp/onmt.model \ | |
| -train_steps 10 -valid_steps 5 \ | |
| -report_every 2 \ | |
| -valid_metrics "BLEU" "TER" \ | |
| -tensorboard "true" \ | |
| -scoring_debug "true" \ | |
| -tensorboard_log_dir /tmp/logs_dynamic-scoring_and_relative \ | |
| -dump_preds /tmp/dump_preds \ | |
| -max_relative_positions 8 | |
| python onmt/tests/test_events.py --logdir /tmp/logs_dynamic-scoring_and_relative -tensorboard_checks valid_metrics | |
| - name : Test Transformer training and validation with dynamic scoring and rotary | |
| run: | | |
| python3 train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -encoder_type transformer \ | |
| -decoder_type transformer \ | |
| -layers 4 \ | |
| -word_vec_size 16 \ | |
| -hidden_size 16 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -heads 2 \ | |
| -transformer_ff 64 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -accum_count 2 4 8 \ | |
| -accum_steps 0 15000 30000 \ | |
| -save_model /tmp/onmt.model \ | |
| -train_steps 10 -valid_steps 5 \ | |
| -report_every 2 \ | |
| -valid_metrics "BLEU" "TER" \ | |
| -tensorboard "true" \ | |
| -scoring_debug "true" \ | |
| -tensorboard_log_dir /tmp/logs_dynamic-scoring_and_rotary \ | |
| -dump_preds /tmp/dump_preds \ | |
| -max_relative_positions -1 | |
| python onmt/tests/test_events.py --logdir /tmp/logs_dynamic-scoring_and_rotary -tensorboard_checks valid_metrics | |
| - name : Test Transformer training and validation with dynamic scoring and alibi | |
| run: | | |
| python3 train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -encoder_type transformer \ | |
| -decoder_type transformer \ | |
| -layers 4 \ | |
| -word_vec_size 16 \ | |
| -hidden_size 16 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -heads 2 \ | |
| -transformer_ff 64 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -accum_count 2 4 8 \ | |
| -accum_steps 0 15000 30000 \ | |
| -save_model /tmp/onmt.model \ | |
| -train_steps 10 -valid_steps 5 \ | |
| -report_every 2 \ | |
| -valid_metrics "BLEU" "TER" \ | |
| -tensorboard "true" \ | |
| -scoring_debug "true" \ | |
| -tensorboard_log_dir /tmp/logs_dynamic-scoring_and_alibi \ | |
| -dump_preds /tmp/dump_preds \ | |
| -max_relative_positions 8 | |
| python onmt/tests/test_events.py --logdir /tmp/logs_dynamic-scoring_and_alibi -tensorboard_checks valid_metrics | |
| - name: Test LM training | |
| run: | | |
| python train.py \ | |
| -config data/lm_data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.src \ | |
| -model_task lm \ | |
| -encoder_type transformer_lm \ | |
| -decoder_type transformer_lm \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -dec_layers 2 -batch_size 10 \ | |
| -heads 4 -transformer_ff 64 \ | |
| -word_vec_size 16 -report_every 5 \ | |
| -hidden_size 16 -train_steps 10 | |
| - name: Test LM training with copy | |
| run: | | |
| python train.py \ | |
| -config data/lm_data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.src \ | |
| -model_task lm \ | |
| -encoder_type transformer_lm \ | |
| -decoder_type transformer_lm \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -dec_layers 2 -batch_size 10 \ | |
| -heads 4 -transformer_ff 64 \ | |
| -word_vec_size 16 -report_every 5 \ | |
| -hidden_size 16 -train_steps 10 \ | |
| -copy_attn | |
| - name: Test Graph neural network training | |
| run: | | |
| python train.py \ | |
| -config data/ggnn_data.yaml \ | |
| -src_seq_length 1000 \ | |
| -tgt_seq_length 30 \ | |
| -encoder_type ggnn \ | |
| -layers 2 \ | |
| -decoder_type rnn \ | |
| -hidden_size 256 \ | |
| -learning_rate 0.1 \ | |
| -learning_rate_decay 0.8 \ | |
| -global_attention general \ | |
| -batch_size 32 \ | |
| -word_vec_size 256 \ | |
| -bridge \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -train_steps 10 \ | |
| -n_edge_types 9 \ | |
| -state_dim 256 \ | |
| -n_steps 10 \ | |
| -n_node 64 | |
| - name: Testing training with features | |
| run: | | |
| python onmt/bin/train.py \ | |
| -config data/features_data.yaml \ | |
| -src_vocab /tmp/onmt_feat.vocab.src \ | |
| -tgt_vocab /tmp/onmt_feat.vocab.tgt \ | |
| -src_vocab_size 1000 -tgt_vocab_size 1000 \ | |
| -hidden_size 2 -batch_size 10 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -word_vec_size 5 -hidden_size 10 \ | |
| -report_every 5 -train_steps 10 \ | |
| -save_model /tmp/onmt.model \ | |
| -save_checkpoint_steps 10 | |
| - name: Testing training with features and dynamic scoring | |
| run: | | |
| python onmt/bin/train.py \ | |
| -config data/features_data.yaml \ | |
| -src_vocab /tmp/onmt_feat.vocab.src \ | |
| -tgt_vocab /tmp/onmt_feat.vocab.tgt \ | |
| -src_vocab_size 1000 -tgt_vocab_size 1000 \ | |
| -hidden_size 2 -batch_size 10 \ | |
| -word_vec_size 5 -hidden_size 10 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -report_every 5 -train_steps 10 -valid_steps 5\ | |
| -valid_metrics "BLEU" "TER" \ | |
| -save_model /tmp/onmt.model \ | |
| -save_checkpoint_steps 10 | |
| - name: Testing translation with features | |
| run: | | |
| python translate.py \ | |
| -model /tmp/onmt.model_step_10.pt \ | |
| -src data/data_features/src-test-with-feats.txt \ | |
| -n_src_feats 1 -verbose | |
| - name: Test RNN translation | |
| run: | | |
| head data/src-test.txt > /tmp/src-test.txt | |
| python translate.py \ | |
| -model onmt/tests/test_model.pt \ | |
| -src /tmp/src-test.txt \ | |
| -verbose | |
| - name: Test RNN ensemble translation | |
| run: | | |
| head data/src-test.txt > /tmp/src-test.txt | |
| python translate.py \ | |
| -model onmt/tests/test_model.pt \ | |
| onmt/tests/test_model.pt \ | |
| -src /tmp/src-test.txt \ | |
| -verbose | |
| - name: Test RNN translation with beam search | |
| run: | | |
| python translate.py \ | |
| -model onmt/tests/test_model2.pt \ | |
| -src data/morph/src.valid \ | |
| -verbose \ | |
| -batch_size 10 \ | |
| -beam_size 10 \ | |
| -tgt data/morph/tgt.valid \ | |
| -out /tmp/trans | |
| diff data/morph/tgt.valid /tmp/trans && rm /tmp/trans | |
| - name: Test RNN translation with random sampling | |
| run: | | |
| python translate.py \ | |
| -model onmt/tests/test_model2.pt \ | |
| -src data/morph/src.valid \ | |
| -verbose \ | |
| -batch_size 10 \ | |
| -beam_size 1 \ | |
| -seed 1 \ | |
| -random_sampling_topk "-1" \ | |
| -random_sampling_temp 0.0001 \ | |
| -tgt data/morph/tgt.valid \ | |
| -out /tmp/trans | |
| diff data/morph/tgt.valid /tmp/trans && rm /tmp/trans | |
| - name: Test LM generation | |
| run: | | |
| head data/src-test.txt > /tmp/src-test.txt | |
| python translate.py \ | |
| -model onmt/tests/test_model_lm.pt \ | |
| -src /tmp/src-test.txt \ | |
| -verbose | |
| - name: Test LM generation with beam search | |
| run: | | |
| python translate.py \ | |
| -model onmt/tests/test_model_lm.pt \ | |
| -src data/data_lm/src-gen.txt \ | |
| -verbose -batch_size 1 \ | |
| -beam_size 10 \ | |
| -ban_unk_token \ | |
| -length_penalty none \ | |
| -out /tmp/gen | |
| diff data/data_lm/gen-beam-sol.txt /tmp/gen && rm /tmp/gen | |
| - name: Test LM generation with random sampling | |
| run: | | |
| python translate.py -model onmt/tests/test_model_lm.pt \ | |
| -src data/data_lm/src-gen.txt \ | |
| -verbose -batch_size 1 \ | |
| -beam_size 1 \ | |
| -seed 1 \ | |
| -random_sampling_topk -1 \ | |
| -random_sampling_temp 0.0001 \ | |
| -ban_unk_token \ | |
| -length_penalty none \ | |
| -out /tmp/gen | |
| diff data/data_lm/gen-sampling-sol.txt /tmp/gen && rm /tmp/gen | |
| - name: Test LM generation with random top-k/nucleus sampling | |
| run: | | |
| python translate.py -model onmt/tests/test_model_lm.pt \ | |
| -src data/data_lm/src-gen.txt \ | |
| -verbose -batch_size 1 \ | |
| -beam_size 1 \ | |
| -seed 3 \ | |
| -random_sampling_topk -1 \ | |
| -random_sampling_topp 0.95 \ | |
| -random_sampling_temp 1 \ | |
| -ban_unk_token \ | |
| -length_penalty none \ | |
| -out /tmp/gen | |
| diff data/data_lm/gen-nucleus-sampling-sol$(python -c "import torch; print(torch.__version__[0])").txt /tmp/gen && rm /tmp/gen | |
| - name: Test LM generation with random sampling multi-beams | |
| run: | | |
| python translate.py -model onmt/tests/test_model_lm.pt \ | |
| -src data/data_lm/src-gen.txt \ | |
| -verbose -batch_size 1 \ | |
| -beam_size 10 \ | |
| -seed 2 \ | |
| -random_sampling_topk 50 \ | |
| -random_sampling_topp 0.95 \ | |
| -random_sampling_temp 1 \ | |
| -length_penalty avg \ | |
| -ban_unk_token \ | |
| -min_length 5 \ | |
| -out /tmp/gen | |
| diff data/data_lm/gen-sampling-beams-sol$(python -c "import torch; print(torch.__version__[0])").txt /tmp/gen && rm /tmp/gen | |
| - name: Test py-LM inference engine | |
| run: | | |
| head data/src-test.txt > /tmp/src-test.txt | |
| python onmt/tests/test_inference_engines.py \ | |
| -model onmt/tests/test_model_lm.pt \ | |
| -model_task lm \ | |
| -input_file /tmp/src-test.txt \ | |
| -inference_config_file data/inference-engine_py.yaml \ | |
| -inference_mode py \ | |
| -out /tmp/inference_engine_lm_py_outputs | |
| - name: Test ct2-LM inference engine | |
| run: | | |
| head data/src-test.txt > /tmp/src-test.txt | |
| python onmt/tests/test_inference_engines.py \ | |
| -model onmt/tests/test_model_lm_ct2 \ | |
| -model_task lm \ | |
| -input_file /tmp/src-test.txt \ | |
| -inference_config_file data/inference-engine_py.yaml \ | |
| -inference_mode ct2 \ | |
| -out /tmp/inference_engine_lm_py_outputs | |
| - name: Test py-SEQ2SEQ inference engine | |
| run: | | |
| head data/src-test.txt > /tmp/src-test.txt | |
| python onmt/tests/test_inference_engines.py \ | |
| -model onmt/tests/test_model.pt \ | |
| -model_task seq2seq \ | |
| -input_file /tmp/src-test.txt \ | |
| -inference_config_file data/inference-engine_py.yaml \ | |
| -inference_mode py \ | |
| -out /tmp/inference_engine_lm_py_outputs | |
| - name: Test extract_vocabulary tool | |
| run: | | |
| python tools/extract_vocabulary.py \ | |
| -model onmt/tests/test_model.pt \ | |
| -side src \ | |
| -out_file /tmp/onmt.vocab.txt | |
| if ! wc -l /tmp/onmt.vocab.txt | grep -qF "1002" | |
| then echo "wrong word count" && exit 1 | |
| else | |
| echo "create vocabulary pass" | |
| fi | |
| - name: Test embeddings_to_torch tool | |
| run: | | |
| python tools/embeddings_to_torch.py \ | |
| -emb_file_enc onmt/tests/sample_glove.txt \ | |
| -emb_file_dec onmt/tests/sample_glove.txt \ | |
| -dict_file onmt/tests/test_model.pt \ | |
| -output_file /tmp/q_gloveembeddings \ | |
| && rm /tmp/q_gloveembeddings* | |
| - name: Test extract_embeddings tool | |
| run: | | |
| python tools/extract_embeddings.py \ | |
| -model onmt/tests/test_model.pt | |
| - name: Test checkpoint vocabulary update | |
| run: | | |
| python train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -hidden_size 2 \ | |
| -batch_size 10 \ | |
| -word_vec_size 5 \ | |
| -report_every 5\ | |
| -hidden_size 10 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -train_steps 10 \ | |
| -save_model /tmp/onmt.model \ | |
| -save_checkpoint_steps 10 | |
| sed -i '1s/^/new_tok\t100000000\n/' /tmp/onmt.vocab.src | |
| python train.py \ | |
| -config data/data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.tgt \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -hidden_size 2 \ | |
| -batch_size 10 \ | |
| -word_vec_size 5 \ | |
| -report_every 5\ | |
| -hidden_size 10 \ | |
| -train_steps 20 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -update_vocab \ | |
| -reset_optim "states" \ | |
| -train_from /tmp/onmt.model_step_10.pt | |
| - name: Test checkpoint vocabulary update with LM | |
| run: | | |
| python train.py \ | |
| -config data/lm_data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.src \ | |
| -model_task lm \ | |
| -encoder_type transformer_lm \ | |
| -decoder_type transformer_lm \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -dec_layers 2 -batch_size 10 \ | |
| -heads 4 -transformer_ff 64 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -word_vec_size 16 -report_every 5 \ | |
| -save_model /tmp/lm.onmt.model \ | |
| -save_checkpoint_steps 10 \ | |
| -hidden_size 16 -train_steps 10 | |
| sed -i '1s/^/new_tok2\t100000000\n/' /tmp/onmt.vocab.src | |
| python train.py \ | |
| -config data/lm_data.yaml \ | |
| -src_vocab /tmp/onmt.vocab.src \ | |
| -tgt_vocab /tmp/onmt.vocab.src \ | |
| -model_task lm \ | |
| -encoder_type transformer_lm \ | |
| -decoder_type transformer_lm \ | |
| -src_vocab_size 1000 \ | |
| -tgt_vocab_size 1000 \ | |
| -num_workers 0 -bucket_size 1024 \ | |
| -dec_layers 2 -batch_size 10 \ | |
| -heads 4 -transformer_ff 64 \ | |
| -word_vec_size 16 -report_every 5 \ | |
| -hidden_size 16 -train_steps 20 \ | |
| -update_vocab -reset_optim "states" \ | |
| -train_from /tmp/lm.onmt.model_step_10.pt | |
| build-docs: | |
| runs-on: ubuntu-latest | |
| steps: | |
| - uses: actions/checkout@v2 | |
| - name: Set up Python 3.8 | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: 3.8 | |
| - name: Install dependencies | |
| run: | | |
| python -m pip install --upgrade pip | |
| pip install --upgrade setuptools | |
| pip install -e . | |
| pip install -r docs/requirements.txt | |
| - name: Build docs | |
| run: | | |
| set -e | |
| # Check that docs are built without errors | |
| cd docs/ && make html && cd .. |