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add acknowledgements #160

Workflow file for this run

.github/workflows/push.yml at fc9e5f6
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 flake8==4.0.1
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
- name: Lint with flake8
run: |
flake8 --max-line-length 120 .
- name: Unit tests
run: |
python -m unittest discover
# ## Broken in FoTraNMT
# - 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 \
# -src_feats_vocab '{"feat0": "/tmp/onmt_feat.vocab.feat0"}' \
# -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 \
# -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 \
# -rnn_size 2 \
# -batch_size 10 \
# -word_vec_size 5 \
# -report_every 5\
# -rnn_size 10 \
# -train_steps 10
# - name: Test RNN training 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 \
# -rnn_size 2 \
# -batch_size 10 \
# -word_vec_size 5 \
# -report_every 5 \
# -rnn_size 10 \
# -train_steps 10 \
# -copy_attn
# - 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 \
# -rnn_size 2 -batch_size 10 \
# -word_vec_size 5 -report_every 5 \
# -coverage_attn true -lambda_coverage 0.1 \
# -rnn_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 \
# -max_generator_batches 0 \
# -encoder_type transformer \
# -decoder_type transformer \
# -layers 4 \
# -word_vec_size 16 \
# -rnn_size 16 \
# -heads 2 \
# -transformer_ff 64 \
# -lambda_align 0.05 \
# -alignment_layer 2 \
# -alignment_heads 0 \
# -report_every 5 \
# -train_steps 10
# - 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 \
# -dec_layers 2 -batch_size 10 \
# -heads 4 -transformer_ff 64 \
# -word_vec_size 16 -report_every 5 \
# -rnn_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 \
# -dec_layers 2 -batch_size 10 \
# -heads 4 -transformer_ff 64 \
# -word_vec_size 16 -report_every 5 \
# -rnn_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 \
# -rnn_size 256 \
# -learning_rate 0.1 \
# -learning_rate_decay 0.8 \
# -global_attention general \
# -batch_size 32 \
# -word_vec_size 256 \
# -bridge \
# -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_feats_vocab '{"feat0": "/tmp/onmt_feat.vocab.feat0"}' \
# -src_vocab_size 1000 -tgt_vocab_size 1000 \
# -rnn_size 2 -batch_size 10 \
# -word_vec_size 5 -rnn_size 10 \
# -report_every 5 -train_steps 10 \
# -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.txt \
# -src_feats "{'feat0': 'data/data_features/src-test.feat0'}" \
# -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 data/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 10 \
# -beam_size 10 \
# -ban_unk_token \
# -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 10 \
# -beam_size 1 \
# -seed 1 \
# -random_sampling_topk -1 \
# -random_sampling_temp 0.0001 \
# -ban_unk_token \
# -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 10 \
# -beam_size 1 \
# -seed 3 \
# -random_sampling_topk -1 \
# -random_sampling_topp 0.95 \
# -random_sampling_temp 1 \
# -ban_unk_token \
# -out /tmp/gen
# diff data/data_lm/gen-nucleus-sampling-sol.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 10 \
# -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.txt /tmp/gen && rm /tmp/gen
# - name: Test extract_vocabulary tool
# run: |
# python tools/extract_vocabulary.py \
# -file /tmp/onmt.train.check.vocab.pt \
# -file_type field \
# -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 /tmp/onmt.train.check.vocab.pt \
# -output_file /tmp/q_gloveembeddings \
# && rm /tmp/q_gloveembeddings*
# rm /tmp/onmt.train.check.*.pt
# - 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 \
# -rnn_size 2 \
# -batch_size 10 \
# -word_vec_size 5 \
# -report_every 5\
# -rnn_size 10 \
# -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 \
# -rnn_size 2 \
# -batch_size 10 \
# -word_vec_size 5 \
# -report_every 5\
# -rnn_size 10 \
# -train_steps 20 \
# -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.tgt \
# -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 \
# -word_vec_size 16 -report_every 5 \
# -save_model /tmp/lm.onmt.model \
# -save_checkpoint_steps 10 \
# -rnn_size 16 -train_steps 10
# sed -i '1s/^/new_tok\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.tgt \
# -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 \
# -word_vec_size 16 -report_every 5 \
# -rnn_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 ..
- name: Deploy docs
uses: JamesIves/[email protected]
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
BRANCH: gh-pages
FOLDER: docs/build/html
CLEAN: true