├── .gitignore ├── README.md ├── bash ├── blending_n_postprocessing.sh ├── download_all_model_ckpts_for_inference.sh ├── download_comp_data.sh ├── inference │ ├── model1_inference.sh │ ├── model2_inference.sh │ ├── model3_inference.sh │ ├── model4_inference.sh │ └── run_inference.sh ├── pseudo │ ├── create_all_pseudo_labels.sh │ ├── create_all_pseudo_labels_toy.sh │ ├── create_pseudo_base.sh │ ├── create_pseudo_base_pretrained.sh │ ├── create_pseudo_large.sh │ ├── train_base.sh │ ├── train_base_pretrained.sh │ └── train_large.sh ├── setup.sh └── training │ ├── load_roberta_weights.sh │ ├── train1a_prepare_stackx_data.sh │ ├── train1b_train_bert_stackx_lang_model.sh │ ├── train2_pseudo_labels.sh │ ├── train3_bert_base_cased_stackx_pretrained.sh │ ├── train4_bert_base_cased_stackx_with_pseudo_labels.sh │ ├── train5_roberta_with_pseudo_labels.sh │ └── train6_bart_with_pseudo_labels.sh ├── experiments ├── 1-8-5-head_tail-pseudonoleakrandom100k-1e-05-210-260-500-26-200 │ ├── command │ ├── commit_hash │ └── config.json ├── 2-4-5-head_tail-pseudonoleakrandom100k-1e-05-210-260-500-26-roberta-200 │ ├── command │ ├── commit_hash │ └── config.json ├── 2-4-roberta-base-saved-5-head_tail-roberta-stackx-base-v2-pl1kksample20k-1e-05-210-260-500-26-roberta-200 │ ├── config.json │ └── config_train.json └── 4-2-5-head_tail-bart-2e-05-210-260-500-26-split_pseudo-250 │ ├── command │ ├── commit_hash │ └── config.json ├── input ├── google-quest-challenge │ ├── sample_submission_toy.csv │ ├── test_toy.csv │ └── train_toy.csv ├── qa_stackexchange_cleaned.csv ├── qa_stackexchange_cleaned_toy.csv └── stackx-base-cased │ ├── config.json │ ├── stackx-base-cased-config.json │ ├── stackx-base-cased-vocab.txt │ ├── training_log.csv │ └── vocab.txt ├── logs ├── all_inference.log ├── model1_inference.log ├── model2_inference.log ├── model3_inference.log └── model4_inference.log ├── packages ├── fairseq-hacked │ ├── .gitignore │ ├── CODE_OF_CONDUCT.md │ ├── CONTRIBUTING.md │ ├── LICENSE │ ├── README.md │ ├── docs │ │ ├── Makefile │ │ ├── _static │ │ │ └── theme_overrides.css │ │ ├── command_line_tools.rst │ │ ├── conf.py │ │ ├── criterions.rst │ │ ├── data.rst │ │ ├── docutils.conf │ │ ├── getting_started.rst │ │ ├── index.rst │ │ ├── lr_scheduler.rst │ │ ├── make.bat │ │ ├── models.rst │ │ ├── modules.rst │ │ ├── optim.rst │ │ ├── overview.rst │ │ ├── requirements.txt │ │ ├── tasks.rst │ │ ├── tutorial_classifying_names.rst │ │ └── tutorial_simple_lstm.rst │ ├── eval_lm.py │ ├── examples │ │ ├── .gitignore │ │ ├── __init__.py │ │ ├── backtranslation │ │ │ └── README.md │ │ ├── bart │ │ │ ├── README.cnn.md │ │ │ ├── README.glue.md │ │ │ └── README.md │ │ ├── camembert │ │ │ └── README.md │ │ ├── conv_seq2seq │ │ │ └── README.md │ │ ├── cross_lingual_language_model │ │ │ └── README.md │ │ ├── joint_alignment_translation │ │ │ ├── README.md │ │ │ └── prepare-wmt18en2de_no_norm_no_escape_no_agressive.sh │ │ ├── language_model │ │ │ ├── README.md │ │ │ ├── conv_lm │ │ │ │ └── README.md │ │ │ ├── prepare-wikitext-103.sh │ │ │ └── transformer_lm │ │ │ │ └── README.md │ │ ├── layerdrop │ │ │ └── README.md │ │ ├── noisychannel │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── rerank.py │ │ │ ├── rerank_generate.py │ │ │ ├── rerank_options.py │ │ │ ├── rerank_score_bw.py │ │ │ ├── rerank_score_lm.py │ │ │ ├── rerank_tune.py │ │ │ └── rerank_utils.py │ │ ├── nonautoregressive_translation │ │ │ ├── README.md │ │ │ └── scripts.md │ │ ├── pay_less_attention_paper │ │ │ └── README.md │ │ ├── roberta │ │ │ ├── README.custom_classification.md │ │ │ ├── README.glue.md │ │ │ ├── README.md │ │ │ ├── README.pretraining.md │ │ │ ├── README.race.md │ │ │ ├── commonsense_qa │ │ │ │ ├── README.md │ │ │ │ ├── __init__.py │ │ │ │ ├── commonsense_qa_task.py │ │ │ │ └── download_cqa_data.sh │ │ │ ├── multiprocessing_bpe_encoder.py │ │ │ ├── preprocess_GLUE_tasks.sh │ │ │ ├── preprocess_RACE.py │ │ │ ├── preprocess_RACE.sh │ │ │ └── wsc │ │ │ │ ├── README.md │ │ │ │ ├── __init__.py │ │ │ │ ├── wsc_criterion.py │ │ │ │ ├── wsc_task.py │ │ │ │ └── wsc_utils.py │ │ ├── scaling_nmt │ │ │ └── README.md │ │ ├── speech_recognition │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── criterions │ │ │ │ ├── ASG_loss.py │ │ │ │ ├── CTC_loss.py │ │ │ │ ├── __init__.py │ │ │ │ └── cross_entropy_acc.py │ │ │ ├── datasets │ │ │ │ ├── asr_prep_json.py │ │ │ │ └── prepare-librispeech.sh │ │ │ ├── infer.py │ │ │ ├── models │ │ │ │ ├── __init__.py │ │ │ │ ├── vggtransformer.py │ │ │ │ └── w2l_conv_glu_enc.py │ │ │ ├── tasks │ │ │ │ ├── __init__.py │ │ │ │ └── speech_recognition.py │ │ │ ├── utils │ │ │ │ └── wer_utils.py │ │ │ └── w2l_decoder.py │ │ ├── stories │ │ │ └── README.md │ │ ├── translation │ │ │ ├── README.md │ │ │ ├── prepare-iwslt14.sh │ │ │ ├── prepare-iwslt17-multilingual.sh │ │ │ ├── prepare-wmt14en2de.sh │ │ │ └── prepare-wmt14en2fr.sh │ │ ├── translation_moe │ │ │ ├── README.md │ │ │ └── score.py │ │ ├── wav2vec │ │ │ └── README.md │ │ ├── wmt19 │ │ │ └── README.md │ │ └── xlmr │ │ │ └── README.md │ ├── fairseq.gif │ ├── fairseq │ │ ├── __init__.py │ │ ├── binarizer.py │ │ ├── bleu.py │ │ ├── checkpoint_utils.py │ │ ├── clib │ │ │ ├── libbleu │ │ │ │ ├── libbleu.cpp │ │ │ │ └── module.cpp │ │ │ └── libnat │ │ │ │ └── edit_dist.cpp │ │ ├── criterions │ │ │ ├── __init__.py │ │ │ ├── adaptive_loss.py │ │ │ ├── binary_cross_entropy.py │ │ │ ├── composite_loss.py │ │ │ ├── cross_entropy.py │ │ │ ├── fairseq_criterion.py │ │ │ ├── label_smoothed_cross_entropy.py │ │ │ ├── label_smoothed_cross_entropy_with_alignment.py │ │ │ ├── legacy_masked_lm.py │ │ │ ├── masked_lm.py │ │ │ ├── nat_loss.py │ │ │ ├── sentence_prediction.py │ │ │ └── sentence_ranking.py │ │ ├── distributed_utils.py │ │ ├── file_utils.py │ │ ├── hub_utils.py │ │ ├── iterative_refinement_generator.py │ │ ├── legacy_distributed_data_parallel.py │ │ ├── meters.py │ │ ├── models │ │ │ ├── __init__.py │ │ │ ├── bart │ │ │ │ ├── __init__.py │ │ │ │ ├── hub_interface.py │ │ │ │ └── model.py │ │ │ ├── cmlm_transformer.py │ │ │ ├── composite_encoder.py │ │ │ ├── distributed_fairseq_model.py │ │ │ ├── fairseq_decoder.py │ │ │ ├── fairseq_encoder.py │ │ │ ├── fairseq_incremental_decoder.py │ │ │ ├── fairseq_model.py │ │ │ ├── fconv.py │ │ │ ├── fconv_lm.py │ │ │ ├── fconv_self_att.py │ │ │ ├── insertion_transformer.py │ │ │ ├── iterative_nonautoregressive_transformer.py │ │ │ ├── levenshtein_transformer.py │ │ │ ├── lightconv.py │ │ │ ├── lightconv_lm.py │ │ │ ├── lstm.py │ │ │ ├── masked_lm.py │ │ │ ├── model_utils.py │ │ │ ├── multilingual_transformer.py │ │ │ ├── nonautoregressive_ensembles.py │ │ │ ├── nonautoregressive_transformer.py │ │ │ ├── roberta │ │ │ │ ├── __init__.py │ │ │ │ ├── alignment_utils.py │ │ │ │ ├── hub_interface.py │ │ │ │ └── model.py │ │ │ ├── transformer.py │ │ │ ├── transformer_from_pretrained_xlm.py │ │ │ ├── transformer_lm.py │ │ │ └── wav2vec.py │ │ ├── modules │ │ │ ├── __init__.py │ │ │ ├── adaptive_input.py │ │ │ ├── adaptive_softmax.py │ │ │ ├── beamable_mm.py │ │ │ ├── character_token_embedder.py │ │ │ ├── conv_tbc.py │ │ │ ├── cuda_utils.cu │ │ │ ├── downsampled_multihead_attention.py │ │ │ ├── dynamic_convolution.py │ │ │ ├── dynamicconv_layer │ │ │ │ ├── __init__.py │ │ │ │ ├── cuda_function_gen.py │ │ │ │ ├── dynamicconv_cuda.cpp │ │ │ │ ├── dynamicconv_cuda.cuh │ │ │ │ ├── dynamicconv_cuda_kernel.cu │ │ │ │ ├── dynamicconv_layer.py │ │ │ │ ├── dynamiconv_cpu.cpp │ │ │ │ └── setup.py │ │ │ ├── gelu.py │ │ │ ├── grad_multiply.py │ │ │ ├── highway.py │ │ │ ├── layer_norm.py │ │ │ ├── learned_positional_embedding.py │ │ │ ├── lightconv_layer │ │ │ │ ├── __init__.py │ │ │ │ ├── cuda_function_gen.py │ │ │ │ ├── lightconv_cuda.cpp │ │ │ │ ├── lightconv_cuda.cuh │ │ │ │ ├── lightconv_cuda_kernel.cu │ │ │ │ ├── lightconv_layer.py │ │ │ │ └── setup.py │ │ │ ├── lightweight_convolution.py │ │ │ ├── linearized_convolution.py │ │ │ ├── logsumexp_moe.py │ │ │ ├── mean_pool_gating_network.py │ │ │ ├── multihead_attention.py │ │ │ ├── positional_embedding.py │ │ │ ├── scalar_bias.py │ │ │ ├── sinusoidal_positional_embedding.py │ │ │ ├── sparse_multihead_attention.py │ │ │ ├── sparse_transformer_sentence_encoder.py │ │ │ ├── sparse_transformer_sentence_encoder_layer.py │ │ │ ├── transformer_layer.py │ │ │ ├── transformer_sentence_encoder.py │ │ │ ├── transformer_sentence_encoder_layer.py │ │ │ ├── unfold.py │ │ │ └── vggblock.py │ │ ├── optim │ │ │ ├── __init__.py │ │ │ ├── adadelta.py │ │ │ ├── adafactor.py │ │ │ ├── adagrad.py │ │ │ ├── adam.py │ │ │ ├── adamax.py │ │ │ ├── bmuf.py │ │ │ ├── fairseq_optimizer.py │ │ │ ├── fp16_optimizer.py │ │ │ ├── lr_scheduler │ │ │ │ ├── __init__.py │ │ │ │ ├── cosine_lr_scheduler.py │ │ │ │ ├── fairseq_lr_scheduler.py │ │ │ │ ├── fixed_schedule.py │ │ │ │ ├── inverse_square_root_schedule.py │ │ │ │ ├── polynomial_decay_schedule.py │ │ │ │ ├── reduce_lr_on_plateau.py │ │ │ │ ├── tri_stage_lr_scheduler.py │ │ │ │ └── triangular_lr_scheduler.py │ │ │ ├── nag.py │ │ │ └── sgd.py │ │ ├── options.py │ │ ├── pdb.py │ │ ├── progress_bar.py │ │ ├── registry.py │ │ ├── search.py │ │ ├── sequence_generator.py │ │ ├── sequence_scorer.py │ │ ├── tasks │ │ │ ├── __init__.py │ │ │ ├── audio_pretraining.py │ │ │ ├── cross_lingual_lm.py │ │ │ ├── denoising.py │ │ │ ├── fairseq_task.py │ │ │ ├── language_modeling.py │ │ │ ├── legacy_masked_lm.py │ │ │ ├── masked_lm.py │ │ │ ├── multilingual_masked_lm.py │ │ │ ├── multilingual_translation.py │ │ │ ├── semisupervised_translation.py │ │ │ ├── sentence_prediction.py │ │ │ ├── sentence_ranking.py │ │ │ ├── translation.py │ │ │ ├── translation_from_pretrained_xlm.py │ │ │ ├── translation_lev.py │ │ │ └── translation_moe.py │ │ ├── tokenizer.py │ │ ├── trainer.py │ │ └── utils.py │ ├── fairseq_cli │ │ ├── __init__.py │ │ ├── eval_lm.py │ │ ├── generate.py │ │ ├── interactive.py │ │ ├── preprocess.py │ │ ├── score.py │ │ ├── setup.py │ │ └── train.py │ ├── fairseq_logo.png │ ├── generate.py │ ├── hubconf.py │ ├── interactive.py │ ├── preprocess.py │ ├── score.py │ ├── scripts │ │ ├── __init__.py │ │ ├── average_checkpoints.py │ │ ├── build_sym_alignment.py │ │ ├── compare_namespaces.py │ │ ├── compound_split_bleu.sh │ │ ├── convert_dictionary.lua │ │ ├── convert_model.lua │ │ ├── count_docs.py │ │ ├── read_binarized.py │ │ ├── rm_pt.py │ │ ├── sacrebleu_pregen.sh │ │ ├── shard_docs.py │ │ ├── split_train_valid_docs.py │ │ ├── spm_decode.py │ │ ├── spm_encode.py │ │ ├── spm_train.py │ │ ├── wav2vec_featurize.py │ │ └── wav2vec_manifest.py │ ├── setup.py │ ├── tests │ │ ├── __init__.py │ │ ├── speech_recognition │ │ │ ├── __init__.py │ │ │ ├── asr_test_base.py │ │ │ ├── test_collaters.py │ │ │ ├── test_cross_entropy.py │ │ │ └── test_vggtransformer.py │ │ ├── test_average_checkpoints.py │ │ ├── test_backtranslation_dataset.py │ │ ├── test_binaries.py │ │ ├── test_bmuf.py │ │ ├── test_character_token_embedder.py │ │ ├── test_concat_dataset.py │ │ ├── test_convtbc.py │ │ ├── test_dictionary.py │ │ ├── test_iterators.py │ │ ├── test_label_smoothing.py │ │ ├── test_memory_efficient_fp16.py │ │ ├── test_multi_corpus_sampled_dataset.py │ │ ├── test_multihead_attention.py │ │ ├── test_noising.py │ │ ├── test_reproducibility.py │ │ ├── test_resampling_dataset.py │ │ ├── test_sequence_generator.py │ │ ├── test_sequence_scorer.py │ │ ├── test_sparse_multihead_attention.py │ │ ├── test_token_block_dataset.py │ │ ├── test_train.py │ │ ├── test_utils.py │ │ └── utils.py │ ├── train.py │ └── validate.py └── gpt2bpe │ ├── encoder.json │ └── vocab.bpe ├── requirements_full.txt ├── requirements_minimal.txt ├── step11_final └── blending_n_postprocessing.py ├── step1_lm_finetuning ├── callbacks.py ├── data │ ├── __init__.py │ ├── augmentation │ │ ├── __init__.py │ │ └── tokenization.py │ ├── config.json │ ├── dataset.py │ ├── folds.csv │ ├── group_kf_folds.csv │ ├── make_folds.py │ ├── sampler.py │ └── vocab.txt ├── data_preparation │ ├── clean_stack_exchange_qa.py │ ├── clean_stackexchange_QA_demonstration.ipynb │ ├── download_and_process_stackexchange_dump_demonstration.ipynb │ └── scrape_stack_exchange.py ├── train_stackx_lm.py └── utils.py ├── step2_pseudo_labeling ├── bert-base-pretrained │ ├── apply_swa.py │ ├── args.py │ ├── dataset.py │ ├── evaluation.py │ ├── infer.py │ ├── infer_pseudo.py │ ├── loops.py │ ├── misc.py │ ├── model.py │ └── run.py ├── bert-base │ ├── apply_swa.py │ ├── args.py │ ├── dataset.py │ ├── evaluation.py │ ├── infer.py │ ├── infer_pseudo.py │ ├── loops.py │ ├── misc.py │ ├── model.py │ └── run.py ├── bert-large │ ├── apply_swa.py │ ├── args.py │ ├── dataset.py │ ├── evaluation.py │ ├── infer.py │ ├── infer_pseudo.py │ ├── loops.py │ ├── misc.py │ ├── model.py │ └── run.py └── blend_pseudo.py ├── step3_model1_bert_code ├── bert.py ├── callbacks.py ├── data │ ├── __init__.py │ ├── augmentation │ │ ├── __init__.py │ │ └── tokenization.py │ ├── dataset.py │ ├── folds.csv │ ├── group_kf_folds.csv │ ├── make_folds.py │ └── sampler.py ├── metrics.py ├── models.py ├── schedule.py ├── train.py └── utils.py ├── step4_model2_bert_code ├── apply_swa.py ├── args.py ├── dataset.py ├── evaluation.py ├── infer.py ├── loops.py ├── misc.py ├── model.py └── run.py ├── step5_model3_roberta_code ├── args.py ├── augmentation.py ├── dataset.py ├── evaluation.py ├── infer.py ├── loops.py ├── misc.py ├── model.py └── run.py ├── step6_model4_bart_code ├── apply_swa.py ├── args.py ├── dataset.py ├── evaluation.py ├── infer.py ├── loops.py ├── misc.py ├── model.py └── run.py ├── steps7_10_inference ├── model1_bert_code │ ├── callbacks.py │ ├── data │ │ ├── __init__.py │ │ ├── augmentation │ │ │ ├── __init__.py │ │ │ └── tokenization.py │ │ ├── dataset.py │ │ ├── folds.csv │ │ ├── group_kf_folds.csv │ │ ├── make_folds.py │ │ └── sampler.py │ ├── metrics.py │ ├── models.py │ ├── predict_test.py │ ├── schedule.py │ └── utils.py ├── model2_bert_code │ ├── args.py │ ├── dataset.py │ ├── loops.py │ ├── model.py │ └── run.py ├── 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