├── .gitignore ├── .isort.cfg ├── LICENSE ├── MANIFEST.in ├── Makefile ├── README.md ├── RESEARCH_REPORT.md ├── analysis ├── README.md ├── __init__.py ├── _make_iterencode.py ├── analyze_run.py ├── article │ ├── README.md │ ├── build_table.ipynb │ ├── files │ │ ├── results_mnli.json │ │ ├── results_squadv1.json │ │ └── results_squadv2.json │ ├── layers_pruning_images.ipynb │ ├── pruning_by_layer_images.ipynb │ └── results_json_rewrite.py ├── aws_download.py ├── cache │ ├── bert_mnli.json │ ├── bert_qqp.json │ ├── bert_squadv1.json │ ├── bert_squadv2.json │ ├── bert_sst2.json │ ├── distilbert_mnli.json │ ├── distilbert_qqp.json │ ├── distilbert_squadv1.json │ ├── distilbert_squadv2.json │ ├── distilbert_sst2.json │ ├── experiments_mnli-results_mnli-1616173633.json │ ├── experiments_mnli-results_mnli-1617092624.json │ ├── experiments_mnli-results_mnli-1620139185.json │ ├── experiments_mnli-results_mnli-1620139670.json │ ├── experiments_mnli-results_mnli-1621160098.json │ ├── experiments_squadv1-results_squadv1-1617091408.json │ ├── experiments_squadv2-results_squadv2-1620236030.json │ ├── experiments_squadv2-results_squadv2-1620306581.json │ ├── experiments_squadv2-results_squadv2-1620307347.json │ ├── experiments_squadv2-results_squadv2-1620373365.json │ ├── experiments_squadv2-results_squadv2-1620373689.json │ ├── experiments_squadv2-results_squadv2-1620394632.json │ ├── experiments_squadv2-results_squadv2-1620642354.json │ ├── experiments_squadv2-results_squadv2-1620666814.json │ ├── glueexperiments_mnli.json │ ├── glueexperiments_qqp.json │ ├── glueexperiments_squadv1.json │ ├── glueexperiments_squadv2.json │ ├── glueexperiments_sst2.json │ ├── mobilebert_mnli.json │ ├── mobilebert_qqp.json │ ├── mobilebert_squadv1.json │ ├── mobilebert_squadv2.json │ ├── mobilebert_sst2.json │ ├── movementpruning_mnli.json │ ├── movementpruning_qqp.json │ ├── movementpruning_squadv1.json │ ├── movementpruning_squadv2.json │ ├── movementpruning_sst2.json │ ├── structuredpruningofbert_mnli.json │ ├── structuredpruningofbert_qqp.json │ ├── structuredpruningofbert_squadv1.json │ ├── structuredpruningofbert_squadv2.json │ ├── structuredpruningofbert_sst2.json │ ├── tinybert_mnli.json │ ├── tinybert_qqp.json │ ├── tinybert_squadv1.json │ ├── tinybert_squadv2.json │ └── tinybert_sst2.json ├── checkpoints │ ├── checkpoints.jsonl │ ├── checkpoints.old.jsonl │ ├── checkpoints.old2.jsonl │ └── checkpoints.old3.jsonl ├── command_line.py ├── create_model.py ├── files │ ├── BERT glue benchmark.xlsx │ ├── README_MODEL.squadv1.jinja.md │ ├── README_MODEL.squadv2.jinja.md │ ├── base_speed_report_file_mnli.json │ ├── base_speed_report_file_squadv1.json │ ├── base_speed_report_file_squadv2.json │ ├── mvmt_pruning.xlsx │ ├── removed_files_2021-03-30_11_27_19.json │ ├── results_mnli.json │ ├── results_squadv1.json │ └── results_squadv2.json ├── final_fine_tune.py ├── graph_util.py ├── graphs │ ├── mnli │ │ ├── block_size_influence_basic │ │ │ ├── block_size_influence_basic_fill_rate.eps │ │ │ ├── block_size_influence_basic_fill_rate.html │ │ │ ├── block_size_influence_basic_fill_rate.js │ │ │ ├── block_size_influence_basic_fill_rate.png │ │ │ ├── block_size_influence_basic_fill_rate_static.png │ │ │ ├── block_size_influence_basic_speedup.eps │ │ │ ├── block_size_influence_basic_speedup.html │ │ │ ├── block_size_influence_basic_speedup.js │ │ │ ├── block_size_influence_basic_speedup.png │ │ │ ├── block_size_influence_basic_speedup_static.png │ │ │ └── logs │ │ │ │ ├── block_size_influence_basic_fill_rate_Hybrid__BERT-base.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Hybrid__abs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Hybrid__bs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Hybrid_filled__BERT-base.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Hybrid_filled__abs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Hybrid__BERT-base.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Hybrid__abs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Hybrid__bs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Hybrid_filled__BERT-base.jsonl │ │ │ │ └── block_size_influence_basic_speedup_Hybrid_filled__abs_32x32.jsonl │ │ ├── comparison_large_teacher │ │ │ ├── comparison_large_teacher_fill_rate.eps │ │ │ ├── comparison_large_teacher_fill_rate.html │ │ │ ├── comparison_large_teacher_fill_rate.js │ │ │ ├── comparison_large_teacher_fill_rate.png │ │ │ ├── comparison_large_teacher_fill_rate_static.png │ │ │ ├── comparison_large_teacher_speedup.eps │ │ │ ├── comparison_large_teacher_speedup.html │ │ │ ├── comparison_large_teacher_speedup.js │ │ │ ├── comparison_large_teacher_speedup.png │ │ │ ├── comparison_large_teacher_speedup_static.png │ │ │ └── logs │ │ │ │ ├── comparison_large_teacher_fill_rate_BERT-base_teacher.jsonl │ │ │ │ ├── comparison_large_teacher_fill_rate_DistilBERT.jsonl │ │ │ │ ├── comparison_large_teacher_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── comparison_large_teacher_fill_rate_TinyBERT.jsonl │ │ │ │ ├── comparison_large_teacher_speedup_BERT-base_teacher.jsonl │ │ │ │ ├── comparison_large_teacher_speedup_DistilBERT.jsonl │ │ │ │ ├── comparison_large_teacher_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ └── comparison_large_teacher_speedup_TinyBERT.jsonl │ │ ├── full_block_size_influence │ │ │ ├── full_block_size_influence_fill_rate.eps │ │ │ ├── full_block_size_influence_fill_rate.html │ │ │ ├── full_block_size_influence_fill_rate.js │ │ │ ├── full_block_size_influence_fill_rate.png │ │ │ ├── full_block_size_influence_fill_rate_static.png │ │ │ ├── full_block_size_influence_speedup.eps │ │ │ ├── full_block_size_influence_speedup.html │ │ │ ├── full_block_size_influence_speedup.js │ │ │ ├── full_block_size_influence_speedup.png │ │ │ ├── full_block_size_influence_speedup_static.png │ │ │ └── logs │ │ │ │ ├── full_block_size_influence_fill_rate_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Original_Soft_Movement.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_TinyBERT.jsonl │ │ │ │ ├── full_block_size_influence_speedup_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_speedup_Original_Soft_Movement.jsonl │ │ │ │ └── full_block_size_influence_speedup_TinyBERT.jsonl │ │ ├── full_block_size_influence_raw │ │ │ ├── full_block_size_influence_raw_fill_rate.eps │ │ │ ├── full_block_size_influence_raw_fill_rate.html │ │ │ ├── full_block_size_influence_raw_fill_rate.js │ │ │ ├── full_block_size_influence_raw_fill_rate.png │ │ │ ├── full_block_size_influence_raw_fill_rate_static.png │ │ │ ├── full_block_size_influence_raw_speedup.eps │ │ │ ├── full_block_size_influence_raw_speedup.html │ │ │ ├── full_block_size_influence_raw_speedup.js │ │ │ ├── full_block_size_influence_raw_speedup.png │ │ │ ├── full_block_size_influence_raw_speedup_static.png │ │ │ └── logs │ │ │ │ ├── full_block_size_influence_raw_fill_rate_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Distilbert.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Original_Soft_Movement.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_TinyBERT.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Tinybert.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Distilbert.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Original_Soft_Movement.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_TinyBERT.jsonl │ │ │ │ └── full_block_size_influence_raw_speedup_Tinybert.jsonl │ │ ├── paper_block_size_influence │ │ │ ├── logs │ │ │ │ ├── paper_block_size_influence_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_BERT-base.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ └── paper_block_size_influence_speedup_TinyBERT.jsonl │ │ │ ├── paper_block_size_influence_fill_rate.eps │ │ │ ├── paper_block_size_influence_fill_rate.html │ │ │ ├── paper_block_size_influence_fill_rate.js │ │ │ ├── paper_block_size_influence_fill_rate.pdf │ │ │ ├── paper_block_size_influence_fill_rate.png │ │ │ ├── paper_block_size_influence_fill_rate_static.png │ │ │ ├── paper_block_size_influence_speedup.eps │ │ │ ├── paper_block_size_influence_speedup.html │ │ │ ├── paper_block_size_influence_speedup.js │ │ │ ├── paper_block_size_influence_speedup.pdf │ │ │ ├── paper_block_size_influence_speedup.png │ │ │ └── paper_block_size_influence_speedup_static.png │ │ ├── paper_hybrid │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_Hybrid.jsonl │ │ │ │ └── paper_hybrid_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_fill_rate.eps │ │ │ ├── paper_hybrid_fill_rate.html │ │ │ ├── paper_hybrid_fill_rate.js │ │ │ ├── paper_hybrid_fill_rate.pdf │ │ │ ├── paper_hybrid_fill_rate.png │ │ │ ├── paper_hybrid_fill_rate_static.png │ │ │ ├── paper_hybrid_speedup.eps │ │ │ ├── paper_hybrid_speedup.html │ │ │ ├── paper_hybrid_speedup.js │ │ │ ├── paper_hybrid_speedup.pdf │ │ │ ├── paper_hybrid_speedup.png │ │ │ └── paper_hybrid_speedup_static.png │ │ ├── paper_hybrid_filled │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_filled_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid_Filled.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid_Filled.jsonl │ │ │ │ └── paper_hybrid_filled_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_filled_fill_rate.eps │ │ │ ├── paper_hybrid_filled_fill_rate.html │ │ │ ├── paper_hybrid_filled_fill_rate.js │ │ │ ├── paper_hybrid_filled_fill_rate.pdf │ │ │ ├── paper_hybrid_filled_fill_rate.png │ │ │ ├── paper_hybrid_filled_fill_rate_static.png │ │ │ ├── paper_hybrid_filled_speedup.eps │ │ │ ├── paper_hybrid_filled_speedup.html │ │ │ ├── paper_hybrid_filled_speedup.js │ │ │ ├── paper_hybrid_filled_speedup.pdf │ │ │ ├── paper_hybrid_filled_speedup.png │ │ │ └── paper_hybrid_filled_speedup_static.png │ │ ├── paper_summary │ │ │ ├── logs │ │ │ │ ├── paper_summary_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid_Filled.jsonl │ │ │ │ ├── paper_summary_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_summary_speedup_BERT-base.jsonl │ │ │ │ ├── paper_summary_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid_Filled.jsonl │ │ │ │ └── paper_summary_speedup_TinyBERT.jsonl │ │ │ ├── paper_summary_fill_rate.eps │ │ │ ├── paper_summary_fill_rate.html │ │ │ ├── paper_summary_fill_rate.js │ │ │ ├── paper_summary_fill_rate.pdf │ │ │ ├── paper_summary_fill_rate.png │ │ │ ├── paper_summary_fill_rate_static.png │ │ │ ├── paper_summary_speedup.eps │ │ │ ├── paper_summary_speedup.html │ │ │ ├── paper_summary_speedup.js │ │ │ ├── paper_summary_speedup.pdf │ │ │ ├── paper_summary_speedup.png │ │ │ └── paper_summary_speedup_static.png │ │ ├── summary │ │ │ ├── logs │ │ │ │ ├── summary_fill_rate_DistilBERT.jsonl │ │ │ │ ├── summary_fill_rate_Hybrid_pruning__BERT-base.jsonl │ │ │ │ ├── summary_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── summary_fill_rate_Original_Soft_Movement.jsonl │ │ │ │ ├── summary_fill_rate_TinyBERT.jsonl │ │ │ │ ├── summary_speedup_DistilBERT.jsonl │ │ │ │ ├── summary_speedup_Hybrid_pruning__BERT-base.jsonl │ │ │ │ ├── summary_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── summary_speedup_Original_Soft_Movement.jsonl │ │ │ │ └── summary_speedup_TinyBERT.jsonl │ │ │ ├── summary_fill_rate.eps │ │ │ ├── summary_fill_rate.html │ │ │ ├── summary_fill_rate.js │ │ │ ├── summary_fill_rate.png │ │ │ ├── summary_fill_rate_static.png │ │ │ ├── summary_speedup.eps │ │ │ ├── summary_speedup.html │ │ │ ├── summary_speedup.js │ │ │ ├── summary_speedup.png │ │ │ └── summary_speedup_static.png │ │ └── summary_with_blocks │ │ │ ├── logs │ │ │ ├── summary_with_blocks_fill_rate_DistilBERT.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-base.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid_filled__BERT-base.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ ├── summary_with_blocks_fill_rate_Original_Soft_Movement.jsonl │ │ │ ├── summary_with_blocks_fill_rate_TinyBERT.jsonl │ │ │ ├── summary_with_blocks_speedup_DistilBERT.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-base.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid_filled__BERT-base.jsonl │ │ │ ├── summary_with_blocks_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ ├── summary_with_blocks_speedup_Original_Soft_Movement.jsonl │ │ │ └── summary_with_blocks_speedup_TinyBERT.jsonl │ │ │ ├── summary_with_blocks_fill_rate.eps │ │ │ ├── summary_with_blocks_fill_rate.html │ │ │ ├── summary_with_blocks_fill_rate.js │ │ │ ├── summary_with_blocks_fill_rate.png │ │ │ ├── summary_with_blocks_fill_rate_static.png │ │ │ ├── summary_with_blocks_speedup.eps │ │ │ ├── summary_with_blocks_speedup.html │ │ │ ├── summary_with_blocks_speedup.js │ │ │ ├── summary_with_blocks_speedup.png │ │ │ └── summary_with_blocks_speedup_static.png │ ├── qqp │ │ ├── paper_block_size_influence │ │ │ ├── logs │ │ │ │ ├── paper_block_size_influence_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Movement_Pruning.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Soft_Movement.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_BERT-base.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Movement_Pruning.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Soft_Movement.jsonl │ │ │ │ └── paper_block_size_influence_speedup_TinyBERT.jsonl │ │ │ ├── paper_block_size_influence_fill_rate.eps │ │ │ ├── paper_block_size_influence_fill_rate.html │ │ │ ├── paper_block_size_influence_fill_rate.js │ │ │ ├── paper_block_size_influence_fill_rate.pdf │ │ │ ├── paper_block_size_influence_fill_rate.png │ │ │ ├── paper_block_size_influence_fill_rate_static.png │ │ │ ├── paper_block_size_influence_speedup.eps │ │ │ ├── paper_block_size_influence_speedup.html │ │ │ ├── paper_block_size_influence_speedup.js │ │ │ ├── paper_block_size_influence_speedup.pdf │ │ │ ├── paper_block_size_influence_speedup.png │ │ │ └── paper_block_size_influence_speedup_static.png │ │ ├── paper_hybrid │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Movement_Pruning.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Soft_Movement.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_Movement_Pruning.jsonl │ │ │ │ ├── paper_hybrid_speedup_Soft_Movement.jsonl │ │ │ │ └── paper_hybrid_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_fill_rate.eps │ │ │ ├── paper_hybrid_fill_rate.html │ │ │ ├── paper_hybrid_fill_rate.js │ │ │ ├── paper_hybrid_fill_rate.pdf │ │ │ ├── paper_hybrid_fill_rate.png │ │ │ ├── paper_hybrid_fill_rate_static.png │ │ │ ├── paper_hybrid_speedup.eps │ │ │ ├── paper_hybrid_speedup.html │ │ │ ├── paper_hybrid_speedup.js │ │ │ ├── paper_hybrid_speedup.pdf │ │ │ ├── paper_hybrid_speedup.png │ │ │ └── paper_hybrid_speedup_static.png │ │ ├── paper_hybrid_filled │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_filled_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Movement_Pruning.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Soft_Movement.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Movement_Pruning.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Soft_Movement.jsonl │ │ │ │ └── paper_hybrid_filled_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_filled_fill_rate.eps │ │ │ ├── paper_hybrid_filled_fill_rate.html │ │ │ ├── paper_hybrid_filled_fill_rate.js │ │ │ ├── paper_hybrid_filled_fill_rate.pdf │ │ │ ├── paper_hybrid_filled_fill_rate.png │ │ │ ├── paper_hybrid_filled_fill_rate_static.png │ │ │ ├── paper_hybrid_filled_speedup.eps │ │ │ ├── paper_hybrid_filled_speedup.html │ │ │ ├── paper_hybrid_filled_speedup.js │ │ │ ├── paper_hybrid_filled_speedup.pdf │ │ │ ├── paper_hybrid_filled_speedup.png │ │ │ └── paper_hybrid_filled_speedup_static.png │ │ └── paper_summary │ │ │ ├── logs │ │ │ ├── paper_summary_fill_rate_DistilBERT.jsonl │ │ │ ├── paper_summary_fill_rate_Hybrid.jsonl │ │ │ ├── paper_summary_fill_rate_Hybrid_w_o_teacher.jsonl │ │ │ ├── paper_summary_fill_rate_Movement_Pruning.jsonl │ │ │ ├── paper_summary_fill_rate_Soft_Movement.jsonl │ │ │ ├── paper_summary_fill_rate_TinyBERT.jsonl │ │ │ ├── paper_summary_fill_rate_glue_experiment_bert.jsonl │ │ │ ├── paper_summary_fill_rate_glue_experiment_bert_teacher.jsonl │ │ │ ├── paper_summary_speedup_BERT-base.jsonl │ │ │ ├── paper_summary_speedup_DistilBERT.jsonl │ │ │ ├── paper_summary_speedup_Hybrid.jsonl │ │ │ ├── paper_summary_speedup_Hybrid_w_o_teacher.jsonl │ │ │ ├── paper_summary_speedup_Movement_Pruning.jsonl │ │ │ ├── paper_summary_speedup_Soft_Movement.jsonl │ │ │ ├── paper_summary_speedup_TinyBERT.jsonl │ │ │ ├── paper_summary_speedup_glue_experiment_bert.jsonl │ │ │ └── paper_summary_speedup_glue_experiment_bert_teacher.jsonl │ │ │ ├── paper_summary_fill_rate.eps │ │ │ ├── paper_summary_fill_rate.html │ │ │ ├── paper_summary_fill_rate.js │ │ │ ├── paper_summary_fill_rate.pdf │ │ │ ├── paper_summary_fill_rate.png │ │ │ ├── paper_summary_fill_rate_static.png │ │ │ ├── paper_summary_speedup.eps │ │ │ ├── paper_summary_speedup.html │ │ │ ├── paper_summary_speedup.js │ │ │ ├── paper_summary_speedup.pdf │ │ │ ├── paper_summary_speedup.png │ │ │ └── paper_summary_speedup_static.png │ ├── squadv1 │ │ ├── block_size_influence_basic │ │ │ ├── block_size_influence_basic_fill_rate.eps │ │ │ ├── block_size_influence_basic_fill_rate.html │ │ │ ├── block_size_influence_basic_fill_rate.js │ │ │ ├── block_size_influence_basic_fill_rate.png │ │ │ ├── block_size_influence_basic_fill_rate_static.png │ │ │ ├── block_size_influence_basic_speedup.eps │ │ │ ├── block_size_influence_basic_speedup.html │ │ │ ├── block_size_influence_basic_speedup.js │ │ │ ├── block_size_influence_basic_speedup.png │ │ │ ├── block_size_influence_basic_speedup_static.png │ │ │ └── logs │ │ │ │ ├── block_size_influence_basic_fill_rate_Block__bs__16x16.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Block__bs__32x32.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Block__bs__4x4.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Block__bs__8x8.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Hybrid__abs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Hybrid_filled__abs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_fill_rate_Unstructured_Soft_Movement_Pruning.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Block__bs__16x16.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Block__bs__32x32.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Block__bs__4x4.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Block__bs__8x8.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Hybrid__abs_32x32.jsonl │ │ │ │ ├── block_size_influence_basic_speedup_Hybrid_filled__abs_32x32.jsonl │ │ │ │ └── block_size_influence_basic_speedup_Unstructured_Soft_Movement_Pruning.jsonl │ │ ├── comparison_large_teacher │ │ │ ├── comparison_large_teacher_fill_rate.eps │ │ │ ├── comparison_large_teacher_fill_rate.html │ │ │ ├── comparison_large_teacher_fill_rate.js │ │ │ ├── comparison_large_teacher_fill_rate.png │ │ │ ├── comparison_large_teacher_fill_rate_static.png │ │ │ ├── comparison_large_teacher_speedup.eps │ │ │ ├── comparison_large_teacher_speedup.html │ │ │ ├── comparison_large_teacher_speedup.js │ │ │ ├── comparison_large_teacher_speedup.png │ │ │ ├── comparison_large_teacher_speedup_static.png │ │ │ └── logs │ │ │ │ ├── comparison_large_teacher_fill_rate_BERT-base_teacher.jsonl │ │ │ │ ├── comparison_large_teacher_fill_rate_BERT-large_teacher.jsonl │ │ │ │ ├── comparison_large_teacher_fill_rate_DistilBERT.jsonl │ │ │ │ ├── comparison_large_teacher_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── comparison_large_teacher_fill_rate_TinyBERT.jsonl │ │ │ │ ├── comparison_large_teacher_speedup_BERT-base_teacher.jsonl │ │ │ │ ├── comparison_large_teacher_speedup_BERT-large_teacher.jsonl │ │ │ │ ├── comparison_large_teacher_speedup_DistilBERT.jsonl │ │ │ │ ├── comparison_large_teacher_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ └── comparison_large_teacher_speedup_TinyBERT.jsonl │ │ ├── full_block_size_influence │ │ │ ├── full_block_size_influence_fill_rate.eps │ │ │ ├── full_block_size_influence_fill_rate.html │ │ │ ├── full_block_size_influence_fill_rate.js │ │ │ ├── full_block_size_influence_fill_rate.png │ │ │ ├── full_block_size_influence_fill_rate_static.png │ │ │ ├── full_block_size_influence_speedup.eps │ │ │ ├── full_block_size_influence_speedup.html │ │ │ ├── full_block_size_influence_speedup.js │ │ │ ├── full_block_size_influence_speedup.png │ │ │ ├── full_block_size_influence_speedup_static.png │ │ │ └── logs │ │ │ │ ├── full_block_size_influence_fill_rate_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Full_block__bs__16x16.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Full_block__bs__32x32.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Full_block__bs__4x4.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Full_block__bs__8x8.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Improved_soft_movement__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_Original_Soft_Movement.jsonl │ │ │ │ ├── full_block_size_influence_fill_rate_TinyBERT.jsonl │ │ │ │ ├── full_block_size_influence_speedup_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Full_block__bs__16x16.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Full_block__bs__32x32.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Full_block__bs__4x4.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Full_block__bs__8x8.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Improved_soft_movement__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_speedup_Original_Soft_Movement.jsonl │ │ │ │ └── full_block_size_influence_speedup_TinyBERT.jsonl │ │ ├── full_block_size_influence_raw │ │ │ ├── full_block_size_influence_raw_fill_rate.eps │ │ │ ├── full_block_size_influence_raw_fill_rate.html │ │ │ ├── full_block_size_influence_raw_fill_rate.js │ │ │ ├── full_block_size_influence_raw_fill_rate.png │ │ │ ├── full_block_size_influence_raw_fill_rate_static.png │ │ │ ├── full_block_size_influence_raw_speedup.eps │ │ │ ├── full_block_size_influence_raw_speedup.html │ │ │ ├── full_block_size_influence_raw_speedup.js │ │ │ ├── full_block_size_influence_raw_speedup.png │ │ │ ├── full_block_size_influence_raw_speedup_static.png │ │ │ └── logs │ │ │ │ ├── full_block_size_influence_raw_fill_rate_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Full_block_method__bs__8x8__dl_0.25.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Full_block_method__bs__8x8__dl_1.0.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Improved_soft_movement__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_Original_Soft_Movement.jsonl │ │ │ │ ├── full_block_size_influence_raw_fill_rate_TinyBERT.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_DistilBERT.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Full_block_method__bs__8x8__dl_0.25.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Full_block_method__bs__8x8__dl_1.0.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Hybrid__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Improved_soft_movement__BERT-base.jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── full_block_size_influence_raw_speedup_Original_Soft_Movement.jsonl │ │ │ │ └── full_block_size_influence_raw_speedup_TinyBERT.jsonl │ │ ├── paper_block_size_influence │ │ │ ├── logs │ │ │ │ ├── paper_block_size_influence_fill_rate_Block_Size_16.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Block_Size_32.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Block_Size_4.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Block_Size_8.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Mobile_Bert.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Movement.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_Soft_Movement.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_BERT-base.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Block_Size_16.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Block_Size_32.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Block_Size_4.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Block_Size_8.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_MobileBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Mobile_Bert.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Movement.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_Soft_Movement.jsonl │ │ │ │ └── paper_block_size_influence_speedup_TinyBERT.jsonl │ │ │ ├── paper_block_size_influence_fill_rate.eps │ │ │ ├── paper_block_size_influence_fill_rate.html │ │ │ ├── paper_block_size_influence_fill_rate.js │ │ │ ├── paper_block_size_influence_fill_rate.pdf │ │ │ ├── paper_block_size_influence_fill_rate.png │ │ │ ├── paper_block_size_influence_fill_rate_static.png │ │ │ ├── paper_block_size_influence_speedup.eps │ │ │ ├── paper_block_size_influence_speedup.html │ │ │ ├── paper_block_size_influence_speedup.js │ │ │ ├── paper_block_size_influence_speedup.pdf │ │ │ ├── paper_block_size_influence_speedup.png │ │ │ └── paper_block_size_influence_speedup_static.png │ │ ├── paper_hybrid │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Hybrid__large.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Hybrid_large__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Mobile_Bert.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Soft_Movement.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Soft_movement.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Structured.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_speedup_Hybrid__large.jsonl │ │ │ │ ├── paper_hybrid_speedup_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_speedup_Hybrid_large__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_speedup_MobileBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_Mobile_Bert.jsonl │ │ │ │ ├── paper_hybrid_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── paper_hybrid_speedup_Soft_Movement.jsonl │ │ │ │ ├── paper_hybrid_speedup_Soft_movement.jsonl │ │ │ │ ├── paper_hybrid_speedup_Structured.jsonl │ │ │ │ └── paper_hybrid_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_fill_rate.eps │ │ │ ├── paper_hybrid_fill_rate.html │ │ │ ├── paper_hybrid_fill_rate.js │ │ │ ├── paper_hybrid_fill_rate.pdf │ │ │ ├── paper_hybrid_fill_rate.png │ │ │ ├── paper_hybrid_fill_rate_static.png │ │ │ ├── paper_hybrid_speedup.eps │ │ │ ├── paper_hybrid_speedup.html │ │ │ ├── paper_hybrid_speedup.js │ │ │ ├── paper_hybrid_speedup.pdf │ │ │ ├── paper_hybrid_speedup.png │ │ │ └── paper_hybrid_speedup_static.png │ │ ├── paper_hybrid_filled │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_filled_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid_Filled.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid_Filled__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid_filled__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Soft_Movement.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid_Filled.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid_Filled__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid_filled__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_MobileBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Soft_Movement.jsonl │ │ │ │ └── paper_hybrid_filled_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_filled_fill_rate.eps │ │ │ ├── paper_hybrid_filled_fill_rate.html │ │ │ ├── paper_hybrid_filled_fill_rate.js │ │ │ ├── paper_hybrid_filled_fill_rate.pdf │ │ │ ├── paper_hybrid_filled_fill_rate.png │ │ │ ├── paper_hybrid_filled_fill_rate_static.png │ │ │ ├── paper_hybrid_filled_speedup.eps │ │ │ ├── paper_hybrid_filled_speedup.html │ │ │ ├── paper_hybrid_filled_speedup.js │ │ │ ├── paper_hybrid_filled_speedup.pdf │ │ │ ├── paper_hybrid_filled_speedup.png │ │ │ └── paper_hybrid_filled_speedup_static.png │ │ ├── paper_summary │ │ │ ├── logs │ │ │ │ ├── paper_summary_fill_rate_All_Block.jsonl │ │ │ │ ├── paper_summary_fill_rate_Block.jsonl │ │ │ │ ├── paper_summary_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid_Filled.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid_Filled_LT.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid_Filled__large_teacher.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_summary_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_summary_fill_rate_Movement.jsonl │ │ │ │ ├── paper_summary_fill_rate_Movement_Pruning.jsonl │ │ │ │ ├── paper_summary_fill_rate_Soft_Movement.jsonl │ │ │ │ ├── paper_summary_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_summary_speedup_All_Block.jsonl │ │ │ │ ├── paper_summary_speedup_BERT-base.jsonl │ │ │ │ ├── paper_summary_speedup_Block.jsonl │ │ │ │ ├── paper_summary_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid_Filled.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid_Filled_LT.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid_Filled__large_teacher.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_summary_speedup_MobileBERT.jsonl │ │ │ │ ├── paper_summary_speedup_Movement.jsonl │ │ │ │ ├── paper_summary_speedup_Movement_Pruning.jsonl │ │ │ │ ├── paper_summary_speedup_Soft_Movement.jsonl │ │ │ │ └── paper_summary_speedup_TinyBERT.jsonl │ │ │ ├── paper_summary_fill_rate.eps │ │ │ ├── paper_summary_fill_rate.html │ │ │ ├── paper_summary_fill_rate.js │ │ │ ├── paper_summary_fill_rate.pdf │ │ │ ├── paper_summary_fill_rate.png │ │ │ ├── paper_summary_fill_rate_static.png │ │ │ ├── paper_summary_speedup.eps │ │ │ ├── paper_summary_speedup.html │ │ │ ├── paper_summary_speedup.js │ │ │ ├── paper_summary_speedup.pdf │ │ │ ├── paper_summary_speedup.png │ │ │ └── paper_summary_speedup_static.png │ │ ├── summary │ │ │ ├── logs │ │ │ │ ├── summary_fill_rate_DistilBERT.jsonl │ │ │ │ ├── summary_fill_rate_Hybrid_filled__BERT-base__large_teacher.jsonl │ │ │ │ ├── summary_fill_rate_Hybrid_pruning__BERT-base.jsonl │ │ │ │ ├── summary_fill_rate_Hybrid_pruning__BERT-large.jsonl │ │ │ │ ├── summary_fill_rate_Improved_soft_movement__BERT-base.jsonl │ │ │ │ ├── summary_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── summary_fill_rate_Original_Soft_Movement.jsonl │ │ │ │ ├── summary_fill_rate_Structured_pruning__BERT-base.jsonl │ │ │ │ ├── summary_fill_rate_TinyBERT.jsonl │ │ │ │ ├── summary_speedup_DistilBERT.jsonl │ │ │ │ ├── summary_speedup_Hybrid_filled__BERT-base__large_teacher.jsonl │ │ │ │ ├── summary_speedup_Hybrid_pruning__BERT-base.jsonl │ │ │ │ ├── summary_speedup_Hybrid_pruning__BERT-large.jsonl │ │ │ │ ├── summary_speedup_Improved_soft_movement__BERT-base.jsonl │ │ │ │ ├── summary_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ │ ├── summary_speedup_Original_Soft_Movement.jsonl │ │ │ │ ├── summary_speedup_Structured_pruning__BERT-base.jsonl │ │ │ │ └── summary_speedup_TinyBERT.jsonl │ │ │ ├── summary_fill_rate.eps │ │ │ ├── summary_fill_rate.html │ │ │ ├── summary_fill_rate.js │ │ │ ├── summary_fill_rate.png │ │ │ ├── summary_fill_rate_static.png │ │ │ ├── summary_speedup.eps │ │ │ ├── summary_speedup.html │ │ │ ├── summary_speedup.js │ │ │ ├── summary_speedup.png │ │ │ └── summary_speedup_static.png │ │ └── summary_with_blocks │ │ │ ├── logs │ │ │ ├── summary_with_blocks_fill_rate_DistilBERT.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-base.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-base__large_teacher.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-base__large_teacher__Full_Patch.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-base__large_teacher__Full_Patch__Rewind.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-base__large_teacher__NoNorm.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-base__large_teacher__nonorm.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid__BERT-large.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid_filled__BERT-base.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid_filled__BERT-base__large_teacher.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Hybrid_filled__BERT-large.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Improved_soft_movement__BERT-base.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Mobile_Bert_(w_o_opt).jsonl │ │ │ ├── summary_with_blocks_fill_rate_Original_Soft_Movement.jsonl │ │ │ ├── summary_with_blocks_fill_rate_Structured_pruning__BERT-base.jsonl │ │ │ ├── summary_with_blocks_fill_rate_TinyBERT.jsonl │ │ │ ├── summary_with_blocks_speedup_DistilBERT.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-base.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-base__large_teacher.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-base__large_teacher__Full_Patch.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-base__large_teacher__Full_Patch__Rewind.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-base__large_teacher__NoNorm.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-base__large_teacher__nonorm.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid__BERT-large.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid_filled__BERT-base.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid_filled__BERT-base__large_teacher.jsonl │ │ │ ├── summary_with_blocks_speedup_Hybrid_filled__BERT-large.jsonl │ │ │ ├── summary_with_blocks_speedup_Improved_soft_movement__BERT-base.jsonl │ │ │ ├── summary_with_blocks_speedup_Mobile_Bert_(w_o_opt).jsonl │ │ │ ├── summary_with_blocks_speedup_Original_Soft_Movement.jsonl │ │ │ ├── summary_with_blocks_speedup_Structured_pruning__BERT-base.jsonl │ │ │ └── summary_with_blocks_speedup_TinyBERT.jsonl │ │ │ ├── summary_with_blocks_fill_rate.eps │ │ │ ├── summary_with_blocks_fill_rate.html │ │ │ ├── summary_with_blocks_fill_rate.js │ │ │ ├── summary_with_blocks_fill_rate.png │ │ │ ├── summary_with_blocks_fill_rate_static.png │ │ │ ├── summary_with_blocks_speedup.eps │ │ │ ├── summary_with_blocks_speedup.html │ │ │ ├── summary_with_blocks_speedup.js │ │ │ ├── summary_with_blocks_speedup.png │ │ │ └── summary_with_blocks_speedup_static.png │ ├── squadv2 │ │ ├── paper_block_size_influence │ │ │ ├── logs │ │ │ │ ├── paper_block_size_influence_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_block_size_influence_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_BERT-base.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_block_size_influence_speedup_MobileBERT.jsonl │ │ │ │ └── paper_block_size_influence_speedup_TinyBERT.jsonl │ │ │ ├── paper_block_size_influence_fill_rate.eps │ │ │ ├── paper_block_size_influence_fill_rate.html │ │ │ ├── paper_block_size_influence_fill_rate.js │ │ │ ├── paper_block_size_influence_fill_rate.pdf │ │ │ ├── paper_block_size_influence_fill_rate.png │ │ │ ├── paper_block_size_influence_fill_rate_static.png │ │ │ ├── paper_block_size_influence_speedup.eps │ │ │ ├── paper_block_size_influence_speedup.html │ │ │ ├── paper_block_size_influence_speedup.js │ │ │ ├── paper_block_size_influence_speedup.pdf │ │ │ ├── paper_block_size_influence_speedup.png │ │ │ └── paper_block_size_influence_speedup_static.png │ │ ├── paper_hybrid │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_hybrid_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_speedup_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_speedup_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_speedup_MobileBERT.jsonl │ │ │ │ └── paper_hybrid_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_fill_rate.eps │ │ │ ├── paper_hybrid_fill_rate.html │ │ │ ├── paper_hybrid_fill_rate.js │ │ │ ├── paper_hybrid_fill_rate.pdf │ │ │ ├── paper_hybrid_fill_rate.png │ │ │ ├── paper_hybrid_fill_rate_static.png │ │ │ ├── paper_hybrid_speedup.eps │ │ │ ├── paper_hybrid_speedup.html │ │ │ ├── paper_hybrid_speedup.js │ │ │ ├── paper_hybrid_speedup.pdf │ │ │ ├── paper_hybrid_speedup.png │ │ │ └── paper_hybrid_speedup_static.png │ │ ├── paper_hybrid_filled │ │ │ ├── logs │ │ │ │ ├── paper_hybrid_filled_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid_Filled.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_BERT-base.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid_Filled.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_hybrid_filled_speedup_MobileBERT.jsonl │ │ │ │ └── paper_hybrid_filled_speedup_TinyBERT.jsonl │ │ │ ├── paper_hybrid_filled_fill_rate.eps │ │ │ ├── paper_hybrid_filled_fill_rate.html │ │ │ ├── paper_hybrid_filled_fill_rate.js │ │ │ ├── paper_hybrid_filled_fill_rate.pdf │ │ │ ├── paper_hybrid_filled_fill_rate.png │ │ │ ├── paper_hybrid_filled_fill_rate_static.png │ │ │ ├── paper_hybrid_filled_speedup.eps │ │ │ ├── paper_hybrid_filled_speedup.html │ │ │ ├── paper_hybrid_filled_speedup.js │ │ │ ├── paper_hybrid_filled_speedup.pdf │ │ │ ├── paper_hybrid_filled_speedup.png │ │ │ └── paper_hybrid_filled_speedup_static.png │ │ ├── paper_summary │ │ │ ├── logs │ │ │ │ ├── paper_summary_fill_rate_DistilBERT.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid_Filled.jsonl │ │ │ │ ├── paper_summary_fill_rate_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_summary_fill_rate_MobileBERT.jsonl │ │ │ │ ├── paper_summary_fill_rate_Structured_Pruning.jsonl │ │ │ │ ├── paper_summary_fill_rate_TinyBERT.jsonl │ │ │ │ ├── paper_summary_speedup_BERT-base.jsonl │ │ │ │ ├── paper_summary_speedup_DistilBERT.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid_Filled.jsonl │ │ │ │ ├── paper_summary_speedup_Hybrid__large_teacher.jsonl │ │ │ │ ├── paper_summary_speedup_MobileBERT.jsonl │ │ │ │ ├── paper_summary_speedup_Structured_Pruning.jsonl │ │ │ │ └── paper_summary_speedup_TinyBERT.jsonl │ │ │ ├── paper_summary_fill_rate.eps │ │ │ ├── paper_summary_fill_rate.html │ │ │ ├── paper_summary_fill_rate.js │ │ │ ├── paper_summary_fill_rate.pdf │ │ │ ├── paper_summary_fill_rate.png │ │ │ ├── paper_summary_fill_rate_static.png │ │ │ ├── paper_summary_speedup.eps │ │ │ ├── paper_summary_speedup.html │ │ │ ├── paper_summary_speedup.js │ │ │ ├── paper_summary_speedup.pdf │ │ │ ├── paper_summary_speedup.png │ │ │ └── paper_summary_speedup_static.png │ │ └── paper_summary_backup │ │ │ ├── logs │ │ │ ├── paper_summary_fill_rate_DistilBERT.jsonl │ │ │ ├── paper_summary_fill_rate_Hybrid.jsonl │ │ │ ├── paper_summary_fill_rate_MobileBERT.jsonl │ │ │ ├── paper_summary_fill_rate_TinyBERT.jsonl │ │ │ ├── paper_summary_speedup_BERT-base.jsonl │ │ │ ├── paper_summary_speedup_DistilBERT.jsonl │ │ │ ├── paper_summary_speedup_Hybrid.jsonl │ │ │ ├── paper_summary_speedup_MobileBERT.jsonl │ │ │ └── paper_summary_speedup_TinyBERT.jsonl │ │ │ ├── paper_summary_fill_rate.eps │ │ │ ├── paper_summary_fill_rate.html │ │ │ ├── paper_summary_fill_rate.js │ │ │ ├── paper_summary_fill_rate.pdf │ │ │ ├── paper_summary_fill_rate.png │ │ │ ├── paper_summary_fill_rate_static.png │ │ │ ├── paper_summary_speedup.eps │ │ │ ├── paper_summary_speedup.html │ │ │ ├── paper_summary_speedup.js │ │ │ ├── paper_summary_speedup.pdf │ │ │ ├── paper_summary_speedup.png │ │ │ └── paper_summary_speedup_static.png │ └── sst2 │ │ ├── paper_block_size_influence │ │ ├── logs │ │ │ ├── paper_block_size_influence_fill_rate_DistilBERT.jsonl │ │ │ ├── paper_block_size_influence_fill_rate_MobileBERT.jsonl │ │ │ ├── paper_block_size_influence_fill_rate_TinyBERT.jsonl │ │ │ ├── paper_block_size_influence_speedup_BERT-base.jsonl │ │ │ ├── paper_block_size_influence_speedup_DistilBERT.jsonl │ │ │ ├── paper_block_size_influence_speedup_MobileBERT.jsonl │ │ │ └── paper_block_size_influence_speedup_TinyBERT.jsonl │ │ ├── paper_block_size_influence_fill_rate.eps │ │ ├── paper_block_size_influence_fill_rate.html │ │ ├── paper_block_size_influence_fill_rate.js │ │ ├── paper_block_size_influence_fill_rate.pdf │ │ ├── paper_block_size_influence_fill_rate.png │ │ ├── paper_block_size_influence_fill_rate_static.png │ │ ├── paper_block_size_influence_speedup.eps │ │ ├── paper_block_size_influence_speedup.html │ │ ├── paper_block_size_influence_speedup.js │ │ ├── paper_block_size_influence_speedup.pdf │ │ ├── paper_block_size_influence_speedup.png │ │ └── paper_block_size_influence_speedup_static.png │ │ ├── paper_hybrid │ │ ├── logs │ │ │ ├── paper_hybrid_fill_rate_DistilBERT.jsonl │ │ │ ├── paper_hybrid_fill_rate_MobileBERT.jsonl │ │ │ ├── paper_hybrid_fill_rate_TinyBERT.jsonl │ │ │ ├── paper_hybrid_speedup_BERT-base.jsonl │ │ │ ├── paper_hybrid_speedup_DistilBERT.jsonl │ │ │ ├── paper_hybrid_speedup_MobileBERT.jsonl │ │ │ └── paper_hybrid_speedup_TinyBERT.jsonl │ │ ├── paper_hybrid_fill_rate.eps │ │ ├── paper_hybrid_fill_rate.html │ │ ├── paper_hybrid_fill_rate.js │ │ ├── paper_hybrid_fill_rate.pdf │ │ ├── paper_hybrid_fill_rate.png │ │ ├── paper_hybrid_fill_rate_static.png │ │ ├── paper_hybrid_speedup.eps │ │ ├── paper_hybrid_speedup.html │ │ ├── paper_hybrid_speedup.js │ │ ├── paper_hybrid_speedup.pdf │ │ ├── paper_hybrid_speedup.png │ │ └── paper_hybrid_speedup_static.png │ │ ├── paper_hybrid_filled │ │ ├── logs │ │ │ ├── paper_hybrid_filled_fill_rate_DistilBERT.jsonl │ │ │ ├── paper_hybrid_filled_fill_rate_MobileBERT.jsonl │ │ │ ├── paper_hybrid_filled_fill_rate_TinyBERT.jsonl │ │ │ ├── paper_hybrid_filled_speedup_BERT-base.jsonl │ │ │ ├── paper_hybrid_filled_speedup_DistilBERT.jsonl │ │ │ ├── paper_hybrid_filled_speedup_MobileBERT.jsonl │ │ │ └── paper_hybrid_filled_speedup_TinyBERT.jsonl │ │ ├── paper_hybrid_filled_fill_rate.eps │ │ ├── paper_hybrid_filled_fill_rate.html │ │ ├── paper_hybrid_filled_fill_rate.js │ │ ├── paper_hybrid_filled_fill_rate.pdf │ │ ├── paper_hybrid_filled_fill_rate.png │ │ ├── paper_hybrid_filled_fill_rate_static.png │ │ ├── paper_hybrid_filled_speedup.eps │ │ ├── paper_hybrid_filled_speedup.html │ │ ├── paper_hybrid_filled_speedup.js │ │ ├── paper_hybrid_filled_speedup.pdf │ │ ├── paper_hybrid_filled_speedup.png │ │ └── paper_hybrid_filled_speedup_static.png │ │ └── paper_summary │ │ ├── logs │ │ ├── paper_summary_fill_rate_DistilBERT.jsonl │ │ ├── paper_summary_fill_rate_Hybrid.jsonl │ │ ├── paper_summary_fill_rate_Hybrid_w_o_teacher.jsonl │ │ ├── paper_summary_fill_rate_MobileBERT.jsonl │ │ ├── paper_summary_fill_rate_TinyBERT.jsonl │ │ ├── paper_summary_speedup_BERT-base.jsonl │ │ ├── paper_summary_speedup_DistilBERT.jsonl │ │ ├── paper_summary_speedup_Hybrid.jsonl │ │ ├── paper_summary_speedup_Hybrid_w_o_teacher.jsonl │ │ ├── paper_summary_speedup_MobileBERT.jsonl │ │ └── paper_summary_speedup_TinyBERT.jsonl │ │ ├── paper_summary_fill_rate.eps │ │ ├── paper_summary_fill_rate.html │ │ ├── paper_summary_fill_rate.js │ │ ├── paper_summary_fill_rate.pdf │ │ ├── paper_summary_fill_rate.png │ │ ├── paper_summary_fill_rate_static.png │ │ ├── paper_summary_speedup.eps │ │ ├── paper_summary_speedup.html │ │ ├── paper_summary_speedup.js │ │ ├── paper_summary_speedup.pdf │ │ ├── paper_summary_speedup.png │ │ └── paper_summary_speedup_static.png ├── model_card_graphics.py ├── plot.py ├── plot_data.py └── tests │ └── test_speed.py ├── docs ├── HOWTO.md ├── README.md ├── RESEARCH_REPORT.md ├── _config.yml ├── assets │ ├── css │ │ └── style.scss │ └── media │ │ ├── mnli │ │ └── graphs │ │ │ ├── summary_fill_rate.html │ │ │ ├── summary_fill_rate.js │ │ │ ├── summary_fill_rate.png │ │ │ ├── summary_fill_rate_static.png │ │ │ ├── summary_speedup.html │ │ │ ├── summary_speedup.js │ │ │ ├── summary_speedup.png │ │ │ └── summary_speedup_static.png │ │ └── squadv1 │ │ ├── graphs │ │ ├── summary_fill_rate.html │ │ ├── summary_fill_rate.js │ │ ├── summary_fill_rate.png │ │ ├── summary_fill_rate_static.png │ │ ├── summary_speedup.html │ │ ├── summary_speedup.js │ │ ├── summary_speedup.png │ │ └── summary_speedup_static.png │ │ └── models │ │ └── network_filled │ │ ├── density_info.html │ │ ├── density_info.js │ │ ├── density_info.png │ │ ├── pruning_info.html │ │ ├── pruning_info.js │ │ └── pruning_info.png └── src │ ├── build.py │ └── files │ ├── README.jinja.md │ ├── RESEARCH_REPORT.jinja.md │ ├── reference_mnli.jsonl │ ├── reference_squadv1.jsonl │ ├── results_mnli.jsonl │ └── results_squadv1.jsonl ├── examples ├── README.md ├── command_line.py ├── question_answering │ ├── launch_qa_sparse.py │ ├── launch_qa_sparse_single.py │ ├── parameters.json │ ├── parameters_test.json │ ├── qa_sparse_train.py │ ├── qa_sparse_xp.py │ ├── qa_train.py │ ├── qa_utils.py │ ├── qa_xp.py │ └── requirements.txt ├── seq2seq │ ├── seq2seq_sparse_train.py │ ├── seq2seq_train.py │ ├── summarization_sparse_xp.py │ ├── summarization_xp.py │ ├── translation_sparse_xp.py │ └── translation_xp.py ├── text_classification │ ├── glue_sparse_train.py │ ├── glue_sparse_xp.py │ ├── glue_train.py │ ├── glue_xp.py │ ├── launch_glue_sparse.py │ └── parameters.json └── xp.py ├── nn_pruning ├── __init__.py ├── hp_naming.py ├── inference_model_patcher.py ├── model_patcher.py ├── model_structure.py ├── modules │ ├── AmpereRework.ipynb │ ├── binarizer.py │ ├── gelu2relu.py │ ├── masked_nn.py │ ├── nonorm.py │ ├── quantization.py │ └── quantization_config.py ├── patch_coordinator.py ├── sparse_trainer.py ├── sparse_xp.py ├── tests │ ├── __init__.py │ ├── test_patch.py │ ├── test_patch2.py │ └── test_quantization.py └── training_patcher.py ├── notebooks ├── 00-using-pruned-transformers.ipynb ├── 01-sparse-trainer.ipynb └── Quantization.ipynb ├── pyproject.toml └── setup.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Compiled python modules. 2 | *.pyc 3 | *.pyo 4 | 5 | # Setuptools distribution folder. 6 | /dist/ 7 | /build/ 8 | 9 | # Python egg metadata, regenerated from source files by setuptools. 10 | /*.egg-info 11 | /*.egg 12 | 13 | # emacs Files 14 | *~ 15 | 16 | # Python cache files 17 | __pycache__/ 18 | 19 | # Jupyter Notebook 20 | .ipynb_checkpoints 21 | 22 | # wandb information directory 23 | wandb 24 | 25 | # backup directories 26 | back -------------------------------------------------------------------------------- /.isort.cfg: -------------------------------------------------------------------------------- 1 | [settings] 2 | multi_line_output=3 3 | include_trailing_comma=True 4 | 5 | -------------------------------------------------------------------------------- /MANIFEST.in: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/huggingface/nn_pruning/0cef2b2435d575f141feb12885f632b173df8f93/MANIFEST.in -------------------------------------------------------------------------------- /Makefile: -------------------------------------------------------------------------------- 1 | .PHONY: style test 2 | 3 | # Run code quality checks 4 | style: 5 | black . 6 | isort . 7 | 8 | # Run tests for the library 9 | test: 10 | python -m pytest nn_pruning 11 | 12 | build_dist: 13 | rm -fr build 14 | rm -fr dist 15 | python -m build 16 | 17 | pypi_upload: build_dist 18 | python -m twine upload dist/* 19 | -------------------------------------------------------------------------------- /analysis/README.md: -------------------------------------------------------------------------------- 1 | # Analyzing experiments results 2 | 3 | This directory contains research tools to: 4 | - 1/ download experiments from AWS SageMaker S3 bucket and unpack them 5 | - 2/ upload the locally produced checkpoints and those unpacked from Sagemaker to the nn_pruning AWS S3 bucket 6 | - 3/ extract information about produced models 7 | - 4/ clean unused checkpoints 8 | - 5/ plot sparsity/accuracy and speed/accuracy graphs 9 | - 6/ upload the best models to the Hugging Face model hub. 10 | 11 | All those commands are available running `command_line.py` (use `--help` to display the details of these commands). 12 | 13 | ## 1/ Downloading models from Amazon SageMaker S3 buckets 14 | 15 | ## 2/ Upload the locally produced checkpoints 16 | 17 | ## 3/ Scanning runs and their checkpoints to produce reports 18 | When running multiple experiments, a lot of checkpoints are produced. 19 | The `analyze` command will scan all the checkpoints information, extract the best ones according to their metrics, extract information about their sparsity, check their accuracy after "compilation", and measure the speed of the model. 20 | ('Compiling' a model means applying once and for all the pruning pattern on the weights, and create a model that has the exact layout as the original one, but with some zeroes at some places) 21 | The results are written by default to files/results_{TASK_NAME}.json . 22 | Some information about the 23 | 24 | ## Creating graphs 25 | 26 | ## Uploading models to the hub with rich model cards 27 | 28 | ## Cleaning unused checkpoints 29 | 30 | -------------------------------------------------------------------------------- /analysis/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/huggingface/nn_pruning/0cef2b2435d575f141feb12885f632b173df8f93/analysis/__init__.py -------------------------------------------------------------------------------- /analysis/article/results_json_rewrite.py: -------------------------------------------------------------------------------- 1 | from pathlib import Path 2 | import json 3 | import copy 4 | 5 | LOCAL_PREFIX="/data_2to/devel_data/" 6 | URL_PREFIX="s3://lagunas-sparsity-experiments/backup/" 7 | 8 | def rewrite(src, dest): 9 | with src.open() as f_in: 10 | j = json.load(f_in) 11 | dest_j = copy.deepcopy(j) 12 | del dest_j["checkpoints"] 13 | dest_j["checkpoints"] = {} 14 | for k,v in j["checkpoints"].items(): 15 | new_k = k.replace(LOCAL_PREFIX, URL_PREFIX) 16 | assert(new_k != k) 17 | dest_j["checkpoints"][new_k] = v 18 | 19 | dest_file = (dest / src.name) 20 | print(dest_file) 21 | with dest_file.open("w") as f_out: 22 | json.dump(dest_j, f_out, sort_keys=True, indent = 4) 23 | 24 | def main(): 25 | path = Path(__file__).parent.parent / "files" 26 | dest = Path(__file__).parent / "files" 27 | if not dest.exists(): 28 | dest.mkdir() 29 | 30 | for f in path.iterdir(): 31 | if f.name.startswith("results_") and f.name.endswith(".json"): 32 | rewrite(f, dest) 33 | 34 | 35 | if __name__ == "__main__": 36 | main() -------------------------------------------------------------------------------- /analysis/cache/bert_mnli.json: -------------------------------------------------------------------------------- 1 | { 2 | "bert": [ 3 | { 4 | "annotate": "BERT", 5 | "fill_rate": 1.0, 6 | "matched": 84.6, 7 | "mismatched": 83.4, 8 | "speedup": 1 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/bert_qqp.json: -------------------------------------------------------------------------------- 1 | { 2 | "bert": [ 3 | { 4 | "accuracy": 91.15, 5 | "annotate": "BERT", 6 | "f1": 88.12, 7 | "fill_rate": 1.0, 8 | "speedup": 1 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/bert_squadv1.json: -------------------------------------------------------------------------------- 1 | { 2 | "bert": [ 3 | { 4 | "annotate": "BERT", 5 | "exact": 80.8, 6 | "f1": 88.5, 7 | "fill_rate": 1.0, 8 | "speedup": 1 9 | } 10 | ], 11 | "bert_large": [ 12 | { 13 | "annotate": "BERT-large", 14 | "fill_rate": 2.0, 15 | "speedup": 0.3221111545868855 16 | } 17 | ] 18 | } -------------------------------------------------------------------------------- /analysis/cache/bert_squadv2.json: -------------------------------------------------------------------------------- 1 | { 2 | "bert": [ 3 | { 4 | "annotate": "BERT", 5 | "exact": 73.85, 6 | "f1": 76.7, 7 | "fill_rate": 1.0, 8 | "speedup": 1 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/bert_sst2.json: -------------------------------------------------------------------------------- 1 | { 2 | "bert": [ 3 | { 4 | "accuracy": 92.66, 5 | "annotate": "BERT", 6 | "fill_rate": 1.0, 7 | "speedup": 1 8 | } 9 | ] 10 | } -------------------------------------------------------------------------------- /analysis/cache/distilbert_mnli.json: -------------------------------------------------------------------------------- 1 | { 2 | "distilbert": [ 3 | { 4 | "annotate": "DistilBERT", 5 | "fill_rate": 0.5034571936567231, 6 | "matched": 82.2, 7 | "speedup": 2.0609917530867805 8 | } 9 | ] 10 | } -------------------------------------------------------------------------------- /analysis/cache/distilbert_qqp.json: -------------------------------------------------------------------------------- 1 | { 2 | "distilbert": [ 3 | { 4 | "accuracy": 88.5, 5 | "annotate": "DistilBERT", 6 | "fill_rate": 0.5034571936567231, 7 | "speedup": 2.0609917530867805 8 | } 9 | ] 10 | } -------------------------------------------------------------------------------- /analysis/cache/distilbert_squadv1.json: -------------------------------------------------------------------------------- 1 | { 2 | "distilbert": [ 3 | { 4 | "annotate": "DistilBERT", 5 | "exact": 79.1, 6 | "f1": 86.9, 7 | "fill_rate": 0.5, 8 | "speedup": 2.0609917530867805 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/distilbert_squadv2.json: -------------------------------------------------------------------------------- 1 | { 2 | "distilbert": [ 3 | { 4 | "annotate": "DistilBERT", 5 | "exact": 64.88976637051661, 6 | "f1": 68.1776176526635, 7 | "fill_rate": 0.5, 8 | "speedup": 2.0609917530867805 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/distilbert_sst2.json: -------------------------------------------------------------------------------- 1 | { 2 | "distilbert": [ 3 | { 4 | "accuracy": 91.3, 5 | "annotate": "DistilBERT", 6 | "fill_rate": 0.5034571936567231, 7 | "speedup": 2.0609917530867805 8 | } 9 | ] 10 | } -------------------------------------------------------------------------------- /analysis/cache/glueexperiments_mnli.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/glueexperiments_squadv1.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/glueexperiments_squadv2.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/mobilebert_mnli.json: -------------------------------------------------------------------------------- 1 | { 2 | "mobile_bert_no_opt": [ 3 | { 4 | "annotate": "MobileBERT w/o opt", 5 | "fill_rate": 0.25333333333333335, 6 | "matched": 84.3, 7 | "mismatched": 83.4, 8 | "speedup": 1.78125 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/mobilebert_qqp.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/mobilebert_squadv1.json: -------------------------------------------------------------------------------- 1 | { 2 | "mobile_bert_measured": [ 3 | { 4 | "annotate": "MobileBERT", 5 | "exact": 82.9, 6 | "f1": 90.0, 7 | "fill_rate": 0.25333333333333335, 8 | "speedup": 1.612951511916643 9 | } 10 | ], 11 | "mobile_bert_no_opt": [ 12 | { 13 | "annotate": "MobileBERT w/o opt", 14 | "exact": 83.4, 15 | "f1": 90.3, 16 | "fill_rate": 0.25333333333333335, 17 | "speedup": 1.78125 18 | } 19 | ] 20 | } -------------------------------------------------------------------------------- /analysis/cache/mobilebert_squadv2.json: -------------------------------------------------------------------------------- 1 | { 2 | "mobile_bert_measured": [ 3 | { 4 | "annotate": "MobileBERT", 5 | "exact": 76.2, 6 | "f1": 79.2, 7 | "fill_rate": 0.25333333333333335, 8 | "speedup": 1.612951511916643 9 | } 10 | ], 11 | "mobile_bert_no_opt": [ 12 | { 13 | "annotate": "MobileBERT w/o opt", 14 | "exact": 77.6, 15 | "f1": 80.2, 16 | "fill_rate": 0.25333333333333335, 17 | "speedup": 1.78125 18 | } 19 | ] 20 | } -------------------------------------------------------------------------------- /analysis/cache/mobilebert_sst2.json: -------------------------------------------------------------------------------- 1 | { 2 | } -------------------------------------------------------------------------------- /analysis/cache/movementpruning_squadv2.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/movementpruning_sst2.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/structuredpruningofbert_mnli.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/structuredpruningofbert_qqp.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/structuredpruningofbert_squadv1.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/structuredpruningofbert_squadv2.json: -------------------------------------------------------------------------------- 1 | { 2 | "structured_pruning": [ 3 | { 4 | "f1": 84.6, 5 | "fill_rate": 1.0, 6 | "speedup": 0.375 7 | }, 8 | { 9 | "f1": 84.2, 10 | "fill_rate": 0.9114, 11 | "speedup": 0.44449300699300703 12 | }, 13 | { 14 | "f1": 83.2, 15 | "fill_rate": 0.6152, 16 | "speedup": 0.4835948644793152 17 | }, 18 | { 19 | "f1": 83.7, 20 | "fill_rate": 0.5272, 21 | "speedup": 0.6100779844031194 22 | }, 23 | { 24 | "f1": 83.2, 25 | "fill_rate": 0.37459999999999993, 26 | "speedup": 0.7311286843997125 27 | }, 28 | { 29 | "f1": 82.4, 30 | "fill_rate": 0.2951999999999999, 31 | "speedup": 0.8384171475680131 32 | }, 33 | { 34 | "f1": 81.5, 35 | "fill_rate": 0.25259999999999994, 36 | "speedup": 0.9015957446808511 37 | } 38 | ] 39 | } -------------------------------------------------------------------------------- /analysis/cache/structuredpruningofbert_sst2.json: -------------------------------------------------------------------------------- 1 | {} -------------------------------------------------------------------------------- /analysis/cache/tinybert_mnli.json: -------------------------------------------------------------------------------- 1 | { 2 | "tinybert": [ 3 | { 4 | "annotate": "TinyBERT6", 5 | "fill_rate": 0.5, 6 | "matched": 84.6, 7 | "mismatched": 83.2, 8 | "speedup": 1.8799112593179124 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/tinybert_qqp.json: -------------------------------------------------------------------------------- 1 | { 2 | "tinybert": [ 3 | { 4 | "accuracy": 91.1, 5 | "annotate": "TinyBERT6", 6 | "f1": 88.0, 7 | "fill_rate": 0.5, 8 | "speedup": 1.8799112593179124 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/tinybert_squadv1.json: -------------------------------------------------------------------------------- 1 | { 2 | "tinybert": [ 3 | { 4 | "annotate": "TinyBERT6", 5 | "exact": 79.7, 6 | "f1": 87.5, 7 | "fill_rate": 0.5, 8 | "speedup": 1.8799112593179124 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/tinybert_squadv2.json: -------------------------------------------------------------------------------- 1 | { 2 | "tinybert": [ 3 | { 4 | "annotate": "TinyBERT6", 5 | "exact": 74.7, 6 | "f1": 77.7, 7 | "fill_rate": 0.5, 8 | "speedup": 1.8799112593179124 9 | } 10 | ] 11 | } -------------------------------------------------------------------------------- /analysis/cache/tinybert_sst2.json: -------------------------------------------------------------------------------- 1 | { 2 | "tinybert": [ 3 | { 4 | "accuracy": 93.0, 5 | "annotate": "TinyBERT6", 6 | "fill_rate": 0.5, 7 | "speedup": 1.8799112593179124 8 | } 9 | ] 10 | } -------------------------------------------------------------------------------- /analysis/checkpoints/checkpoints.old3.jsonl: -------------------------------------------------------------------------------- 1 | {'speedup': 1.0188259739389196, 'f1': 89.04987146464723, 'meta': {'fill_rate': 0.12083943684895837, 'f1': 89.04987146464723, 'speedup': 1.0188259739389196, 'annotate': 'l=(10, 1.0, 1.0)', 'path': '/data_2to/devel_data/nn_pruning/output/squad_test_large/large_regu_10/checkpoint-221320'}} 2 | 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-------------------------------------------------------------------------------- /analysis/files/base_speed_report_file_squadv2.json: -------------------------------------------------------------------------------- 1 | {"eval_elapsed_time": 48.512564, "cuda_eval_elapsed_time": 44.131452} -------------------------------------------------------------------------------- /analysis/files/mvmt_pruning.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/huggingface/nn_pruning/0cef2b2435d575f141feb12885f632b173df8f93/analysis/files/mvmt_pruning.xlsx -------------------------------------------------------------------------------- /analysis/graph_util.py: -------------------------------------------------------------------------------- 1 | import bokeh.plotting as plotting 2 | import bokeh.models 3 | from bokeh.resources import CDN 4 | from bokeh.embed import autoload_static 5 | 6 | class BokehHelper: 7 | def __init__(self, div_id, js_path): 8 | self.div_id = div_id 9 | self.js_path = js_path 10 | 11 | def create_fig(self, *args, **kwargs): 12 | raise RuntimeError("Please implement in subclass") 13 | 14 | def run(self, *args, show=False, **kwargs): 15 | # html = file_html(self.fig, CDN, self.div_id) 16 | if show: 17 | plotting.output_notebook() 18 | fig = self.create_fig(*args, **kwargs) 19 | 20 | if show: 21 | bokeh.plotting.show(fig) 22 | else: 23 | js, tag = autoload_static(fig, CDN, self.js_path) 24 | return fig, js, tag 25 | 26 | 27 | class SamplePlotter(BokehHelper): 28 | def __init__(self): 29 | super().__init__("main_graph", "$$JS_SOURCE$$") 30 | 31 | def create_fig(self): 32 | # prepare some data 33 | x = [1, 2, 3, 4, 5] 34 | y = [6, 7, 2, 4, 5] 35 | 36 | # output to static HTML file 37 | # output_notebook() 38 | 39 | # create a new plot with a title and axis labels 40 | fig = bokeh.plotting.figure(title="simple line example", x_axis_label='x', y_axis_label='y', sizing_mode='scale_width') 41 | 42 | # add a line renderer with legend and line thickness 43 | fig.line(x, y, legend_label="Temp.", line_width=2) 44 | # add a line renderer with legend and line thickness 45 | fig.line(y, x, legend_label="Temp 2.", line_width=2) 46 | 47 | fig.legend.click_policy = "hide" 48 | return fig 49 | -------------------------------------------------------------------------------- /analysis/graphs/mnli/block_size_influence_basic/block_size_influence_basic_fill_rate.html: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /analysis/graphs/mnli/block_size_influence_basic/block_size_influence_basic_fill_rate.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/huggingface/nn_pruning/0cef2b2435d575f141feb12885f632b173df8f93/analysis/graphs/mnli/block_size_influence_basic/block_size_influence_basic_fill_rate.png 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/examples/question_answering/launch_qa_sparse.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import copy 3 | 4 | def main(): 5 | import json 6 | from pathlib import Path 7 | import sys 8 | 9 | sys.path += ["."] 10 | 11 | import examples.question_answering.qa_sparse_xp as qa_sparse_xp 12 | 13 | if len(sys.argv) < 2: 14 | raise RuntimeError("Please specify json file") 15 | filename = Path(sys.argv[1]).resolve() 16 | param_dict = json.load(open(filename)) 17 | 18 | # variants = [{"dense_lambda":1.0, "regularization_final_lambda": 20}] 19 | # for variant in variants: 20 | # param_dict_ = copy.deepcopy(param_dict) 21 | # param_dict_.update(variant) 22 | qa = qa_sparse_xp.QASparseXP(param_dict) 23 | 24 | def hp_space(trial): 25 | return {} 26 | 27 | qa.hyperparameter_search(direction="minimize", hp_space=hp_space, n_trials=1) 28 | 29 | if __name__ == "__main__": 30 | main() 31 | -------------------------------------------------------------------------------- /examples/question_answering/launch_qa_sparse_single.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import copy 3 | 4 | def main(): 5 | import json 6 | from pathlib import Path 7 | 8 | if len(sys.argv) < 2: 9 | raise RuntimeError("Please specify json file") 10 | filename = Path(sys.argv[1]).resolve() 11 | param_dict = json.load(open(filename)) 12 | 13 | import examples.question_answering.qa_sparse_xp as qa_sparse_xp 14 | 15 | qa = qa_sparse_xp.QASparseXP(param_dict) 16 | qa.run() 17 | 18 | 19 | 20 | def _mp_fn(index): 21 | # For xla_spawn (TPUs) 22 | main() 23 | 24 | 25 | if __name__ == "__main__": 26 | main() 27 | -------------------------------------------------------------------------------- /examples/question_answering/parameters.json: -------------------------------------------------------------------------------- 1 | { 2 | "model_name_or_path": "bert-base-uncased", 3 | "dataset_name": "squad", 4 | "do_train": 1, 5 | "do_eval": 1, 6 | "per_device_train_batch_size": 16, 7 | "max_seq_length": 384, 8 | "doc_stride": 128, 9 | "num_train_epochs": 20, 10 | "logging_steps": 250, 11 | "save_steps": 5000, 12 | "eval_steps": 5000, 13 | "save_total_limit": 50, 14 | "seed": 17, 15 | "evaluation_strategy": "steps", 16 | "learning_rate": 3e-5, 17 | "mask_scores_learning_rate": 1e-2, 18 | "output_dir": "/data_2to/devel_data/nn_pruning/output/squad_test_8_mvp_lt/", 19 | "logging_dir": "/data_2to/devel_data/nn_pruning/output/squad_test_8_mvp_lt/", 20 | "overwrite_cache": 0, 21 | "overwrite_output_dir": 1, 22 | "warmup_steps": 5400, 23 | "initial_warmup": 1, 24 | "final_warmup": 10, 25 | "initial_threshold": 0, 26 | "final_threshold": 0.1, 27 | "dense_pruning_method": "sigmoied_threshold", 28 | "dense_block_rows":1, 29 | "dense_block_cols":1, 30 | "dense_lambda":1.0, 31 | "attention_pruning_method": "sigmoied_threshold", 32 | "attention_block_rows":1, 33 | "attention_block_cols":1, 34 | "attention_lambda":1.0, 35 | "ampere_pruning_method": "sigmoied_threshold", 36 | "mask_init": "constant", 37 | "mask_scale": 0.0, 38 | "regularization": "l1", 39 | "regularization_final_lambda": 20, 40 | "distil_teacher_name_or_path":"bert-large-uncased-whole-word-masking-finetuned-squad", 41 | "distil_alpha_ce": 0.1, 42 | "distil_alpha_teacher": 0.9, 43 | "attention_output_with_dense": 0, 44 | "layer_norm_patch" : 0, 45 | "gelu_patch":0 46 | } 47 | -------------------------------------------------------------------------------- /examples/question_answering/parameters_test.json: -------------------------------------------------------------------------------- 1 | { 2 | "model_name_or_path": "bert-base-uncased", 3 | "dataset_name": "squad", 4 | "do_train": 1, 5 | "do_eval": 1, 6 | "per_device_train_batch_size": 1, 7 | "max_seq_length": 384, 8 | "doc_stride": 128, 9 | "num_train_epochs": 20, 10 | "logging_steps": 25, 11 | "save_steps": 50, 12 | "save_total_limit": 5, 13 | "eval_steps": 50, 14 | "seed": 17, 15 | "evaluation_strategy": "steps", 16 | "learning_rate": 3e-5, 17 | "mask_scores_learning_rate": 1e-2, 18 | "output_dir": "output/squad_test", 19 | "logging_dir": "output/squad_test", 20 | "overwrite_cache": 0, 21 | "overwrite_output_dir": 1, 22 | "warmup_steps": 5400, 23 | "initial_warmup": 0, 24 | "final_warmup": 10, 25 | "initial_threshold": 0, 26 | "final_threshold": 0.1, 27 | "dense_pruning_method": "sigmoied_threshold:1d_alt", 28 | "dense_block_rows":1, 29 | "dense_block_cols":1, 30 | "attention_pruning_method": "sigmoied_threshold", 31 | "attention_block_rows":32, 32 | "attention_block_cols":32, 33 | "ampere_pruning_method": "sigmoied_threshold", 34 | "mask_init": "constant", 35 | "mask_scale": 0.0, 36 | "regularization": "l1", 37 | "regularization_final_lambda": 20.0, 38 | "distil_teacher_name_or_path":"csarron/bert-base-uncased-squad-v1", 39 | "distil_alpha_ce": 0.1, 40 | "distil_alpha_teacher": 0.9 41 | } -------------------------------------------------------------------------------- /examples/question_answering/qa_sparse_train.py: -------------------------------------------------------------------------------- 1 | # coding=utf-8 2 | # Copyright 2020 The HuggingFace Team All rights reserved. 3 | # 4 | # Licensed under the Apache License, Version 2.0 (the "License"); 5 | # you may not use this file except in compliance with the License. 6 | # You may obtain a copy of the License at 7 | # 8 | # http://www.apache.org/licenses/LICENSE-2.0 9 | # 10 | # Unless required by applicable law or agreed to in writing, software 11 | # distributed under the License is distributed on an "AS IS" BASIS, 12 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 | # See the License for the specific language governing permissions and 14 | # limitations under the License. 15 | """ 16 | Sparse Fine-tuning the library models for question answering. 17 | """ 18 | # You can also adapt this script on your own question answering task. Pointers for this are left as comments. 19 | 20 | from nn_pruning.sparse_trainer import SparseTrainer 21 | from .qa_train import QATrainer 22 | 23 | # SparseTrainer should appear first in the base classes, as its functions must override QATrainer and its base classes (Trainer) 24 | class QASparseTrainer(SparseTrainer, QATrainer): 25 | def __init__(self, sparse_args, *args, **kwargs): 26 | QATrainer.__init__(self, *args, **kwargs) 27 | SparseTrainer.__init__(self, sparse_args) 28 | -------------------------------------------------------------------------------- /examples/question_answering/requirements.txt: -------------------------------------------------------------------------------- 1 | datasets >= 1.1.3 2 | -------------------------------------------------------------------------------- /examples/seq2seq/seq2seq_sparse_train.py: -------------------------------------------------------------------------------- 1 | # coding=utf-8 2 | # Copyright 2020 The HuggingFace Team All rights reserved. 3 | # 4 | # Licensed under the Apache License, Version 2.0 (the "License"); 5 | # you may not use this file except in compliance with the License. 6 | # You may obtain a copy of the License at 7 | # 8 | # http://www.apache.org/licenses/LICENSE-2.0 9 | # 10 | # Unless required by applicable law or agreed to in writing, software 11 | # distributed under the License is distributed on an "AS IS" BASIS, 12 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 | # See the License for the specific language governing permissions and 14 | # limitations under the License. 15 | """ 16 | Sparse Fine-tuning the library models for seq2seq tasks. 17 | """ 18 | 19 | from nn_pruning.sparse_trainer import SparseTrainer 20 | from .seq2seq_train import Seq2SeqXPTrainer 21 | 22 | # SparseTrainer should appear first in the base classes, as its functions must override Seq2SeqXPTrainer and its base classes 23 | class Seq2SeqSparseTrainer(SparseTrainer, Seq2SeqXPTrainer): 24 | def __init__(self, sparse_args, *args, **kwargs): 25 | Seq2SeqXPTrainer.__init__(self, *args, **kwargs) 26 | SparseTrainer.__init__(self, sparse_args) 27 | -------------------------------------------------------------------------------- /examples/text_classification/glue_sparse_train.py: -------------------------------------------------------------------------------- 1 | # coding=utf-8 2 | # Copyright 2020 The HuggingFace Team All rights reserved. 3 | # 4 | # Licensed under the Apache License, Version 2.0 (the "License"); 5 | # you may not use this file except in compliance with the License. 6 | # You may obtain a copy of the License at 7 | # 8 | # http://www.apache.org/licenses/LICENSE-2.0 9 | # 10 | # Unless required by applicable law or agreed to in writing, software 11 | # distributed under the License is distributed on an "AS IS" BASIS, 12 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 | # See the License for the specific language governing permissions and 14 | # limitations under the License. 15 | """ 16 | Sparse Fine-tuning the library models for question answering. 17 | """ 18 | # You can also adapt this script on your own question answering task. Pointers for this are left as comments. 19 | 20 | from nn_pruning.sparse_trainer import SparseTrainer 21 | from .glue_train import GlueTrainer 22 | 23 | # SparseTrainer should appear first in the base classes, as its functions must override QATrainer and its base classes (Trainer) 24 | class GlueSparseTrainer(SparseTrainer, GlueTrainer): 25 | def __init__(self, sparse_args, *args, **kwargs): 26 | GlueTrainer.__init__(self, *args, **kwargs) 27 | SparseTrainer.__init__(self, sparse_args) 28 | -------------------------------------------------------------------------------- /examples/text_classification/launch_glue_sparse.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import copy 3 | 4 | def main(): 5 | import json 6 | from pathlib import Path 7 | 8 | if len(sys.argv) < 2: 9 | raise RuntimeError("Please specify json file") 10 | filename = Path(sys.argv[1]).resolve() 11 | param_dict = json.load(open(filename)) 12 | 13 | import examples.text_classification.glue_sparse_xp as glue_sparse_xp 14 | 15 | glue = glue_sparse_xp.GlueSparseXP(param_dict) 16 | 17 | def hp_space(trial): 18 | return {} 19 | 20 | glue.hyperparameter_search(direction="minimize", hp_space=hp_space, n_trials=1) 21 | 22 | 23 | def _mp_fn(index): 24 | # For xla_spawn (TPUs) 25 | main() 26 | 27 | 28 | if __name__ == "__main__": 29 | main() 30 | -------------------------------------------------------------------------------- /examples/text_classification/parameters.json: -------------------------------------------------------------------------------- 1 | { 2 | "model_name_or_path": "aloxatel/bert-base-mnli", 3 | "dataset_name": "mnli", 4 | "dataset_cache_dir": "dataset_cache_dir", 5 | "do_train": 1, 6 | "do_eval": 1, 7 | "per_device_train_batch_size": 32, 8 | "per_device_eval_batch_size": 128, 9 | "max_seq_length": 128, 10 | "doc_stride": 128, 11 | "num_train_epochs": 12, 12 | "logging_steps": 250, 13 | "save_steps": 5000, 14 | "eval_steps": 5000, 15 | "save_total_limit": 50, 16 | "seed": 17, 17 | "evaluation_strategy": "steps", 18 | "learning_rate": 3e-5, 19 | "mask_scores_learning_rate": 1e-2, 20 | "output_dir": "output/mnli_test2/", 21 | "logging_dir": "output/mnli_test2/", 22 | "overwrite_cache": 0, 23 | "overwrite_output_dir": 1, 24 | "warmup_steps": 12000, 25 | "initial_warmup": 1, 26 | "final_warmup": 4, 27 | "initial_threshold": 0, 28 | "final_threshold": 0.1, 29 | "dense_pruning_method": "sigmoied_threshold:1d_alt", 30 | "dense_block_rows":1, 31 | "dense_block_cols":1, 32 | "dense_lambda":1.0, 33 | "attention_pruning_method": "sigmoied_threshold", 34 | "attention_block_rows":32, 35 | "attention_block_cols":32, 36 | "attention_lambda":1.0, 37 | "ampere_pruning_method": "disabled", 38 | "mask_init": "constant", 39 | "mask_scale": 0.0, 40 | "regularization": "l1", 41 | "regularization_final_lambda": 30, 42 | "distil_teacher_name_or_path":"aloxatel/bert-base-mnli", 43 | "distil_alpha_ce": 0.1, 44 | "distil_alpha_teacher": 0.90, 45 | "attention_output_with_dense": 0 46 | } 47 | -------------------------------------------------------------------------------- /nn_pruning/__init__.py: -------------------------------------------------------------------------------- 1 | def run1(path, output): 2 | return "run1_ok" 3 | 4 | 5 | def run2(path, output): 6 | return "run2_ok" 7 | -------------------------------------------------------------------------------- /nn_pruning/tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/huggingface/nn_pruning/0cef2b2435d575f141feb12885f632b173df8f93/nn_pruning/tests/__init__.py -------------------------------------------------------------------------------- /nn_pruning/tests/test_quantization.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | 3 | from transformers import AutoModelForQuestionAnswering, AutoTokenizer 4 | 5 | from nn_pruning.modules.quantization import ( 6 | prepare_qat, 7 | prepare_static, 8 | quantize, 9 | ) 10 | 11 | 12 | class TestQuantization(unittest.TestCase): 13 | def _test_quantization(self, prepare_fn): 14 | model_name = "bert-base-uncased" 15 | tokenizer = AutoTokenizer.from_pretrained(model_name) 16 | model = AutoModelForQuestionAnswering.from_pretrained(model_name) 17 | prepared_model = prepare_fn( 18 | model, input_names=["input_ids", "attention_mask", "token_type_ids"], qconfig_name="default" 19 | ) 20 | prepared_model(**prepared_model.dummy_inputs) 21 | quantized = quantize(prepared_model) 22 | quantized(**prepared_model.dummy_inputs) 23 | 24 | def test_static_quantization(self): 25 | self._test_quantization(prepare_static) 26 | 27 | def test_qat(self): 28 | self._test_quantization(prepare_qat) 29 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.black] 2 | line-length = 119 3 | target-version = ['py35'] 4 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import setup 2 | 3 | 4 | def readme(): 5 | with open("README.md") as f: 6 | return f.read() 7 | 8 | extras = { 9 | "tests": ["pytest"], 10 | "examples": ["numpy>=1.2.0", "datasets>=1.4.1", "ipywidgets>=7.6.3", "matplotlib>=3.3.4", "pandas>=1.2.3"], 11 | } 12 | 13 | def combine_requirements(base_keys): 14 | return list(set(k for v in base_keys for k in extras[v])) 15 | 16 | extras["dev"] = combine_requirements([k for k in extras if k != "examples"]) 17 | 18 | 19 | setup( 20 | name="nn_pruning", 21 | version="0.1.2", 22 | description="nn_pruning is a python package for pruning PyTorch models.", 23 | long_description="nn_pruning is a python package for pruning PyTorch models.", 24 | classifiers=[ 25 | "Development Status :: 3 - Alpha", 26 | "License :: OSI Approved :: MIT License", 27 | "Programming Language :: Python :: 3.0", 28 | "Topic :: Text Processing", 29 | ], 30 | keywords="", 31 | url="", 32 | author="", 33 | author_email="", 34 | license="MIT", 35 | packages=["nn_pruning", "nn_pruning.modules"], 36 | install_requires=["click", "transformers>=4.3.0", "torch>=1.6", "scikit-learn>=0.24"], 37 | extras_require=extras, 38 | test_suite="nose.collector", 39 | tests_require=["nose", "nose-cover3"], 40 | entry_points={ 41 | "console_scripts": ["nn_pruning_run_example=examples.command_line:main"], 42 | }, 43 | include_package_data=True, 44 | zip_safe=False, 45 | ) 46 | --------------------------------------------------------------------------------