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### Description This PR is to update the win-ort-main branch to the tip main branch as of 2025-01-16. ### Motivation and Context This update includes the OpenVino fix for debug builds. --------- Signed-off-by: Liqun Fu <liqfu@microsoft.com> Signed-off-by: Liqun Fu <liqun.fu@microsoft.com> Signed-off-by: Junze Wu <junze.wu@intel.com> Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: Jianhui Dai <jianhui.j.dai@intel.com> Co-authored-by: Yueqing Zhang <yuz75@Pitt.edu> Co-authored-by: amancini-N <63410090+amancini-N@users.noreply.github.com> Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com> Co-authored-by: liqun Fu <liqfu@microsoft.com> Co-authored-by: Guenther Schmuelling <guschmue@microsoft.com> Co-authored-by: Yifan Li <109183385+yf711@users.noreply.github.com> Co-authored-by: yf711 <yifanl@microsoft.com> Co-authored-by: Wanming Lin <wanming.lin@intel.com> Co-authored-by: wejoncy <wejoncy@163.com> Co-authored-by: wejoncy <wejoncy@.com> Co-authored-by: Scott McKay <skottmckay@gmail.com> Co-authored-by: Changming Sun <chasun@microsoft.com> Co-authored-by: Jean-Michaël Celerier <jeanmichael.celerier+github@gmail.com> Co-authored-by: Dmitry Deshevoy <mityada@gmail.com> Co-authored-by: xhcao <xinghua.cao@intel.com> Co-authored-by: Yueqing Zhang <yueqingz@amd.com> Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Co-authored-by: Jiajia Qin <jiajiaqin@microsoft.com> Co-authored-by: Wu, Junze <junze.wu@intel.com> Co-authored-by: Jian Chen <cjian@microsoft.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: Matthieu Darbois <mayeut@users.noreply.github.com> Co-authored-by: Prathik Rao <prathik.rao@gmail.com> Co-authored-by: wonchung-microsoft <wonchung@microsoft.com> Co-authored-by: Vincent Wang <wangwchpku@outlook.com> Co-authored-by: PARK DongHa <luncliff@gmail.com> Co-authored-by: Hector Li <hecli@microsoft.com> Co-authored-by: Sam Webster <13457618+samwebster@users.noreply.github.com> Co-authored-by: Adrian Lizarraga <adrianlm2@gmail.com> Co-authored-by: Preetha Veeramalai <preetha.veeramalai@intel.com> Co-authored-by: jatinwadhwa921 <jatin.wadhwa@intel.com> Co-authored-by: Satya Kumar Jandhyala <satya.k.jandhyala@gmail.com> Co-authored-by: Corentin Maravat <101636442+cocotdf@users.noreply.github.com> Co-authored-by: Xiaoyu <85524621+xiaoyu-work@users.noreply.github.com> Co-authored-by: Tianlei Wu <tlwu@microsoft.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Jie Chen <jie.a.chen@intel.com> Co-authored-by: Jianhui Dai <jianhui.j.dai@intel.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com> Co-authored-by: Baiju Meswani <bmeswani@microsoft.com> Co-authored-by: kunal-vaishnavi <115581922+kunal-vaishnavi@users.noreply.github.com> Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com> Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com> Co-authored-by: Ted Themistokleous <107195283+TedThemistokleous@users.noreply.github.com> Co-authored-by: Jeff Daily <jeff.daily@amd.com> Co-authored-by: Artur Wojcik <artur.wojcik@outlook.com> Co-authored-by: Ted Themistokleous <tedthemistokleous@amd.com> Co-authored-by: Xinya Zhang <Xinya.Zhang@amd.com> Co-authored-by: ikalinic <ilija.kalinic@amd.com> Co-authored-by: sstamenk <sstamenk@amd.com> Co-authored-by: Yi-Hong Lyu <yilyu@microsoft.com> Co-authored-by: Ti-Tai Wang <titaiwang@microsoft.com> |
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| .. | ||
| experiment.py | ||
| gpt2_model_transform.py | ||
| layer_norm_transform.py | ||
| model_transform.py | ||
| nv_run_pretraining.py | ||
| opset12_model_transform.py | ||
| performance_investigation.py | ||
| pipeline_model_split.py | ||
| README.txt | ||
| single_node_perf.sh | ||
| sqldb_to_tensors.py | ||
| train.py | ||
| watch_experiment.py | ||
Procedure to export NV's pytorch model to ONNX. 1. cd into BERT in DeepLearningExamples and launch the docker. 2. run nv_run_pretraining.py using the same parameter you run run_pretraining.py. It will produce a model in your checkpoint directory. 3. Assume that the exported model's name is 'bert.onnx'. Run model_transform.py bert.onnx 4. Then run layer_norm_transform.py bert_optimized.onnx. The final model name would be bert_optimized_layer_norm.onnx 5. Now, you can run training with the newly created model. Note that if you want to change model's configuration, you can edit bert_config.json in the BERT directory. Example commands: Step 2 (inside docker): python3 /workspace/bert/nv_run_pretraining.py --input_dir=data/bookcorpus/hdf5_shards/ --output_dir=/results/checkpoints1 --config_file=bert_config.json --bert_model=bert-large-uncased --warmup_proportion=0 --num_steps_per_checkpoint=2000 --learning_rate=0.875e-4 --seed=42 --do_train --phase2 --max_seq_length=512 --max_predictions_per_seq=80 --max_steps=200 --train_batch_size=2 Step 3 (inside onnxruntime/build/Linux/RelWithDeb): sudo /data/anaconda/envs/py35/bin/python /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/model_transform.py /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/results/checkpoints1/bert_for_pretraining_without_loss_vocab_30528_hidden_1024_maxpos_512.onnx Step 4 (inside onnxruntime/build/Linux/RelWithDeb): sudo /data/anaconda/envs/py35/bin/python /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/layer_norm_transform.py /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/results/checkpoints1/bert_for_pretraining_without_loss_vocab_30528_hidden_1024_maxpos_512_optimized.onnx Step 5 (inside onnxruntime/build/Linux/RelWithDeb): ./onnxruntime_training_bert --num_of_perf_samples=100 --train_batch_size=1 --mode=perf --model_name /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/results/checkpoints1/bert_for_pretraining_without_loss_vocab_30528_hidden_1024_maxpos_512_optimized_layer_norm