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Large model inference #2215
Large model inference #2215
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Codecov Report
@@ Coverage Diff @@
## master #2215 +/- ##
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- Coverage 71.47% 70.31% -1.17%
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Files 73 75 +2
Lines 3341 3392 +51
Branches 57 57
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- Hits 2388 2385 -3
- Misses 950 1004 +54
Partials 3 3
... and 1 file with indirect coverage changes 📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more |
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I added comments for Huggingface_pippy. They can apply to the Hugingfac_accelerate and Deepspeed_mii
docs/large_model_inference.md
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This document explain how Torchserve supports large model serving, here large model refers to the models that are not able to fit into one gpu so they need be splitted in multiple partitions over multiple gpus. | ||
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## PiPPY (PyTorch Native solution for large model inference) |
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could move this readme under dir Huggingface_pippy since this doc is about pippy?
Can we add common instruction/steps in this doc?
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### Step 0: Install torchserve from src | ||
```bash | ||
python ts_scripts/install_from_src.py |
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yes
…for others pipe_driver
LGTM, please just make sure lint jobs are green and we can merge |
Thanks @msaroufim , sure will address the failing spell checks and lints |
Description
Adding PiPPy large model inference with HF example
Note waiting for PiPPY binaries later this week(04/10) to update the dev requirements.
Also this PR moves all our large model related examples, deepspeed, accelerate under example/ large_model folder
Type of change
Please delete options that are not relevant.
Feature/Issue validation/testing
Please describe the Unit or Integration tests that you ran to verify your changes and relevant result summary. Provide instructions so it can be reproduced.
Please also list any relevant details for your test configuration.
Test A
Logs for regression tests
https://drive.google.com/file/d/1k7iBydhIv2MpBXmwDuaPkFuerXige5Tm/view?usp=share_link
Test B
Logs for Test B
Checklist: