pytorch / pytorch/benchmark

Add Stanza model to benchmark repo

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Python
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Description

We're building a suite of pytorch benchmarks by forking popular open-source models and modifying them to conform to a common API that facilitates a central tool installing, running, and collecting measurements.

The hub repo is no longer used, models are no longer added as git submodules, other parts remain largely the same. Instructions are found in the README in the new repo

Benchmark Repo: https://github.com/pytorch/benchmark
Instructions: https://github.com/pytorch/benchmark/blob/master/torchbenchmark/models/ADDING_MODELS.md
Source model: https://github.com/ezyang/stanza

The Stanza model has already been forked and modified in a previous phase of this process, but the API (install.py, hubconf.py) had not yet been standardized. Copy the repo into benchmark.git, follow the latest instructions in the ADDING_MODELS readme to add the new API. Note, the 'install.sh' and 'run.sh' scripts added in the previous effort would serve as good hints on how to proceed.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with torchbenchmark/models/ADDING_MODELS.md in the benchmark repository, then inspect the existing Stanza fork and its install.sh and run.sh scripts. Standardize the model with the required install.py and hubconf.py API, and verify that it can be installed, run, and measured through the benchmark tooling.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning, performance
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Clearly specified
Newbie friendliness
55/100

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