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Document setup instructions (#206)
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* Document setup instructions

* Include lock file
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BrunoGrandePhD authored Nov 10, 2024
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9 changes: 9 additions & 0 deletions .gitignore
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ENV/
env.bak/
venv.bak/

# Datasets
data

# Azure
.amlignore*

# Jupyter
.ipynb_*
23 changes: 23 additions & 0 deletions ModelTraining/README.md
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# Repo to explain FastAI modeling methodology
- Author : Aayush Agrawal (aaagraw@microsoft.com)

## Setup

Author: Bruno Grande

The following instructions describe how I was able to install the dependencies for these Jupyter notebooks. I was running into a version conflict with `pip install`. I was able to resolve dependencies using `uv pip install`.

```console
# Navigate to ModelTraining subdirectory
cd aifororcas-livesystem/ModelTraining

# Create a new conda environment with Python 3.8
conda create -n <env-name> python=3.8
conda activate <env-name>

# Install uv (better at resolving package version conflicts)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install dependencies using `uv pip` (instead of plain `pip`)
uv pip install -r requirements.txt
```

I'm also including a full list of installed packages and versions in `requirements.lock.txt`, which was generated using `pip freeze`.

## Model data
The base data used here is hosted on Current test set for evaluation is hosted on [Orca Sound website ](https://github.com/orcasound/orcadata/wiki/Pod.Cast-data-archive#test-sets). The model was trained with the following dataset -

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132 changes: 132 additions & 0 deletions ModelTraining/requirements.lock.txt
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annotated-types==0.7.0
asttokens==2.4.1
attrs==24.2.0
audioread==3.0.1
backcall==0.2.0
beautifulsoup4==4.12.3
bleach==6.1.0
blis==0.7.11
Bottleneck==1.4.0
catalogue==2.0.10
certifi==2024.8.30
cffi==1.17.1
charset-normalizer==3.4.0
click==8.1.7
cloudpathlib==0.20.0
comm==0.2.2
confection==0.1.5
contourpy==1.1.1
cycler==0.12.1
cymem==2.0.8
debugpy==1.8.8
decorator==5.1.1
defusedxml==0.7.1
docopt==0.6.2
executing==2.1.0
fastai==1.0.61
fastai_audio @ git+https://github.com/fastaudio/fastai_audio@3730194a0ed14e142416f60e71effa6e28058b60
fastjsonschema==2.20.0
fastprogress==1.0.3
fire==0.7.0
fonttools==4.54.1
future==1.0.0
idna==3.10
importlib_metadata==8.5.0
importlib_resources==6.4.5
ipykernel==6.29.5
ipython==8.12.3
jedi==0.19.1
Jinja2==3.1.4
joblib==1.4.2
jsonschema==4.23.0
jsonschema-specifications==2023.12.1
jupyter_client==8.6.3
jupyter_core==5.7.2
jupyterlab_pygments==0.3.0
kiwisolver==1.4.7
langcodes==3.4.1
language_data==1.2.0
lazy_loader==0.4
librosa==0.10.0
llvmlite==0.41.1
marisa-trie==1.2.1
markdown-it-py==3.0.0
MarkupSafe==2.1.5
matplotlib==3.7.5
matplotlib-inline==0.1.7
mdurl==0.1.2
mistune==3.0.2
msgpack==1.1.0
murmurhash==1.0.10
nbclient==0.10.0
nbconvert==7.16.4
nbformat==5.10.4
nest-asyncio==1.6.0
numba==0.58.1
numexpr==2.8.6
numpy==1.24.4
nvidia-ml-py3==7.352.0
packaging==24.2
pandas==2.0.3
pandocfilters==1.5.1
parso==0.8.4
pexpect==4.9.0
pickleshare==0.7.5
pillow==10.4.0
pipreqs==0.5.0
pkgutil_resolve_name==1.3.10
platformdirs==4.3.6
pooch==1.8.2
preshed==3.0.9
prompt_toolkit==3.0.48
psutil==6.1.0
ptyprocess==0.7.0
pure_eval==0.2.3
pycparser==2.22
pydantic==2.9.2
pydantic_core==2.23.4
pydub==0.24.1
Pygments==2.18.0
pyparsing==3.1.4
python-dateutil==2.9.0.post0
pytz==2024.2
PyYAML==6.0.2
pyzmq==26.2.0
referencing==0.35.1
requests==2.32.3
rich==13.9.4
rpds-py==0.20.1
scikit-learn==1.3.2
scipy==1.10.1
shellingham==1.5.4
six==1.16.0
smart-open==7.0.5
soundfile==0.12.1
soupsieve==2.6
soxr==0.3.7
spacy==3.7.5
spacy-legacy==3.0.12
spacy-loggers==1.0.5
srsly==2.4.8
stack-data==0.6.3
termcolor==2.4.0
thinc==8.2.5
threadpoolctl==3.5.0
tinycss2==1.4.0
torch==1.6.0+cu92
torchaudio==0.6.0
torchvision==0.7.0+cu92
tornado==6.4.1
tqdm==4.67.0
traitlets==5.14.3
typer==0.13.0
typing_extensions==4.12.2
tzdata==2024.2
urllib3==2.2.3
wasabi==1.1.3
wcwidth==0.2.13
weasel==0.4.1
webencodings==0.5.1
wrapt==1.16.0
yarg==0.1.9
zipp==3.20.2

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