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# Byte-compiled / optimized / DLL files | ||
__pycache__/ | ||
*.py[cod] | ||
*$py.class | ||
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# C extensions | ||
*.so | ||
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# Distribution / packaging | ||
.Python | ||
build/ | ||
develop-eggs/ | ||
dist/ | ||
downloads/ | ||
eggs/ | ||
.eggs/ | ||
lib/ | ||
lib64/ | ||
parts/ | ||
sdist/ | ||
var/ | ||
wheels/ | ||
share/python-wheels/ | ||
*.egg-info/ | ||
.installed.cfg | ||
*.egg | ||
MANIFEST | ||
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# PyInstaller | ||
# Usually these files are written by a python script from a template | ||
# before PyInstaller builds the exe, so as to inject date/other infos into it. | ||
*.manifest | ||
*.spec | ||
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# Installer logs | ||
pip-log.txt | ||
pip-delete-this-directory.txt | ||
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# Unit test / coverage reports | ||
htmlcov/ | ||
.tox/ | ||
.nox/ | ||
.coverage | ||
.coverage.* | ||
.cache | ||
nosetests.xml | ||
coverage.xml | ||
*.cover | ||
*.py,cover | ||
.hypothesis/ | ||
.pytest_cache/ | ||
cover/ | ||
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# Translations | ||
*.mo | ||
*.pot | ||
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# Django stuff: | ||
*.log | ||
local_settings.py | ||
db.sqlite3 | ||
db.sqlite3-journal | ||
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# Flask stuff: | ||
instance/ | ||
.webassets-cache | ||
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# Scrapy stuff: | ||
.scrapy | ||
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# Sphinx documentation | ||
docs/_build/ | ||
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# PyBuilder | ||
.pybuilder/ | ||
target/ | ||
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# Jupyter Notebook | ||
.ipynb_checkpoints | ||
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# IPython | ||
profile_default/ | ||
ipython_config.py | ||
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# pyenv | ||
# For a library or package, you might want to ignore these files since the code is | ||
# intended to run in multiple environments; otherwise, check them in: | ||
# .python-version | ||
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# pipenv | ||
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. | ||
# However, in case of collaboration, if having platform-specific dependencies or dependencies | ||
# having no cross-platform support, pipenv may install dependencies that don't work, or not | ||
# install all needed dependencies. | ||
#Pipfile.lock | ||
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# UV | ||
# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control. | ||
# This is especially recommended for binary packages to ensure reproducibility, and is more | ||
# commonly ignored for libraries. | ||
#uv.lock | ||
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# poetry | ||
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. | ||
# This is especially recommended for binary packages to ensure reproducibility, and is more | ||
# commonly ignored for libraries. | ||
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control | ||
#poetry.lock | ||
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# pdm | ||
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. | ||
#pdm.lock | ||
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it | ||
# in version control. | ||
# https://pdm.fming.dev/latest/usage/project/#working-with-version-control | ||
.pdm.toml | ||
.pdm-python | ||
.pdm-build/ | ||
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm | ||
__pypackages__/ | ||
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# Celery stuff | ||
celerybeat-schedule | ||
celerybeat.pid | ||
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# SageMath parsed files | ||
*.sage.py | ||
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# Environments | ||
.env | ||
.venv | ||
env/ | ||
venv/ | ||
ENV/ | ||
env.bak/ | ||
venv.bak/ | ||
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# Spyder project settings | ||
.spyderproject | ||
.spyproject | ||
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# Rope project settings | ||
.ropeproject | ||
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# mkdocs documentation | ||
/site | ||
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# mypy | ||
.mypy_cache/ | ||
.dmypy.json | ||
dmypy.json | ||
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# Pyre type checker | ||
.pyre/ | ||
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# pytype static type analyzer | ||
.pytype/ | ||
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# Cython debug symbols | ||
cython_debug/ | ||
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# PyCharm | ||
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can | ||
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore | ||
# and can be added to the global gitignore or merged into this file. For a more nuclear | ||
# option (not recommended) you can uncomment the following to ignore the entire idea folder. | ||
#.idea/ | ||
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# Ruff stuff: | ||
.ruff_cache/ | ||
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# PyPI configuration file | ||
.pypirc | ||
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ecoml_models |
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3.12.3 |
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# EcoML | ||
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## Table of Contents | ||
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- [Introduction](#introduction) | ||
- [Installation](#installation) | ||
- [Usage](#usage) | ||
- [Contributing](#contributing) | ||
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## Introduction | ||
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EcoML aims to provide accurate power consumption estimates for various edge devices, helping developers optimize their applications for energy efficiency. By leveraging machine learning, EcoML can predict power usage based on different workloads and device configurations. | ||
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## Installation | ||
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To install the necessary dependencies, run the following command: | ||
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```bash | ||
python3 -m venv venv | ||
source venv/bin/activate | ||
pip install ecoml | ||
``` | ||
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## Usage | ||
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To use EcoML for energy estimation of PyTorch models, follow these steps: | ||
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```bash | ||
ecoml predict --model sample_data/resnet18.json | ||
``` | ||
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[Sample data](./sample_data/) contains model summary for 3 models - Resnet18, Mobilenetv2 and VGG16. | ||
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To use a custom model for inference, you have to generate a model summary for the PyTorch model. | ||
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`--verbose` flag can be passed to above command to get a detailed output. | ||
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## Contributing | ||
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We welcome contributions to EcoML! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request. |
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[project] | ||
name = "ecoml" | ||
version = "0.1.0" | ||
description = "Predict energy consumption of PyTorch CNN models on Jetson Orin" | ||
readme = "README.md" | ||
authors = [ | ||
{ name = "fuzzylabs", email = "[email protected]" } | ||
] | ||
requires-python = ">=3.11" | ||
dependencies = [ | ||
"dagshub>=0.5.5", | ||
"mlflow==2.18.0", | ||
"pandas>=2.2.3", | ||
"pydantic>=2.10.6", | ||
"rich>=13.9.4", | ||
"typer>=0.15.1", | ||
"cloudpickle==3.1.0", | ||
"psutil==6.1.0", | ||
"scikit-learn==1.5.2", | ||
"scipy==1.14.1", | ||
"numpy==2.1.2" | ||
] | ||
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[project.scripts] | ||
ecoml = "ecoml.ecoml:app" | ||
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[build-system] | ||
requires = ["hatchling"] | ||
build-backend = "hatchling.build" |
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