Rename package from zeus-ml to zeus

.github/workflows/publish_pypi.yaml

@@ -6,9 +6,11 @@ on:
       - zeus-v*
 
 jobs:
-  publish:
+  pypi-publish:
     runs-on: ubuntu-latest
     if: github.repository_owner == 'ml-energy'
+    permissions:
+      id-token: write
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
@@ -21,5 +23,3 @@ jobs:
         run: pip install build && python -m build
       - name: Publish to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
-        with:
-          password: ${{ secrets.PYPI_API_KEY }}

docs/getting_started/index.md

@@ -10,7 +10,7 @@ Some optimizers or examples may require some extra setup steps, which are descri
 Install the Zeus Python package simply with:
 
 ```sh
-pip install zeus-ml
+pip install zeus
 ```
 
 ### From source for development

docs/optimize/batch_size_optimizer.md

@@ -164,7 +164,7 @@ In order for your recurring training job to communicate with the BSO server, you
 1. Install the Zeus package, including dependencies needed for the batch size optimizer.
 
     ```sh
-    pip install zeus-ml[bso]
+    pip install zeus[bso]
     ```
 
 2. Integrate [`BatchSizeOptimizer`][zeus.optimizer.batch_size.client.BatchSizeOptimizer] to your training script.

docs/optimize/pipeline_frequency_optimizer.md

@@ -97,7 +97,7 @@ As another example, in Megatron-LM, users can pass in their custom `forward_step
 
 ### Integrate `PipelineFrequencyOptimizer`
 
-1. Add `zeus-ml[pfo]` to your dependencies.
+1. Add `zeus[pfo]` to your dependencies.
 1. Instantiate the [`PipelineFrequencyOptimizer`][zeus.optimizer.pipeline_frequency.optimizer.PipelineFrequencyOptimizer] somewhere before actual training runs. Let's call the object `opt`.
 1. Surround one training step with `opt.on_step_begin()` and `opt.on_step_end()`.
 1. Wrap the forward pass region with `opt.on_instruction_begin("forward")` and `opt.on_instruction_end("forward")`.

examples/carbon_emission_monitor/requirements.txt

@@ -1,4 +1,4 @@
-zeus-ml
+zeus
 accelerate >= 0.12.0
 torch >= 1.3
 datasets >= 1.8.0

examples/huggingface/README.md

@@ -15,7 +15,7 @@ To run the `SFTTrainer` integration script (`run_gemma_sft_qlora.py`):
 ```sh
 pip install -r requirements-qlora.txt
 ```
-Note that you may have to tweak `requirements-qlora.txt` depending on your setup. The current requirements file assumes that you are using CUDA 11, and installs `nvidia-cusparse-cu11` for `bitsandbytes`. Basically, you want to get a setup where training runs, and just add `pip install zeus-ml` on top of it.
+Note that you may have to tweak `requirements-qlora.txt` depending on your setup. The current requirements file assumes that you are using CUDA 11, and installs `nvidia-cusparse-cu11` for `bitsandbytes`. Basically, you want to get a setup where training runs, and just add `pip install zeus` on top of it.
 
 ## `ZeusMonitor` and `HFGlobalPowerLimitOptimizer`
 

examples/huggingface/requirements-qlora.txt

@@ -1,4 +1,4 @@
-zeus-ml
+zeus
 accelerate >= 0.12.0
 torch >= 1.3
 datasets >= 1.8.0

examples/huggingface/requirements.txt

@@ -1,4 +1,4 @@
-zeus-ml
+zeus
 accelerate >= 0.12.0
 torch >= 1.3
 datasets >= 1.8.0

examples/jax/requirements.txt

@@ -1,2 +1,2 @@
-zeus-ml
+zeus
 jax[cuda12]==0.4.30

pyproject.toml

@@ -3,7 +3,7 @@ requires = ["setuptools>=61.0.0", "wheel"]
 build-backend = "setuptools.build_meta"
 
 [project]
-name = "zeus-ml"
+name = "zeus"
 description = "A framework for deep learning energy measurement and optimization."
 readme = "README.md"
 authors = [
@@ -52,7 +52,7 @@ lint = ["ruff", "black==22.6.0", "pyright", "pandas-stubs", "transformers"]
 test = ["fastapi[standard]", "sqlalchemy", "pydantic<2", "pytest==7.3.2", "pytest-mock==3.10.0", "pytest-xdist==3.3.1", "anyio==3.7.1", "aiosqlite==0.20.0", "numpy<2"]
 docs = ["mkdocs-material[imaging]==9.5.19", "mkdocstrings[python]==0.25.0", "mkdocs-gen-files==0.5.0", "mkdocs-literate-nav==0.6.1", "mkdocs-section-index==0.3.9", "mkdocs-redirects==1.2.1", "urllib3<2", "black"]
 # greenlet is for supporting apple mac silicon for sqlalchemy(https://docs.sqlalchemy.org/en/20/faq/installation.html)
-dev = ["zeus-ml[pfo-server,bso,bso-server,migration,prometheus,lint,test]", "greenlet"]
+dev = ["zeus[pfo-server,bso,bso-server,migration,prometheus,lint,test]", "greenlet"]
 
 [tool.setuptools.packages.find]
 where = ["."]