Merge pull request #68 from jbusche/jb-dependency-issue56

Switches dependencies from txt file to toml file

CONTRIBUTING.md

@@ -78,7 +78,6 @@ The following tools are required:
 
 Installation:
 ``` 
-pip install -r requirements.txt
 pip install -U datasets
 pip install -e .
 ```

README.md

@@ -8,12 +8,15 @@ This repo provides basic tuning scripts with support for specific models. The re
 ## Installation
 
 ```
-pip install -r requirements.txt
-pip install -U datasets
 pip install -e .
 ```
 
-> Note: If you wish to use [FlashAttention](https://github.com/Dao-AILab/flash-attention), then you need to install these requirements: `pip install -r flashattn_requirements`. [FlashAttention](https://github.com/Dao-AILab/flash-attention) requires the [CUDA Toolit](https://developer.nvidia.com/cuda-toolkit) to be pre-installed.
+> Note: After installing, if you wish to use [FlashAttention](https://github.com/Dao-AILab/flash-attention), then you need to install these requirements:
+'''
+pip install -e ".[dev]"
+pip install -e ".[flash-attn]"
+```
+[FlashAttention](https://github.com/Dao-AILab/flash-attention) requires the [CUDA Toolit](https://developer.nvidia.com/cuda-toolkit) to be pre-installed.
 
 ## Data format
 The data format expectation is a single column text. The trainer is configured to expect a response template as a string. For example, if one wants to prepare the `alpaca` format data to feed into this trainer, it is quite easy and can be done with the following code.

build/Dockerfile

@@ -96,18 +96,14 @@ RUN dnf install -y python3.11 git && \
 RUN mkdir /app
 
 WORKDIR /tmp
-RUN python -m pip install packaging && \
-    python -m pip install --upgrade pip && \
-    python -m pip install torch && \
-    python -m pip install wheel
+RUN python -m pip install --upgrade pip
 
 # TODO Move to installing wheel once we have proper releases setup instead of cloning the repo
 RUN git clone https://github.com/foundation-model-stack/fms-hf-tuning.git && \
     cd fms-hf-tuning && \
-    python -m pip install -r requirements.txt && \
-    python -m pip install -r flashattn_requirements.txt && \
-    python -m pip install -U datasets  && \
-    python -m pip install /tmp/fms-hf-tuning
+    python -m pip install ".[dev]" && \
+    python -m pip install ".[flash-attn]" && \
+    python -m pip install -U datasets
 
 RUN mkdir -p /licenses
 COPY LICENSE /licenses/
@@ -129,4 +125,4 @@ RUN useradd -u $USER_UID tuning -m -g 0 --system && \
 WORKDIR /app
 USER ${USER}
 
-CMD [ "tail", "-f", "/dev/null" ]
+CMD [ "tail", "-f", "/dev/null" ]

pyproject.toml

@@ -0,0 +1,34 @@
+[build-system]
+requires = [
+    "setuptools>=61",
+    "setuptools-scm>=8.0"]
+
+[project]
+name = "fms-hf-tuning"
+version = "0.0.1"
+description = "FMS HF Tuning"
+authors = [
+  {name = "Sukriti Sharma", email = "sukriti.sharma4@ibm.com"},
+  {name = "Anh Uong", email = "anh.uong@ibm.com"},
+]
+license = {text = "Apache-2.0"}
+readme = "README.md"
+requires-python = "~=3.9"
+keywords = ['fms-hf-tuning', 'python', 'tuning']
+classifiers=[
+    "License :: OSI Approved :: Apache Software License"
+]
+
+dynamic = ["dependencies"]
+
+[project.optional-dependencies]
+dev = ["wheel", "packaging", "ninja"]
+flash-attn = ["flash-attn"]
+
+[tool.setuptools.dynamic]
+dependencies = {file = ["requirements.txt"]}
+
+[project.urls]
+Homepage = "https://github.com/foundation-model-stack/fms-hf-tuning"
+Repository = "https://github.com/foundation-model-stack/fms-hf-tuning"
+Issues = "https://github.com/foundation-model-stack/fms-hf-tuning/issues"

requirements.txt

@@ -1,15 +1,12 @@
 numpy
 accelerate>=0.20.3
-packaging
-transformers>=4.34.1
+transformers
 torch
 aim==3.18.1
 sentencepiece
 tokenizers>=0.13.3
 tqdm
 trl
-ninja
 peft>=0.8.0
 datasets>=2.15.0
 fire
-

setup.py

@@ -15,4 +15,4 @@
 # Third Party
 from setuptools import find_packages, setup
 
-setup(name="tuning", version="0.0.1", packages=find_packages())
+setup(name="fms-hf-tuning", version="0.0.1", packages=find_packages())