[BUILD][TRITON] Sync with triton main and use pyproject.toml (#51)

README.md

@@ -43,26 +43,32 @@ The best part about this tool is that while it does focus on visualizing GPU ope
 ## Getting Started
 
 ### Prerequisites
+
 - Python installed (preferably the latest available version).
 - [Triton](https://github.com/openai/triton/blob/main/README.md) installed. Follow the installation instructions in the linked repository.
 
 Upon successfully installing Triton, install Torch using the following command:
+
 ```sh
 pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
 ```
 
 Upon successful installation of Torch make sure to uninstall `pytorch-triton` using the following command:
+
 ```sh
 pip uninstall pytorch-triton
 ```
+
 ### Installation of Triton-Viz
+
 Clone the repository to your local machine:
 
 ```sh
 git clone https://github.com/Deep-Learning-Profiling-Tools/triton-viz.git
 cd triton-viz
 pip install -e .
 ```
+
 You're all set!
 
 ## Working with Examples
@@ -71,10 +77,13 @@ You're all set!
 cd examples
 python <file_name>.py
 ```
+
 ## More Puzzles
+
 If you're interested in fun puzzles to work with in Triton, do check out: [Triton Puzzles](https://github.com/srush/Triton-Puzzles)
 
 ## License
+
 Triton-Viz is licensed under the MIT License. See the [LICENSE](LICENSE) for details.
 
 ## Publication

pyproject.toml

@@ -1,2 +1,34 @@
 [tool.ruff]
 ignore = ["E731"]
+
+[build-system]
+requires = ["setuptools>=42", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "triton-viz"
+version = "1.1.1"
+description = "A visualization tool for Triton"
+authors = [
+  {name = "Deep Learning Profiling Tools Team", email = "[email protected]"}
+]
+readme = "README.md"
+license = {text = "MIT"}
+requires-python = ">=3.7"
+classifiers = [
+  "Programming Language :: Python :: 3",
+  "License :: OSI Approved :: MIT License",
+  "Operating System :: OS Independent",
+]
+dependencies = [
+    "setuptools",
+    "triton",
+    "gradio",
+    "pyarrow",
+    "pre-commit",
+    "pytest",
+  "chalk-diagrams @ git+https://github.com/chalk-diagrams/chalk.git"
+]
+
+[project.urls]
+homepage = "https://github.com/Deep-Learning-Profiling-Tools/triton-viz"

setup.py

@@ -1,20 +1,4 @@
-from setuptools import setup, find_packages
+# setup.py
+from setuptools import setup
 
-setup(
-    name="triton-viz",
-    version="1.1.1",
-    packages=find_packages(),
-    description="A visualization tool for Triton",
-    author="Deep Learning Profiling Tools Team",
-    author_email="[email protected]",
-    url="https://github.com/Deep-Learning-Profiling-Tools/triton-viz",
-    install_requires=[
-        "setuptools",
-        "triton",
-        "gradio",
-        "chalk-diagrams @ git+https://github.com/chalk-diagrams/chalk.git",
-        "pyarrow",
-        "pre-commit",
-        "pytest",
-    ],
-)
+setup()

triton_viz/interpreter.py

@@ -17,7 +17,6 @@
 from triton.runtime.interpreter import (
     GridExecutor,
     _implicit_cvt,
-    RESERVED_KWS,
     interpreter_builder,
     InterpretedFunction,
 )
@@ -136,7 +135,8 @@ def _check_storage_contiguous(tensor):
 
 def _grid_executor_call(self, *args_dev, **kwargs):
     # Removes reserved keywords from kwargs
-    kwargs = {k: v for k, v in kwargs.items() if k not in RESERVED_KWS}
+    argspec = inspect.getfullargspec(self.fn)
+    kwargs = {k: v for k, v in kwargs.items() if k in argspec.args}
     if kwargs.pop("warmup", False):
         return
     args_hst, kwargs_hst = self._init_args_hst(args_dev, kwargs)