# Installation

## System Requirements

Helion currently targets Linux systems and requires a recent Python and PyTorch environment:

### Operating System
- Linux-based OS
- Other Unix-like systems may work but are not officially supported

### Python Environment
- **Python 3.10, 3.11, or 3.12**
- We recommend using [conda](https://www.anaconda.com/docs/getting-started/miniconda/install) for environment management

### Dependencies
- **[PyTorch](https://github.com/pytorch/pytorch) nightly build**
- **[Triton](https://github.com/triton-lang/triton) development version** installed from source

  *Note: Older versions may work, but will lack support for features like TMA on Hopper/Blackwell GPUs and may exhibit lower performance.*

## Installation Methods

### Method 1: Install via pip

The easiest way to install Helion is directly from GitHub:

```bash
pip install git+https://github.com/pytorch-labs/helion.git
```

We also publish [PyPI releases](https://pypi.org/project/helion/), but the GitHub version is recommended for the latest features and fixes.

### Method 2: Development Installation

For development purposes or if you want to modify Helion:

```bash
# Clone the repository
git clone https://github.com/pytorch-labs/helion.git
cd helion

# Install in editable mode with development dependencies
pip install -e '.[dev]'
```

This installs Helion in "editable" mode so that changes to the source code take effect without needing to reinstall.

## Step-by-Step Setup Guide

### 1. Set Up Conda Environment

We recommend using conda to manage dependencies:

```bash
# Create a new environment
conda create -n helion python=3.12
conda activate helion
```

### 2. Install PyTorch Nightly

Install the latest PyTorch nightly build:

```bash
# For CUDA 12.6 systems
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu126
```
see [PyTorch installation instructions](https://pytorch.org/get-started/locally/) for other options.

### 3. Install Triton from Source

Helion requires a development version of Triton:

```bash
# Clone and install Triton
git clone https://github.com/triton-lang/triton.git
cd triton

# Install Triton
pip install -e .

# Return to your working directory
cd ..
```

### 4. Install Helion

Choose one of the installation methods above:

```bash
# Option A: From GitHub
pip install git+https://github.com/pytorch-labs/helion.git

# Option B: Development installation
git clone https://github.com/pytorch-labs/helion.git
cd helion
pip install -e '.[dev]'
```

## Verification

Verify your installation by running a simple test:

```python
import torch
import helion
import helion.language as hl

@helion.kernel(use_default_config=True)
def test_kernel(x: torch.Tensor) -> torch.Tensor:
    out = torch.empty_like(x)
    for tile in hl.tile(x.shape[0]):
        out[tile] = x[tile] * 2
    return out

x = torch.randn(100, device='cuda')
result = test_kernel(x)
torch.testing.assert_close(result, x * 2)
print("Verification successful!")
```

## Development Dependencies

If you installed with `[dev]`, you get additional development tools:

- **pytest** - Test runner
- **pre-commit** - Code formatting and linting hooks

Set up pre-commit hooks for development:

```bash
pre-commit install
```

## Optional Dependencies

### Documentation Building

To build documentation locally:

```bash
pip install -e '.[docs]'
cd docs
make html
```

### GPU Requirements

Matches the requirements of [Triton](https://github.com/triton-lang/triton).  At the time of writing:
* NVIDIA GPUs (Compute Capability 8.0+)
* AMD GPUs (ROCm 6.2+)
* Via third-party forks: Intel XPU, CPU, and many other architectures

## Next Steps

Once installation is complete:

1. **Check out the {doc}`api/index` for complete API documentation**
2. **Explore the [examples/](https://github.com/pytorch-labs/helion/tree/main/examples) folder for real-world patterns**