torchcts 0.2.2

A comprehensive PyTorch backend validation and benchmarking suite

TorchCTS — Validate Your PyTorch Backend

TorchCTS is a comprehensive conformance test suite that stress-tests operators, autograd, memory, training pipelines, and torch.compile — across every dtype and layout — against CPU references. It is built specifically for backend developers shipping CUDA, MPS, XPU, or custom PrivateUse1 backends.

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Why TorchCTS?

• 🔬 Correctness Over Everything: Every registered ATen operator is tested against CPU references across all dtypes, strides, and layouts. Non-contiguous memory, channels-last, overlapping strides — nothing is skipped unless explicitly configured.
• 📊 Actionable Scorecards: Self-contained reports with pass/fail per capability, dtype coverage matrices, and regression diffs. Understand what failed and why without needing to rerun.
• ⚡ Manifest-Driven: Declare your backend capabilities in a single file (manifest.py). The suite automatically skips unsupported features. Pick a template — minimal, inference, training, or complete — and customize from there.

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Quick Start (How It Works)

1. Install

Add TorchCTS to your project (requires Python ≥ 3.10 and PyTorch ≥ 2.12):

pip install torchcts

2. Init

Initialize a manifest file in your directory by choosing one of the available templates (complete, training, inference, minimal):

torchcts init

3. Run

Execute the test suite against your targeted backend:

torchcts run --device mps

Note: Run torchcts show-skips for a collection-only dry-run to print which tests will be skipped and why.

4. Report

Generate or update the comprehensive HTML/Markdown scorecard and validation reports from the test execution results:

torchcts report

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CLI Reference

TorchCTS provides a CLI with the following subcommands:

• init: Initialize manifest.py from a template.
• run: Run the test suite against the target backend.
• show-skips: Dry-run collection to show which tests will be skipped and why.
• report: Regenerate scorecards and reports from JSON results.
• sync-opinfo: Force-rebuild the OpInfo registry cache.
• check-manifest: Validate manifest.py syntax and schema.

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Project Structure & Development

• The package entry point is torchcts.
• Manifest templates are located in torchcts/templates/.
• Test execution results are saved under the ./results/ directory.