Changelog¶

All notable changes to TiRex-2 are documented here.

Unreleased ¶

Removed the xlstm dependency to reduce the package footprint, in #71, contributed by Martin Loretz.
Default safetensors weights: All checkpoints ship model configuration and weights in json and safetensors formats. load_model now loads from config.json and model.safetensors, which avoids unpickling and is faster. The legacy yaml and ckpt files are deprecated with a FutureWarning in #55, contributed by Suad0.

Refactored the sLSTM recurrence interface to support future kernel implementations and decoupled its configuration from FlashRNN in #70, contributed by Martin Loretz.
Added the Intended Use, Limitations and EU AI Act Notice (INTENDED_USE.md), linked from the README and the documentation, in #67, contributed by Lukas Fischer and Yipeng Sun.
Added a script to convert legacy checkpoints to new formats in #55, contributed by Suad0.

Refactored internal prediction pipeline, and renamed _predict_once(...) to _predict(...) for clarity in #62, contributed by Christian Ganhör.

⭐️📊 Use forecast_df() to forecast directly from pandas, Polars, PyArrow, and other supported eager dataframes. It handles multiple series, covariates, and batching, and returns results in the input dataframe library by default, in #18, contributed by Suad0 and Zhihao Dai.
⭐️🚀 Added a pad_context=False option to forecast(...) to skip padding to the default context length, enabling much faster inference for short contexts at a small accuracy cost, in #57, contributed by Daniil Yefimov.
⭐️🚀 Added opt-in recurrent-layer compilation with load_model(..., compile=True) for faster repeated forecasts (up to 1.82x on CPU), in #47, contributed by Daniil Yefimov.
Added a preserve_grad=True option to _predict_once(...) and postprocessing for fine-tuning, preserving finite gradients through inverse differencing, in #58, contributed by Zhihao Dai.
Replaced einops rearrangements with native PyTorch operations and removed the direct einops dependency in #41, contributed by Copilot and Zhihao Dai.
Removed a redundant torch.no_grad() context from prediction code in #42, contributed by Zhihao Dai.

Added a dataframe forecasting guide for native dataframe forecasting via forecast_df, contributed by Suad0 and Zhihao Dai.
Corrected deployment examples and guidance for covariates, model caching, compilation, and the HTTP API, and added an Open Source vs PRO feature comparison table with consistent PRO naming in #21, contributed by Lukas Fischer, Claude Sonnet 5, and Zhihao Dai.
Made the default Windows CUDA Pixi platform use the cu130 PyTorch index and fail CUDA tests early when CUDA is unavailable, in #51, contributed by Yipeng Sun.
Added FAQs covering CUDA setup, supported NVIDIA GPU architectures, and Windows MSVC compiler setup in #19, contributed by Yipeng Sun and Daniil Yefimov.
Added a Pixi documentation environment and preview/build commands, migrated documentation deployment to GitHub Pages artifact actions, and updated contributor instructions in #37, contributed by Zhihao Dai.
Removed the unused root requirements.txt in #40, contributed by Copilot and Zhihao Dai.
Added named Pixi platforms for Linux and Windows CPU builds and CUDA 12.6, 13.0, and 13.2 builds, with matching CUDA toolchains and updated development and benchmark commands in #20, contributed by Zhihao Dai.
Added GitHub issue and pull request templates in #25, contributed by Zhihao Dai.

Migrated the cross-platform CPU test matrix to Pixi for Python 3.11 and 3.14, added lower-bound tests with Python 3.11 and PyTorch 2.8.0 and Python 3.15 preview coverage, and restricted test workflow permissions in #43, contributed by Zhihao Dai.
Added a CPU test job using the frozen Pixi lockfile in #44, contributed by Zhihao Dai.
Updated requests from 2.34.0 to 2.34.2 in the inference dependencies in #35, contributed by Dependabot and Zhihao Dai.
Hardened Pixi dependency resolution with a seven-day package release cooldown (except for xlstm, mlstm_kernels, and flashrnn), disabled dependency wheel builds, and required Pixi 0.67.0 or newer in #24, contributed by Zhihao Dai and Copilot Autofix.
Enabled weekly Dependabot version updates for the root Python dependencies in #28, contributed by Zhihao Dai.
Added a security policy documenting supported versions and private vulnerability reporting in #23, contributed by Copilot and Zhihao Dai.
Pinned GitHub Actions to commit SHAs and updated action versions in #27, contributed by Copilot and Zhihao Dai.
Added Visual Studio developer-shell initialization for Windows builds in #27, contributed by Copilot and Zhihao Dai.

Fixed TiRex-2 functionality on macOS for CPU and MPS backends in #10, contributed by Suad0.
Fixed TiRex-2 functionality on Windows for CPU and CUDA backends in #5, contributed by Daniil Yefimov.
Relaxed package requirements to make installation via pip more flexible in #12 and #13, contributed by Daniil Yefimov.
Added an option to use Flex Attention in #6, contributed by danieleb1861.

Initial TiRex-2 release, contributed by martinloretzzz in the initial commit.