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SDK Version: 2.4.0

Change Log

v2.4.1 (2026-07-27)​

DX-Compiler Version

  • DX-COM: v2.4.0
  • DX-TRON: v2.0.1 (Deprecated)

Documentation-only hotfix; no changes to DX-COM or DX-TRON binaries.

Fixed​

  • Fixed broken internal links and reorganized several pages in the user manual for improved navigation.
  • Corrected the dx_com.pre_optimize() supported-model listings in the user manual: YOLOv10 is not a valid target and has been removed from the yolo_postprocess and PPU-type-2 migration guidance.

v2.4.0 (2026-06-16)​

DX-Compiler Version

  • DX-COM: v2.4.0
  • DX-TRON: v2.0.1 (Deprecated)
Deprecation Notice — DX-TRON

Starting with DX-Compiler v2.4.0, DX-TRON is deprecated and will be removed in a future release. No further feature updates or bug fixes are planned for DX-TRON. We recommend migrating to the new HTML graph viewer bundled with DX-COM (see Interactive HTML Graph Viewer below) for model inspection and visualization.

Deprecation Notice — PPU Type 2

Starting with DX-Compiler v2.4.0, the legacy PPU type 2 post-processing mode (used for YOLOv8-family DFL post-processing) is deprecated and will be removed in a future release. Compiling a model that uses PPU type 2 now emits a deprecation warning. Please migrate to the new dx_com.pre_optimize() API with the built-in YOLO post-processing passes (see Added below).

Changed​

  • PPU Type 2 Deprecated: The legacy PPU type 2 post-processing mode is now deprecated and emits a deprecation warning when used. See the Deprecation Notice above for the migration path.
  • Faster, Lighter Compilation: Reduced memory usage and improved compile time, especially on large models.
  • Expanded Python Version Support: In addition to Python 3.8–3.12, DX-COM now supports Python 3.13 and 3.14.

Fixed​

  • Fixed a Python API issue where models expecting integer inputs were sometimes fed float data, causing accuracy degradation.
  • Fixed several Q-PRO / DXQ quantization crashes and stability issues observed on real models.
  • Fixed multiple compilation errors and runtime issues caused by tiling, partitioning, and memory allocation in models containing Split, Concat, Reshape, Bilinear Resize, Clip, or odd spatial dimensions.
  • Fixed compatibility issues with NumPy 2.4+ and onnxruntime ≥ 1.25.0.

Added​

  • Automated Q-PRO Configuration: Q-PRO quantization (formerly available only by hand-picking DXQ combinations) is now much easier to use. DX-COM can now automatically generate DXQ combinations for you and run Q-PRO under the hood, removing the need to manually tune the many DXQ knobs to get higher-accuracy quantization.
  • Quantization-Aware Training (QAT): Added end-to-end QAT support directly through dx_com.compile(). When the supplied config JSON includes a qmaster block, dx_com.compile() automatically switches to QAT mode and runs the training pipeline using the same dataset settings as PTQ calibration. Available from both the dxcom CLI and the Python API. A new fast_run flag is also available for quick QAT smoke tests. See Quantization-Aware Training (QAT).
  • QXNN Resume (Re-quantization without Recompile): Added a checkpoint-based QXNN resume flow available from both the dxcom CLI and the Python API. Once a model has been compiled, users can re-run quantization with different settings (e.g., a different calibration method) without repeating the earlier compile phases, dramatically shortening the iteration loop when tuning quantization quality.
  • Quantization Diagnosis Report (HTML): Added an HTML report that visualizes per-region quantization quality, flags high-severity regions, and includes ready-to-paste compile snippets to retry compilation with recommended settings. Enabled via the new quant_diagnosis option, available from both the dxcom CLI and dx_com.compile().
  • Interactive HTML Graph Viewer (replaces DX-TRON): DX-COM now produces a standalone HTML viewer for inspecting compiled models, including parameter shapes, CPU/NPU partition reasons, and cross-subgraph connections. This replaces the DX-TRON workflow (see Deprecation Notice above).
  • dx_com.pre_optimize() API: Added a new top-level dx_com.pre_optimize() API for applying ONNX-level pre-processing transforms before compilation, with built-in support for YOLO post-processing integration (detection and segmentation modes). See the Pre-Optimize API chapter.
  • Ubuntu 26.04 Validation: DX-COM is now validated on Ubuntu 26.04, in addition to the previously supported Linux distributions.

Known Issues​

  • Significant FPS degradation has been observed in models using PReLU as an activation function.

v2.3.1 (May 2026)​

DX-Compiler Version

  • DX-COM: v2.3.0
  • DX-TRON: v2.0.1

Fixed​

  • Fixed uninstall.sh not removing installed packages and extracted module directories.
    • dx_com Python package is now properly uninstalled via pip3 uninstall before the virtual environment is removed.
    • dxtron Debian package is now properly removed via apt-get remove.
    • dx_com/ and dx_tron/ directories are now deleted on uninstall.

Added​

  • Added --target=<dx_com|dx_tron|all> option to uninstall.sh (default: all), consistent with install.sh.

v2.3.0 (March 2026)​

DX-Compiler Version

  • dx_com : 2.3.0
  • dx_tron : 2.0.1

Changed​

  • Python Packaging: Relaxed Python package dependency constraints to improve installation flexibility.

  • Distribution: The standalone DX-COM executable distribution is deprecated. The user manual now documents the wheel-based workflow only.

  • Performance:

    • Reduced NPU inference latency for most models.
    • Improved compiler performance to reduce compilation time.

Fixed​

  • Compiler Stability: Fixed various DX-COM compiler stability issues.

Added​

  • TopK-Optimized Post-Processing Pipeline: Added an optimized post-processing pipeline for supported DFL-based YOLO models that applies TopK filtering before bounding box decoding, reducing CPU post-processing workload and improving runtime efficiency.
  • Batched Convolution Support: Added support for batched convolution.
  • Linux Distribution Validation: In addition to Ubuntu 20.04, 22.04, and 24.04, DX-COM v2.3.0 was also validated on Fedora 42-45, Red Hat 9-10, and CentOS Stream 9-10.

v2.2.1 (February 2026)​

DX-Compiler Version

  • dx_com : 2.2.1
  • dx_tron : 2.0.1

Changed​

  • None

Fixed​

  • DXQ Quantization: Fixed DXQ enhanced quantization option bugs.
  • Python Wheel Package: Fixed PPU compilation bug for Python 3.8, 3.9, and 3.10.
  • Input Validation: Fixed an issue where compilation proceeded without error when invalid model input names were specified.

Added​

  • GPU Quantization (JSON Config): Added quantization_device support in JSON configuration file, enabling GPU-accelerated quantization via CLI (dxcom) in addition to the dx_com Python module. Available only with the Python wheel package installation.
  • GPU Auto-Detection: When quantization_device is not specified, DX-COM now automatically uses GPU if a CUDA-compatible GPU is available, otherwise falls back to CPU.

v2.2.0 (December 2025)​

DX-Compiler Version

  • dx_com : 2.2.0
  • dx_tron : 2.0.1

Changed​

  • None

Fixed​

  • Model Accuracy: Resolved accuracy degradation issue in the DeepLabV3PlusMobilenet-1 model from DX ModelZoo.

Added​

  • PPU Support: Extended PPU support to YOLOv8, YOLOv9, YOLOv10, YOLOv11, and YOLOv12.
  • Python Wheel Package: DX-COM is now available as a Python wheel package (in addition to the existing executable file), supporting Python 3.8, 3.9, 3.10, 3.11, and 3.12, enabling programmatic compilation using torch DataLoader without configuration files.
  • Multi-Input Model Support: Added support for multi-input models through torch DataLoader in the Python wheel package.
  • DX-TRON:
    • Debian package (.deb) installation support
    • Local web browser hosting (dxtron command)
    • Ubuntu 24.04 support

v2.1.0 (November 2025)​

DX-Compiler Version

  • dx_com : 2.1.0
  • dx_tron : 2.0.0

Changed​

  • Command-Line Interface: Removed deprecated command-line options: --jobs, --shrink, --info (or -i).

  • ONNX Support:

    • Removed restrictions on Split, Transpose, Reshape, Flatten, and Slice operators.
    • Clarified ONNX opset version support (versions 11-21 are supported; version 22 and above are not supported).

Added​

  • Command-Line Interface:

    • --aggressive_partitioning: Enables aggressive partitioning to maximize operations executed on NPU.
    • --opt_level {0,1}: Controls optimization level (default: 1).
    • --compile_input_nodes and --compile_output_nodes: Support for partial compilation.

  • ONNX Support: Added support for Gather operator.

  • Quantization: Reintroduced the DXQ enhanced quantization option (enhanced_scheme, DXQ-P0 to DXQ-P5), previously removed in dx_com v2.0.0.

  • PPU (Post-Processing Unit): Reinstated PPU support.

    • Supported models: YOLOv3, YOLOv4, YOLOv5, YOLOv7 (anchor-based), YOLOX (anchor-free).

v2.0.0 (September 2025)​

ONNX Support

  • Re-enabled support for the following operators:

    • Softmax
    • Slice

  • Newly added support for the following operator:

    • ConvTranspose

Model Support

  • Partial support for Vision Transformer (ViT) models

  • Verified with the following OpenCLIP models:

    • ViT-L-14, ViT-L-14-336, ViT-L-14-quickgelu
    • RN50x64, RN50x16
    • ViT-B-16, ViT-B-32-256, ViT-B-16-quickgelu

Compatibility and Deprecations

  • Compatibility with DX-RT versions earlier than v3.0.0 is not guaranteed
  • The DXQ enhanced quantization option (enhanced_scheme) was removed in dx_com v2.0.0 and reintroduced in dx_com v2.1.0
  • PPU (Post-Processing Unit) is no longer supported, and there are no current plans to reinstate it

v1.60.1 (June 2025)​

Bug Fixes

  • Internal bug fixes

Command-Line Interface Updates

  • Added support for:
    • -v option: Displays DX-COM module version
    • -i option: Displays internal module information
      → For usage, see: the CLI Execution section in Execution of DX-COM

ONNX Support

  • The following operators were deprecated and are scheduled to be re-supported in a future release:
    • Softmax
    • Slice
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