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Changelog update - tested on tools
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CHANGELOG.md

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# Changelog
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## 0.13.0 (unreleased)
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## 0.13.0
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- new: Introducing custom_args in TensorConfig for custom runners to use which
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allows dynamic shapes setup for TorchTensorRT compilation
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- new: autocast_dtype added Torch runner configuration to set the dtype for autocast
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- fix: Warn when using autocast with bfloat16 in Torch
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- fix: Pass runner configuration to runners in nav.profile
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[//]: <> (put here on external component update with short summary what change or link to changelog)
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- Version of external components used during testing:
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- [PyTorch 2.6.0a0+df5bbc0](https://github.com/pytorch/pytorch/commit/df5bbc09d191fff3bdb592c184176e84669a7157)
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- [TensorFlow 2.16.1](https://github.com/tensorflow/tensorflow/releases/tag/v2.16.1)
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- [TensorRT 10.6.0.26](https://docs.nvidia.com/deeplearning/tensorrt/release-notes/index.html)
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- [Torch-TensorRT 2.6.0a0](https://github.com/NVIDIA/Torch-TensorRT)
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- [ONNX Runtime 1.19.2](https://github.com/microsoft/onnxruntime/releases/tag/v1.19.2)
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- [Polygraphy](https://github.com/NVIDIA/TensorRT/tree/master/tools/Polygraphy/): 0.49.13
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- [GraphSurgeon](https://github.com/NVIDIA/TensorRT/tree/master/tools/onnx-graphsurgeon/): 0.5.2
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- [tf2onnx v1.16.1](https://github.com/onnx/tensorflow-onnx/releases/tag/v1.16.1)
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- Other component versions depend on the used framework containers versions.
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See its [support matrix](https://docs.nvidia.com/deeplearning/frameworks/support-matrix/index.html)
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for a detailed summary.
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## 0.12.0
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- new: simple and detailed reporting of the optimization process

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