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Updated in [July 09th, 2023]

The 2X Performance Plugin course focuses on leveraging advanced technologies such as TensorRT, ONNX, Olive, and other tools to significantly enhance performance in the field of AI. The course is designed to provide participants with the necessary knowledge and skills to utilize the AUTOMATIC1111's Stable Diffusion WebUI, along with the TensorRT extension, to achieve a doubling of performance. The course assumes a basic understanding of AI concepts and familiarity with Nvidia RTX graphics cards.
Throughout the course, learners will explore various topics related to improving performance, including the latest developments in TensorRT, Olive, DirectML, and other speed-related news. The limitations and requirements of implementing the double performance extension for SDUI using TensorRT will be discussed in detail. Participants will also gain hands-on experience by following step-by-step instructions on downloading and installing TensorRT from Nvidia, as well as the TensorRT plugin.
The course will guide learners through the process of preparing models for conversion to ONNX format, addressing potential errors such as the "RuntimeError: invalid unordered_map K, T key." They will learn how to convert models from ONNX to TensorRT, and the techniques for speeding up the conversion process. The course will provide insights into the necessary steps to be taken after the model conversion and will showcase the significant performance improvements achieved through the use of the plugin.
Additionally, the course will address the compatibility of various models such as LORAs, TIs, and others with the implemented enhancements. You will gain a comprehensive understanding of how to evaluate and apply the 2X Performance Plugin to their specific AI projects.
Through practical hands-on exercises and comprehensive explanations, you have been able to harness the power of advanced technologies to double their performance.
During the course, participants expressed excitement about the early-stage development of the technology and the potential it holds. You found the AUTOMATIC1111's Stable Diffusion WebUI, coupled with TensorRT, to be a powerful combination for achieving remarkable speed improvements. The integration of Nvidia RTX graphics cards further bolstered their confidence in the efficacy of the plugin.
Participants appreciated the clear breakdown of the necessary steps involved in implementing the plugin. From downloading and installing TensorRT from Nvidia to converting models from ONNX to TensorRT, they found the instructions to be concise and easy to follow. The troubleshooting guidance provided for common errors, such as the "RuntimeError: invalid unordered_map K, T key," proved invaluable in ensuring a smooth learning experience.
The practical demonstrations showcased the dramatic performance improvements achieved after applying the 2X Performance Plugin. Participants were particularly impressed by the before-and-after comparison, which illustrated the tangible impact of the plugin on their AI models. They were eager to explore the compatibility of their existing models, including LORAs, TIs, and others, and the instructors provided valuable insights in this regard.
Overall, the 2X Performance Plugin course has been a transformative learning experience for participants, equipping them with the necessary knowledge and skills to leverage cutting-edge technologies and elevate their AI projects to new heights of performance.