Annexure 6: PyTorch Troubleshooting and Error-Handling Guide.
Abstract: Below is the complete Annexure 6: PyTorch Troubleshooting and Error-Handling Guide . **ANNEXURE 6 PyTorch Troubleshooting and Error-Handling Guide** This annexure provides a comprehensive reference to common PyTorch errors, their causes, and step-by-step solutions. It is designed to help learners, researchers, and developers debug PyTorch code effectively and avoid recurring mistakes. 1. Introduction Despite PyTorch being a flexible and developer-friendly deep-learning framework, beginners and even advanced users frequently encounter errors—especially related to tensors, shapes, gradients, CUDA, and data handling. This annexure covers: Common error messages Likely root causes How to fix them Preventive practices Debugging techniques Tools inside and outside PyTorch for diagnosing issues 2. Common PyTorch Errors and Their Solutions 2.1 Shape Mismatch Errors Error Example RuntimeError: mat1 and mat2 shapes cannot be multiplied (32x1...