Table of Contents

PyTorch Builder’s Companion Book

A Deep Dive into the Torch API for Engineers, Builders, and Curious Minds

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Contents

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📖 Preface

• Why This Book Exists
• Who Should Read This
• From Tensors to Gradients: How This Book Was Born
• What You’ll Learn (and What You Won’t)
• How to Read This Book (Even if You’re Just Starting Out)

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Part I – Getting Started with torch

     Chapter 1: What is torch?
     Chapter 2: Installation & Setup
     Chapter 3: Tensor Fundamentals

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Part II – torch API Deep Dive

     Chapter 4: torch.Tensor
     Chapter 5: Data Types and Devices
     Chapter 6: Random Sampling and Seeding
     Chapter 7: Math Operations
     Chapter 8: Broadcasting and Shape Ops
     Chapter 9: Autograd and Differentiation
     Chapter 10: Type Conversions and Casting

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Part III – Specialized Modules in torch

     Chapter 11: torch.linalg
     Chapter 12: torch.nn.functional
     Chapter 13: torch.special
     Chapter 14: torch.fft
     Chapter 15: torch.utils
     Chapter 16: Storage and Memory Format

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Part IV – torch in the Real World

     Chapter 17: Using torch with CUDA
     Chapter 18: Integration with NumPy
     Chapter 19: Debugging, Profiling, and Best Practices

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📎 Appendices

     A. Tensor Shapes Cheat Sheet
     B. PyTorch Idioms & Gotchas
     C. Full API Reference

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