Bridging the Gap: Unveiling the C++ Implementation Behind torch._C Functions

• torch._C is an extension module written in C++. It acts as a bridge between Python and the underlying C/C++ functionality of PyTorch.
• This module allows defining new data types like PyTorch tensors and calling functions written in C/C++.

Finding the C++ Implementation

The actual implementation of these functions resides in the PyTorch source code, but it's not directly exposed in the Python package. Here's a general idea:

1. Source Files: The C/C++ code for these functions is likely located in the PyTorch source codebase. You can find the source code on PyTorch's GitHub repository.
2. Build Process: PyTorch uses a build process that involves parsing header files (like THNN.h and THCUNN.h) containing function declarations.
3. Code Generation: A tool called cwrap reads these headers and generates Python bindings for the C/C++ functions. This creates the Python-accessible versions you see as torch._C.some_function.

Resources for Deep Dive

While directly finding the C++ code for individual functions might be cumbersome, here are resources to understand the bigger picture:

import torch

# Example function likely implemented in C++ and wrapped by torch._C
x = torch.randn(3, 3)  # Create a random tensor
y = torch._C.add(x, 5)  # Call a function from torch._C (assuming it adds 5 to each element)

print(y)

In this example:

1. We import the torch library.
2. We create a random tensor x using torch.randn.
3. We call the function torch._C.add (assuming it exists) to add 5 to each element of x. The actual implementation of add resides in C++.
4. We print the result y which will be a new tensor with the elements of x plus 5.

Important Note:

• This is a hypothetical example. Function names and functionalities within torch._C can vary depending on the PyTorch version.
• It's generally not recommended to directly modify functions within torch._C. The recommended approach is to use the Python functions exposed by the PyTorch library itself. These functions often provide a higher-level and user-friendly way to interact with the underlying C++ functionality.

1. Community Resources: