FX is a toolkit for developers to use to transform nn.Module instances. FX consists of three main components: a symbolic tracer, an intermediate representation, and Python code generation. A demonstration of these components in action: The symbolic tracer performs “symbolic execution” of the Python code.

torch.fx （以下简称 fx）是 PyTorch 推出的一个用于捕获和转换 PyTorch 程序（可以理解为神经网络结构）的纯 Python 系统。 Pytorch 这样的采用 动态计算图 执行模式的训练框架，给用户带来了极高的易用性，但是在某些情况下，用户也需要捕获和变换神经网络结构来做优化和分析（例如算子融合）。 简单来说，动态计算图适用于模型开发调试（训练阶段）， 静态计算图 适用于模型部署调优，这两者之间就产生了一个很大的 gap，因此 fx 为了修补这个 gap 就应运而生了。 fx …

Dec 15, 2021 · We apply this principle in this http URL, a program capture and transformation library for PyTorch written entirely in Python and optimized for high developer productivity by ML practitioners. We present case studies showing how this http URL enables workflows previously inaccessible in the PyTorch ecosystem.

FX’s front-end makes use of the dynamic nature of Python to intercept call-sites for various entities (PyTorch operators, Module invocations, and Tensor method invocations). The simplest way to get an FX graph is by using torch.fx.symbolic_trace. We can see how this works by …

We apply this principle in torch.fx, a program capture and transformation library for PyTorch written entirely in Python and optimized for high developer productivity by ML practitioners. We present case studies showing how torch.fx enables workflows previously inaccessible in the PyTorch ecosystem.

Mar 16, 2025 · torch.fx is a tool within PyTorch that allows you to capture and manipulate the symbolic representation of a PyTorch module. Instead of directly executing the code, FX traces the operations and creates a graph representing the module's structure and data flow. This is incredibly useful for things like:

In this tutorial, we are going to use FX to do the following: Build out a small class that will serve as a simple performance “profiler”, collecting runtime statistics about each part of the model from actual runs. For this tutorial, we are going to use the torchvision ResNet18 model for demonstration purposes.

Mar 16, 2025 · Instead of executing the code of your model directly, FX traces the intent of the code. It captures the operations (like addition, multiplication, convolutions, etc.) and how they relate to each other, without actually performing the calculations.

In this tutorial, we are going to use FX, a toolkit for composable function transformations of PyTorch, to do the following: Find patterns of conv/batch norm in the data dependencies. For the patterns found in 1), fold the batch norm statistics into the convolution weights.

Apr 18, 2021 · I just read about some of the new features of PyTorch 1.8 and noticed the introduction of the torch.fx module. I read the documentation and I kind of get what it does but I have two questions: What are the use cases?