symtorch 0.0.0

Symbolic Expressions in PyTorch

---

Fast, optimisable, symbolic expressions in PyTorch.

>>> from symtorch import symtorchify
>>> f = symtorchify("x**2 + 2.5*x + 1.7")
>>> f
x²+2.5x+1.7
>>> len(list(f.parameters()))
2
>>> import torch
>>> f.evalf({"x": torch.tensor(2.0)})
tensor([10.7000], grad_fn=<AddBackward0>)

Installation

pip install symtorch

Features and Documentation

What about SymPyTorch?

This package attempts to supersede the amazing Patrick Kidger's original SymPyTorch. Useful features improvements here are:

• implementations of state_dict and load_state_dict for all SymTorch objects, allowing for automated saving and loading via the native PyTorch mechanisms
• plays nicely with TorchScript, allowing for integration into C++ code
• a SymbolAssignment helper class to enable "drag-and-drop" replace of existing NN components with symbolic ones:

>>> model = nn.Sequential(
    SymbolAssignment(["a", "b"]), 
    symtorchify("3*a + b")
)
>>> model(torch.tensor([[1, 2], [3, 4]]))
tensor([[ 5.],
        [13.]], grad_fn=<AddBackward0>)