{"library":"torchdiffeq","type":"library","category":null,"description":"torchdiffeq is a Python library providing ordinary differential equation (ODE) solvers implemented in PyTorch. It supports backpropagation through ODE solutions using the adjoint method, ensuring constant memory cost. The library offers a clean API for usage in deep learning applications, fully supporting GPU execution. The current version is 0.2.5, last released in November 2024, indicating an active development and maintenance cadence.","language":"python","status":"active","version":"0.2.5","tags":["PyTorch","ODE solvers","deep learning","differentiable programming","adjoint method","neural ODEs"],"last_verified":"Fri May 22","install":[{"cmd":"pip install torchdiffeq","imports":["from torchdiffeq import odeint","from torchdiffeq import odeint_adjoint as odeint"]}],"homepage":null,"github":"https://github.com/rtqichen/torchdiffeq","docs":null,"changelog":null,"pypi":"https://pypi.org/project/torchdiffeq/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":40,"avg_install_s":70.9,"avg_import_s":7.77,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/torchdiffeq/compatibility"}}