Source: onnx Section: science Homepage: https://onnx.ai Priority: optional Standards-Version: 4.5.0 Vcs-Git: https://salsa.debian.org/deeplearning-team/onnx.git Vcs-Browser: https://salsa.debian.org/deeplearning-team/onnx Maintainer: Debian Deep Learning Team Uploaders: Mo Zhou Build-Depends: cmake, debhelper-compat (= 12), dh-exec, dh-python, libprotobuf-dev, protobuf-compiler, pybind11-dev, python3-all-dev, python3-protobuf , python3-pybind11, python3-pytest , python3-pytest-runner, python3-tabulate Rules-Requires-Root: no Package: python3-onnx Architecture: any Depends: ${misc:Depends}, ${python3:Depends}, ${shlibs:Depends} Provides: ${python3:Provides} Description: Open Neural Network Exchange (ONNX) (Python) Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Initially onnx focuses on the capabilities needed for inferencing (evaluation). . Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are developing ONNX support. Enabling interoperability between different frameworks and streamlining the path from research to production will increase the speed of innovation in the AI community. . This package contains the python interface. Package: libonnx1 Architecture: any Multi-Arch: same Depends: ${misc:Depends}, ${shlibs:Depends} Description: Open Neural Network Exchange (ONNX) (libs) Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Initially onnx focuses on the capabilities needed for inferencing (evaluation). . Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are developing ONNX support. Enabling interoperability between different frameworks and streamlining the path from research to production will increase the speed of innovation in the AI community. . This package contains the shared objects. Package: libonnxifi Architecture: any Multi-Arch: same Depends: ${misc:Depends}, ${shlibs:Depends} Description: Open Neural Network Exchange (ONNX) (ONNXIFI) Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Initially onnx focuses on the capabilities needed for inferencing (evaluation). . Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are developing ONNX support. Enabling interoperability between different frameworks and streamlining the path from research to production will increase the speed of innovation in the AI community. . This package contains the libonnxifi.so shared object. Package: libonnx-dev Architecture: any Multi-Arch: same Depends: libonnx1 (= ${binary:Version}), libonnxifi (= ${binary:Version}), ${misc:Depends} Description: Open Neural Network Exchange (ONNX) (dev) Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Initially onnx focuses on the capabilities needed for inferencing (evaluation). . Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are developing ONNX support. Enabling interoperability between different frameworks and streamlining the path from research to production will increase the speed of innovation in the AI community. . This package contains the development files. Package: libonnx-testdata Architecture: all Multi-Arch: foreign Depends: ${misc:Depends} Description: Open Neural Network Exchange (ONNX) (test data) Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Initially onnx focuses on the capabilities needed for inferencing (evaluation). . Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are developing ONNX support. Enabling interoperability between different frameworks and streamlining the path from research to production will increase the speed of innovation in the AI community. . This package contains the test data.