Source: armnn Section: devel Priority: optional Maintainer: Francis Murtagh Uploaders: Wookey Build-Depends: libboost-test-dev (>= 1.64), libboost-system-dev (>= 1.64), libboost-filesystem-dev (>= 1.64), libboost-log-dev (>= 1.64), libboost-program-options-dev (>= 1.64), cmake, debhelper-compat (= 12), valgrind, libflatbuffers-dev, libarm-compute-dev [arm64 armhf], swig (>= 4.0.1-5), dh-python, python3-all, python3-setuptools, python3-dev, python3-numpy, xxd, flatbuffers-compiler, chrpath Standards-Version: 4.5.0 Vcs-Git: https://salsa.debian.org/deeplearning-team/armnn.git Vcs-Browser: https://salsa.debian.org/deeplearning-team/armnn Package: libarmnn22 Architecture: amd64 arm64 armhf i386 mipsel mips64el ppc64el Multi-Arch: same Depends: ${shlibs:Depends}, ${misc:Depends} Suggests: libarmnntfliteparser22 (= ${binary:Version}), python3-pyarmnn (= ${binary:Version}) Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the shared library package. Package: libarmnn-dev Architecture: amd64 arm64 armhf i386 mipsel mips64el ppc64el Multi-Arch: same Depends: libarmnn22 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends} Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the development package containing header files. Package: libarmnntfliteparser22 Architecture: amd64 arm64 armhf i386 mipsel mips64el ppc64el Multi-Arch: same Depends: libarmnn22 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends} Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the shared library package. Package: libarmnntfliteparser-dev Architecture: amd64 arm64 armhf i386 mipsel mips64el ppc64el Multi-Arch: same Depends: libarmnn-dev (= ${binary:Version}), libarmnntfliteparser22 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends} Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the development package containing header files. Package: python3-pyarmnn Architecture: amd64 arm64 armhf i386 mipsel mips64el ppc64el Depends: libarmnn22 (= ${binary:Version}), libarmnntfliteparser22 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends}, ${python3:Depends} Description: PyArmNN is a python extension for the Armnn SDK PyArmNN provides interface similar to Arm NN C++ Api. . PyArmNN is built around public headers from the armnn/include folder of Arm NN. PyArmNN does not implement any computation kernels itself, all operations are delegated to the Arm NN library. Package: libarmnn-cpuacc-backend22 Architecture: armhf arm64 Multi-Arch: same Depends: libarmnn22 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends} Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the dynamically loadable Neon backend package. Package: libarmnnaclcommon22 Architecture: armhf arm64 Multi-Arch: same Depends: libarmnn22 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends} Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the common shared library used by Arm Compute Library backends. Package: libarmnn-cpuref-backend22 Architecture: amd64 arm64 armhf i386 mipsel mips64el ppc64el Multi-Arch: same Depends: libarmnn22 (= ${binary:Version}), libarmnnaclcommon22 (= ${binary:Version}) [arm64 armhf], ${shlibs:Depends}, ${misc:Depends} Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the dynamically loadable Reference backend package. Package: libarmnn-gpuacc-backend22 Architecture: armhf arm64 Multi-Arch: same Depends: libarmnn22 (= ${binary:Version}), libarmnnaclcommon22 (= ${binary:Version}) [arm64 armhf], ${shlibs:Depends}, ${misc:Depends} Description: Arm NN is an inference engine for CPUs, GPUs and NPUs Arm NN is a set of tools that enables machine learning workloads on any hardware. It provides a bridge between existing neural network frameworks and whatever hardware is available and supported. On arm architectures (arm64 and armhf) it utilizes the Arm Compute Library to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as possible. On other architectures/hardware it falls back to unoptimised functions. . This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX. Arm NN takes networks from these frameworks, translates them to the internal Arm NN format and then through the Arm Compute Library, deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs. . This is the dynamically loadable CL backend package.