pytorch.txt
ARMv8 Cortex-A78E testing with a NVIDIA Jetson Orin NX Engineering Developer Kit (36.3.0-gcid-36191598 BIOS) and Orin on Ubuntu 22.04 via the Phoronix Test Suite.


all of them: 

	Processor: ARMv8 Cortex-A78E @ 1.98GHz (8 Cores), Motherboard: NVIDIA Jetson Orin NX Engineering Developer Kit (36.3.0-gcid-36191598 BIOS), Memory: 16GB, Disk: 128GB FORESEE XP1000F128G, Graphics: Orin, Network: Realtek RTL8111/8168/8411

	OS: Ubuntu 22.04, Kernel: 5.15.136-tegra (aarch64), Desktop: GNOME Shell 42.9, Display Server: X Server 1.21.1.4, Display Driver: NVIDIA, Vulkan: 1.3.251, Compiler: GCC 11.4.0 + CUDA 12.2, File-System: ext4, Screen Resolution: 6582x1234


TensorFlow Lite 2022-05-18
Model: SqueezeNet
Microseconds < Lower Is Better
all of them . 8886.22 |========================================================


TensorFlow Lite 2022-05-18
Model: Inception V4
Microseconds < Lower Is Better
all of them . 128466 |=========================================================


TensorFlow Lite 2022-05-18
Model: NASNet Mobile
Microseconds < Lower Is Better
all of them . 22370.4 |========================================================


TensorFlow Lite 2022-05-18
Model: Mobilenet Float
Microseconds < Lower Is Better
all of them . 6848.70 |========================================================


TensorFlow Lite 2022-05-18
Model: Mobilenet Quant
Microseconds < Lower Is Better
all of them . 3307.88 |========================================================


TensorFlow Lite 2022-05-18
Model: Inception ResNet V2
Microseconds < Lower Is Better
all of them . 117511 |=========================================================