![]() ![]() Getting Started - Accelerate Your Scripts with nvFuser.Grokking PyTorch Intel CPU performance from first principles (Part 2).Grokking PyTorch Intel CPU performance from first principles.(beta) Static Quantization with Eager Mode in PyTorch.(beta) Quantized Transfer Learning for Computer Vision Tutorial.(beta) Dynamic Quantization on an LSTM Word Language Model.Extending dispatcher for a new backend in C++.Registering a Dispatched Operator in C++.Extending TorchScript with Custom C++ Classes.Extending TorchScript with Custom C++ Operators.Fusing Convolution and Batch Norm using Custom Function.Jacobians, Hessians, hvp, vhp, and more: composing function transforms.Forward-mode Automatic Differentiation (Beta).(beta) Channels Last Memory Format in PyTorch.(beta) Building a Simple CPU Performance Profiler with FX.(beta) Building a Convolution/Batch Norm fuser in FX.Real Time Inference on Raspberry Pi 4 (30 fps!).(optional) Exporting a Model from PyTorch to ONNX and Running it using ONNX Runtime.Deploying PyTorch in Python via a REST API with Flask.Reinforcement Learning (PPO) with TorchRL Tutorial.Preprocess custom text dataset using Torchtext.Language Translation with nn.Transformer and torchtext.Text classification with the torchtext library.NLP From Scratch: Translation with a Sequence to Sequence Network and Attention.NLP From Scratch: Generating Names with a Character-Level RNN.NLP From Scratch: Classifying Names with a Character-Level RNN.Fast Transformer Inference with Better Transformer.Language Modeling with nn.Transformer and torchtext.Optimizing Vision Transformer Model for Deployment.Transfer Learning for Computer Vision Tutorial.TorchVision Object Detection Finetuning Tutorial.Visualizing Models, Data, and Training with TensorBoard.Deep Learning with PyTorch: A 60 Minute Blitz.Introduction to PyTorch - YouTube Series.But the Backbone’s accompanying app is the cherry on top of an already excellent package, creating a unified interface for your gaming apps, screen captures and social gaming options. ![]() With an iPhone’s Lightning port automatically picking up connectivity to Backbone One, the team would have been forgiven for calling it a day there, with many an app’s auto-recognition of an accompanying controller doing the rest of the work for them when it came to button mapping and the like. Our one concern would be the durability of the Lightning connector – unless you’re particularly nimble-fingered, the snap-back telescoping nature of the device can mean your phone may at times hold the connection at an awkward angle until you’ve had time to adjust it.īut with Lightning connection pass-through charging of the phone, and the presence of a 3.5mm headphone jack on the bottom, it’s about as fully-featured as you could hope for. But we’ve been testing with a large iPhone 13 Pro, and have found it to be comfortable throughout. There will be some difference from paired device to device of course, as the size of iPhones can vary. The sticks have just the right amount of travel (though they are on the smaller side), with a responsively-springy D-Pad and satisfyingly-clicky buttons. It’s a supremely comfortable device from our testing.
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