Tensorflow

Photo Credit Introduction The Tensorflow Profiler in the upcoming Tensorflow 2.2 release is a much-welcomed addition to the ecosystem. For image-related tasks, often the bottleneck is the input pipeline. But you also don’t want to spend time optimizing the input pipeline unless it is necessary. The Tensorflow Profiler makes pinpointing the bottleneck of the training process much easier, so you can decide where the optimization effort should be put into. ...

Photo Credit Executive Summary TensorFlow has become much easier to use: As an experience PyTorch developer who only knows a bit of TensorFlow 1.x, I was able to pick up TensorFlow 2.x in my spare time in 60 days and do competitive machine learning. TPU has never been more accessible: The new interface to TPU in TensorFlow 2.1 works right out of the box in most cases and greatly reduces the development time required to make a model TPU-compatible. Using TPU drastically increases the iteration speed of experiments. We present a case study of solving a Q&A labeling problem by fine-tuning the RoBERTa-base model from huggingface/transformer library: Codebase Colab TPU training notebook Kaggle Inference Kernel High-level library TF-HelperBot to provide more flexibility than the Keras interface. (TensorFlow 2.1 and TPU are also a very good fit for CV applications. A case study of solving an image classification problem will be published in about a month.) Acknowledgment I was granted free access to Cloud TPUs for 60 days via TensorFlow Research Cloud. It was for the TensorFlow 2.0 Question Answering competition. I chose to do this simpler Google QUEST Q&A Labeling competition first but unfortunately couldn’t find enough time to go back and do the original one (sorry!). ...

Photo by Josh Gordon on Unsplash The new Tensorflow 2.0 is going to standardize on Keras as its High-level API. The existing Keras API will mostly remain the same, while Tensorflow features like eager execution, distributed training and other deeper Tensorflow integration will be added or improved. I think it’s a good time to revisit Keras as someone who had switched to use PyTorch most of the time. ...