不堪折磨的我发现了一篇优秀的关于transformer的技术博客The Illustrated Transformer,本文的大量插图和内容来自这篇博客(我做的大部分为翻译工作),同时pytorch实现完全参考guide annotating the paper with PyTorch implementation,它的TensorFlow实现是Tensor2Tensor包的一部分。
$ git clone https://github.com/lilianweng/transformer-tensorflow.git $cdtransformer-tensorflow $ pip install -r requirements.txt Train a Model #Check the help message:$ python train.py --help Usage: train.py [OPTIONS] Options: --seq-len INTEGER Input sequence length. [default: 20] --d-...
A TensorFlow Implementation of the Transformer: Attention Is All You NeedRequirementsNumPy >= 1.11.1 TensorFlow >= 1.2 (Probably 1.1 should work, too, though I didn't test it) regex nltkWhy This Project?I tried to implement the idea in Attention Is All You Need. They authors claimed that...
Implementing the Transformer Decoder from Scratch in TensorFlow and KerasBy Stefania Cristina on January 6, 2023 in Attention 15 Share Post Share There are many similarities between the Transformer encoder and decoder, such as their implementation of multi-head attention, layer normalization, and ...
by Alex Dosovitskiy et.al. showed for the first time how Transformer can be implemented for Computer Vision tasks and outperform CNN (e.g. ResNet) in image classification tasks. This post is a deep dive and step by step implementation of Vision Transformer (ViT) using TensorFlow 2.0. What...
This is almost an exact implementation of the original Transformer encoder. See the original paper: https://arxiv.org/abs/1706.03762 Also see: https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/models/transformer.py Args: ...
_dropout_rate, dropout_implementation="upscale_in_train", is_test=False) out = fluid.layers.matmul(weights_droped, transpose_v) else: out = fluid.layers.matmul(weights, transpose_v) # combine heads if len(out.shape) != 4: raise ValueError("Input(x) should be a 4-D Tensor.") trans...
This is aTensorflowimplementation ofSpatial Transformer NetworksbyMax Jaderberg, Karen Simonyan, Andrew ZissermanandKoray Kavukcuoglu, accompanying by two-part blogtutorial series. Spatial Transformer Networks(STN) is a differentiable module that can be inserted anywhere in ConvNet architecture to increase...
A TensorFlow implementation of the Transformer model.The Transformer model was originally proposed in "Attention is all you need" by Vaswani et al. (2017). Transformers are the current state-of-the-art in Natural Language tasks. Transformers are deep neural networks that replace CNNs and RNNs ...
🐝Tensorflow Implementation of Spatial Transformer Networks - GitHub - daviddao/spatial-transformer-tensorflow: 🐝Tensorflow Implementation of Spatial Transformer Networks