seq2seq之tensorflow实现 - 知乎
https://zhuanlan.zhihu.com/p/79939961import tensorflow as tf import argparse from seq2seq.data_utils import load_data, create_mapping, get_batches, Batch, sentences_to_ids from seq2seq.seq2seq_tensorflow import Seq2SeqModel import os from sklearn.model_selection import train_test_split parser = argparse.
GitHub - google/seq2seq: A general-purpose encoder-decoder ...
github.com › google › seq2seqApr 17, 2017 · A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more. The official code used for the Massive Exploration of Neural Machine Translation Architectures paper. @ARTICLE {Britz:2017, author = { {Britz}, Denny and {Goldie}, Anna and ...
Overview - seq2seq
google.github.io › seq2seqtf-seq2seq is a general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more. Design Goals. We built tf-seq2seq with the following goals in mind:
Module: tfa.seq2seq | TensorFlow Addons
www.tensorflow.org › api_docs › pythonNov 15, 2021 · class BahdanauMonotonicAttention: Monotonic attention mechanism with Bahdanau-style energy function. class BaseDecoder: An RNN Decoder that is based on a Keras layer. class BasicDecoder: Basic sampling decoder for training and inference. class BasicDecoderOutput: Outputs of a tfa.seq2seq.BasicDecoder step.