@@ -17,9 +17,9 @@ Then we'll switch to its more complicated versions, namely LSTM which helps gett ### This repo. is under construction However, you may start by reading the following tutorials: - [Vanilla RNN for Digit Classification](https://github.com/easy-tensorflow/easy-tensorflo...
# Unstack to get a list of 'timesteps' tensors of shape (batch_size, n_input) num_examples = tf.shape(x)[0] x = tf.unstack(x, timesteps, 1) # Define a rnn cell with tensorflow cell = tf.nn.rnn_cell.LSTMCell(num_hidden) w_repeated = tf.tile(tf.expand_dims(weights, 0),...
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Simple and comprehensive tutorials in TensorFlow. Contribute to easy-tensorflow/easy-tensorflow development by creating an account on GitHub.
Quick run NLP in many task 快速运行分类、序列标注、匹配、生成等NLP任务的Tensorflow框架 (中文 NLP 支持分布式) - Qznan/QizNLP