AttributeError: module 'tensorflow.python.ops.nn' has no attribute 'legacy_seq2s eq'

最新推荐文章于 2025-05-30 17:36:50 发布

原创最新推荐文章于 2025-05-30 17:36:50 发布 · 2.5k 阅读

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CC 4.0 BY-SA版权

本文介绍使用TensorFlow实现循环神经网络(RNN)的过程，包括GRU单元的使用、Dropout技术的应用及动态RNN的搭建。针对不同版本的TensorFlow，文章还提供了关于sequence_loss函数调用方式变化的说明。

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tensorflow 版本改动较大 如
self.lossFct = tf.nn.legacy_seq2seq.sequence_loss
改成了 
self.lossFct = tf.nn.seq2seq.sequence_loss

import tensorflow as tf


print(tf.__version__)
def _run_rnn(self, inputs):
        # embedded inputs are passed in here
        self.initial_state = tf.zeros([self._batch_size, self._hidden_size], tf.float32)
        cell = tf.nn.rnn_cell.GRUCell(self._hidden_size)
        cell = tf.nn.rnn_cell.DropoutWrapper(cell, output_keep_prob=self._dropout_placeholder)
        cell = tf.nn.rnn_cell.MultiRNNCell([cell] * self._num_layers, state_is_tuple=False)

        outputs, last_state = tf.nn.dynamic_rnn(
            cell = cell,
            inputs = inputs,
            sequence_length = self.sequence_length,
            initial_state = self.initial_state
        )

        return outputs, last_state