tf.nn.rnn_cell貌似要弃用了。 将所有tf.nn.rnn_cell更改为tf.contrib.rnn 一个最简单的LSTM单元。先说一下用法。 __init__( numunits, # int类型,LSTM内部的单元数,即每个time_step的输出大小 forget_bias=1.0,…
首先输入X是一个 [batch_size,step,input_size] = [4,2,3] 的tensor,注意我们这里调用的是BasicRNNCell,只有一层循环网络,outputs是最后一层每个step的输出,它的结构是[batch_size,step,n_neurons] = [4,2,5],states是每一层的最后那个step的输出,由于本例中,我们的循环网络只有一个隐藏层,所以它就代表...
For Tensorflow 1.2 and Keras 2.0, the linetf.contrib.rnn.core_rnn_cell.BasicLSTMCellshould be replaced bytf.contrib.rnn.BasicLSTMCell.
use peep-hole connections: it is the basic baseline. For advanced models, please use the full @{tf.nn.rnn_cell.LSTMCell} that follows. """ def__init__(self, num_units, forget_bias=1.0, state_is_tuple=True, activation=None, reuse=None, name=None, dtype=None): """Initialize the b...
首先tf.nn.dynamic_rnn()的time_major是默认的false,故输入X应该是一个[batch_size,step,input_size]=[4,2,3] 的tensor,注意我们这里调用的是BasicRNNCell,只有一层循环网络,outputs是最后一层每个step的输出,它的结构是[batch_size,step,n_neurons]=[4,2,5] ,states是每一层的最后那个step的输出,由于本...
cell=lstm_cell()else: cell=gru_cell()returntf.contrib.rnn.DropoutWrapper(cell, output_keep_prob=self.keep_prob)#词向量映射with tf.device('/cpu:0'): embedding= tf.get_variable('embedding', [self.config.vocab_size, self.config.embedding_dim]) ...
class BasicLSTMCell(LayerRNNCell): """Basic LSTM recurrent network cell. The implementation is based on: http:///abs/1409.2329. We add forget_bias (default: 1) to the biases of the forget gate in order to reduce the scale of forgetting in the beginning of the training. ...
@tf_export("nn.rnn_cell.BasicLSTMCell")classBasicLSTMCell(LayerRNNCell):"""Basic LSTM recurrent network cell. The implementation is based on: http://arxiv.org/abs/1409.2329. We add forget_bias (default: 1) to the biases of the forget gate in order to ...
tf.contrib.rnn.BasicLSTMCell(rnn_unit)函数的解读 函数功能解读 函数代码实现 1.2. @tf_export("nn.rnn_cell.BasicLSTMCell")3. class BasicLSTMCell(LayerRNNCell):4. """Basic LSTM recurrent network cell.5.6. The implementation is based on: http://arxiv.org/abs/1409.2329.7.8. We add forget_...
"""Initialize the basic LSTM cell. 基本LSTM递归网络单元。 实现基于:http://arxiv.org/abs/1409.2329。 我们在遗忘门的偏见中加入了遗忘偏见(默认值:1),以减少训练开始时的遗忘程度。 它不允许细胞剪切(一个投影层),也不使用窥孔连接:它是基本的基线。对于高级模型,请使用完整的@{tf.n .rnn_cell. lstm...