self.rnn()defrnn(self):"""rnn模型"""deflstm_cell():#lstm核returntf.contrib.rnn.BasicLSTMCell(self.config.hidden_dim, state_is_tuple=True)defgru_cell():#gru核returntf.contrib.rnn.GRUCell(self.config.hidden_dim)defdropout():#为每一个rnn核后面加一个dropout层if(self.config.rnn =='lstm...
tf.contrib.rnn.BasicLSTMCell设置默认LSTM单元,隐含节点数hidden_size、gorget_bias(forget gate bias) 0,state_is_tuple True,接受返回state是2-tuple形式。训练状态且Dropout keep_prob小于1,1stm_cell接Dropout层,tf.contrib.rnn.DropoutWrapper函数。RNN堆叠函数 tf.contrib.rnn.MultiRNNCell 1stm_cell多层堆叠到...
"""Initialize the basic LSTM cell. Args: num_units: int, The number of units in the LSTM cell. forget_bias: float, The bias added to forget gates (see above). Must set to `0.0` manually when restoring from CudnnLSTM-trained checkpoints. state_is_tuple: If True, accepted and returne...
LSTM_cell=tf.contrib.rnn.BasicLSTMCell(128, dtype=float.32) 放一下官网给的源代码: def call(self, inputs, state): """Long short-term memory cell (LSTM).""" sigmoid = math_ops.sigmoid one = constant_op.constant(1, dtype=dtypes.int32) # Parameters of gates are concatenated into one...
When restoring from CudnnLSTM-trained checkpoints, must use `CudnnCompatibleLSTMCell` instead. """ 参数: num_units: int类型, LSTM单元中的单元数。 forget_bias: float类型,偏见添加到忘记门(见上面)。 从cudnnlstm训练的检查点恢复时,必须手动设置为“0.0”。
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_...
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 basic LSTM cell. ...
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 basic LSTM cell. ...
tf.contrib.rnn.BasicLSTMCell :new_c= (c*sigmoid(f+self._forget_bias) +sigmoid(i) *self._activation(j)) 所以forget_bias参数是为了减少训练过程中遗忘的规模。因为sigmoid(x)的特点是x越大越接近1,这样始终让里面的值有一个固定偏置,这样会使得sigmoid(f+self._forget_bias)不会太小,能记住之前更多...
定义语言模型class,PTBModel。初始化函数__init__(),参数,训练标记is_training、配置参数config、PTBInput类实例input_。读取input_的batch_size、num_steps,读取config的hidden_size(LSTM节点数)、vocab_size(词汇表大小)到本地变量。 tf.contrib.rnn.BasicLSTMCell设置默认LSTM单元,隐含节点数hidden_size、gorget_bi...