RNNCell#

classtorch.ao.nn.quantized.dynamic.RNNCell(input_size,hidden_size,bias=True,nonlinearity='tanh',dtype=torch.qint8)[source]#

An Elman RNN cell with tanh or ReLU non-linearity.A dynamic quantized RNNCell module with floating point tensor as inputs and outputs.Weights are quantized to 8 bits. We adopt the same interface astorch.nn.RNNCell,please seehttps://pytorch.org/docs/stable/nn.html#torch.nn.RNNCell for documentation.

Examples:

>>>rnn=nn.RNNCell(10,20)>>>input=torch.randn(6,3,10)>>>hx=torch.randn(3,20)>>>output=[]>>>foriinrange(6):...hx=rnn(input[i],hx)...output.append(hx)