public AttentionUnit(string name, int hiddenDim, int contextDim, int deviceId, bool enableCoverageModel, bool isTrainable)
{
m_name = name;
m_hiddenDim = hiddenDim;
m_contextDim = contextDim;
m_deviceId = deviceId;
m_enableCoverageModel = enableCoverageModel;
m_isTrainable = isTrainable;
Logger.WriteLine($"Creating attention unit '{name}' HiddenDim = '{hiddenDim}', ContextDim = '{contextDim}', DeviceId = '{deviceId}', EnableCoverageModel = '{enableCoverageModel}'");
m_Ua = new WeightTensor(new long[2] {
contextDim, hiddenDim
}, deviceId, normType: NormType.Uniform, name: $"{name}.{nameof(m_Ua)}", isTrainable: isTrainable);
m_Wa = new WeightTensor(new long[2] {
hiddenDim, hiddenDim
}, deviceId, normType: NormType.Uniform, name: $"{name}.{nameof(m_Wa)}", isTrainable: isTrainable);
m_bUa = new WeightTensor(new long[2] {
1, hiddenDim
}, 0, deviceId, name: $"{name}.{nameof(m_bUa)}", isTrainable: isTrainable);
m_bWa = new WeightTensor(new long[2] {
1, hiddenDim
}, 0, deviceId, name: $"{name}.{nameof(m_bWa)}", isTrainable: isTrainable);
m_V = new WeightTensor(new long[2] {
hiddenDim, 1
}, deviceId, normType: NormType.Uniform, name: $"{name}.{nameof(m_V)}", isTrainable: isTrainable);
if (m_enableCoverageModel)
{
m_Wc = new WeightTensor(new long[2] {
k_coverageModelDim, hiddenDim
}, deviceId, normType: NormType.Uniform, name: $"{name}.{nameof(m_Wc)}", isTrainable: isTrainable);
m_bWc = new WeightTensor(new long[2] {
1, hiddenDim
}, 0, deviceId, name: $"{name}.{nameof(m_bWc)}", isTrainable: isTrainable);
m_coverage = new LSTMCell(name: $"{name}.{nameof(m_coverage)}", hdim: k_coverageModelDim, dim: 1 + contextDim + hiddenDim, deviceId: deviceId, isTrainable: isTrainable);
}
}
