Method convertRNNBias

samples/sampleCharRNN/sampleCharRNN.cpp:481–493

\brief Converts RNN Biases from TensorFlow's format to TensorRT's format. \param input Biases that are stored in TensorFlow's format. \return Converted bias in TensorRT's format. \note TensorFlow bias parameters for BasicLSTMCell are formatted as: CellN: Bi, Bc, Bf, Bo TensorRT expects the format to be: CellN: Wi, Wc, Wf, Wo, Ri, Rc, Rf, Ro Since tensorflow already combines U and W, we double

//!       Since tensorflow already combines U and W,
//!       we double the size and set all of U to zero.
nvinfer1::Weights SampleCharRNNBase::convertRNNBias(nvinfer1::Weights input)
{
    auto mem = new samplesCommon::FloatMemory(input.count * 2);
    weightsMemory.emplace_back(mem);
    auto ptr = mem->raw();
    const float* iptr = static_cast<const float*>(input.values);
    int64_t count = 4 * mParams.hiddenSize;
    ASSERT(input.count == count);
    std::copy(iptr, iptr + count, ptr);
    float* shiftedPtr = ptr + count;
    std::fill(shiftedPtr, shiftedPtr + count, 0.0);
    return nvinfer1::Weights{input.type, ptr, input.count * 2};
}

nvinfer1::ILayer* SampleCharRNNLoop::addLSTMCell(SampleUniquePtr<nvinfer1::INetworkDefinition>& network,
    const LstmIO& inputTensors, nvinfer1::ITensor* sequenceSize, const LstmParams& params, LstmIO& outputTensors)