Method configure

src/runtime/NEON/functions/NELSTMLayerQuantized.cpp:113–348

}

void NELSTMLayerQuantized::configure(const ITensor *input,
                                     const ITensor *input_to_input_weights,
                                     const ITensor *input_to_forget_weights,
                                     const ITensor *input_to_cell_weights,
                                     const ITensor *input_to_output_weights,
                                     const ITensor *recurrent_to_input_weights,
                                     const ITensor *recurrent_to_forget_weights,
                                     const ITensor *recurrent_to_cell_weights,
                                     const ITensor *recurrent_to_output_weights,
                                     const ITensor *input_gate_bias,
                                     const ITensor *forget_gate_bias,
                                     const ITensor *cell_bias,
                                     const ITensor *output_gate_bias,
                                     ITensor       *cell_state_in,
                                     const ITensor *output_state_in,
                                     ITensor       *cell_state_out,
                                     ITensor       *output_state_out)
{
    ARM_COMPUTE_TRACE_EVENT(ARM_COMPUTE_PROF_CAT_CPU, ARM_COMPUTE_PROF_LVL_CPU, "NELSTMLayerQuantized::configure");
    ARM_COMPUTE_ERROR_ON_NULLPTR(input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights,
                                 input_to_output_weights, recurrent_to_input_weights, recurrent_to_forget_weights,
                                 recurrent_to_cell_weights, recurrent_to_output_weights, input_gate_bias,
                                 forget_gate_bias, cell_bias, output_gate_bias, cell_state_in, output_state_in,
                                 cell_state_out, output_state_out);

    ARM_COMPUTE_ERROR_THROW_ON(NELSTMLayerQuantized::validate(
        input->info(), input_to_input_weights->info(), input_to_forget_weights->info(), input_to_cell_weights->info(),
        input_to_output_weights->info(), recurrent_to_input_weights->info(), recurrent_to_forget_weights->info(),
        recurrent_to_cell_weights->info(), recurrent_to_output_weights->info(), input_gate_bias->info(),
        forget_gate_bias->info(), cell_bias->info(), output_gate_bias->info(), cell_state_in->info(),
        output_state_in->info(), cell_state_out->info(), output_state_out->info()));

    ARM_COMPUTE_LOG_PARAMS(input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights,
                           input_to_output_weights, recurrent_to_input_weights, recurrent_to_forget_weights,
                           recurrent_to_cell_weights, recurrent_to_output_weights, input_gate_bias, forget_gate_bias,
                           cell_bias, output_gate_bias, cell_state_in, output_state_in, cell_state_out,
                           output_state_out);

    const int input_size  = input->info()->dimension(0);
    const int batch_size  = input->info()->dimension(1);
    const int output_size = input_to_input_weights->info()->dimension(1);

    const QuantizationInfo qweights = input_to_input_weights->info()->quantization_info(); // Weights quantization

    auto_init_if_empty(*cell_state_out->info(),
                       TensorInfo(TensorShape(batch_size, output_size), 1, DataType::QSYMM16, qsymm_4));
    auto_init_if_empty(*output_state_out->info(),
                       TensorInfo(TensorShape(batch_size, output_size), 1, DataType::QASYMM8, qasymm));

    _input_to_input_weights      = input_to_input_weights;
    _input_to_forget_weights     = input_to_forget_weights;
    _input_to_cell_weights       = input_to_cell_weights;
    _input_to_output_weights     = input_to_output_weights;
    _recurrent_to_input_weights  = recurrent_to_input_weights;
    _recurrent_to_forget_weights = recurrent_to_forget_weights;
    _recurrent_to_cell_weights   = recurrent_to_cell_weights;
    _recurrent_to_output_weights = recurrent_to_output_weights;
    _input_gate_bias             = input_gate_bias;