Method configure

src/cpu/operators/CpuFullyConnected.cpp:233–360

}

void CpuFullyConnected::configure(const ITensorInfo      *src,
                                  const ITensorInfo      *weights,
                                  const ITensorInfo      *biases,
                                  ITensorInfo            *dst,
                                  FullyConnectedLayerInfo fc_info,
                                  const WeightsInfo      &weights_info)
{
    ARM_COMPUTE_TRACE_EVENT(ARM_COMPUTE_PROF_CAT_CPU, ARM_COMPUTE_PROF_LVL_CPU, "CpuFullyConnected::configure");
    // Perform validate step
    ARM_COMPUTE_ERROR_ON_NULLPTR(src, weights, dst);
    ARM_COMPUTE_ERROR_THROW_ON(
        CpuFullyConnected::validate(src, weights, biases != nullptr ? biases : nullptr, dst, fc_info, weights_info));
    ARM_COMPUTE_LOG_PARAMS(src, weights, biases, dst, fc_info);

    _needs_weights_conversion = false;
    _needs_weights_reshape    = fc_info.transpose_weights ? !fc_info.are_weights_reshaped : false;
    _needs_weights_reshape    = _needs_weights_reshape && !fc_info.retain_internal_weights;
    _is_fc_after_conv         = true;
    _is_quantized_asymmetric  = is_data_type_quantized_asymmetric(src->data_type());
    _is_prepared              = false;
    _trans_weights_idx        = AuxTensorIdx::Count;
    _enable_fast_math         = fc_info.enable_fast_math;
    _fixed_format             = weights_info.weight_format() != WeightFormat::UNSPECIFIED;
    _weight_format            = weights_info.weight_format();
    _dynamic_weights          = !weights->are_values_constant() && _needs_weights_reshape;

    // With the Fully Connected layer we can have 4 different cases:
    //  1) Convolution layer -> Fully Connected layer without batches
    //  2) Fully Connected layer -> Fully Connected layer without batches
    //  3) Convolution layer -> Fully Connected layer with batches
    //  4) Fully Connected layer -> Fully Connected layer with batches

    const ITensorInfo *weights_to_use = weights;

    // Check if we have a fully connected layer with batches
    const bool is_batched_fc_layer = dst->dimension(1) > 1;
    if (is_batched_fc_layer)
    {
        _is_fc_after_conv = (TensorShape::num_max_dimensions >= 4) &&
                            (std::equal(src->tensor_shape().cbegin() + 3, src->tensor_shape().cend(),
                                        dst->tensor_shape().cbegin() + 1));
    }
    else
    {
        _is_fc_after_conv = src->num_dimensions() > 1;
    }

    // Reshape weights if needed
    if (_needs_weights_reshape)
    {
        // Reshape the weights
        _transpose_weights = std::make_unique<kernels::CpuTransposeKernel>();
        _transpose_weights->configure(weights, &_reshaped_weights);
        _reshaped_weights.set_are_values_constant(weights->are_values_constant());

        weights_to_use     = &_reshaped_weights;
        _trans_weights_idx = AuxTensorIdx::TransposedWeights;
    }