diff options
Diffstat (limited to 'src/graph/nodes/ConvolutionLayer.cpp')
| -rw-r--r-- | src/graph/nodes/ConvolutionLayer.cpp | 14 |
1 files changed, 9 insertions, 5 deletions
diff --git a/src/graph/nodes/ConvolutionLayer.cpp b/src/graph/nodes/ConvolutionLayer.cpp index ae4a8d7e6b..53d06ea75f 100644 --- a/src/graph/nodes/ConvolutionLayer.cpp +++ b/src/graph/nodes/ConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -184,14 +184,17 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_node(Graph // Set weights and biases info if(_weights.tensor() == nullptr) { - _weights.set_info(TensorInfo(TensorShape(_conv_width, _conv_height, in->info()->dimension(2) / _num_groups, _ofm), + TensorInfo info = TensorInfo(TensorShape(_conv_width, _conv_height, in->info()->dimension(2) / _num_groups, _ofm), in->info()->num_channels(), in->info()->data_type(), - in->info()->fixed_point_position())); + in->info()->fixed_point_position()); + info.set_quantization_info(_weights_quant_info); + _weights.set_info(std::move(info)); } if(_biases.has_accessor() && _biases.tensor() == nullptr) { - _biases.set_info(TensorInfo(TensorShape(_ofm), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); + DataType dt = in->info()->data_type(); + _biases.set_info(TensorInfo(TensorShape(_ofm), in->info()->num_channels(), is_data_type_quantized_asymmetric(dt) ? DataType::S32 : dt, in->info()->fixed_point_position())); } std::unique_ptr<arm_compute::IFunction> func; @@ -213,7 +216,8 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_node(Graph TensorShape output_shape = calculate_convolution_layer_output_shape(in->info()->tensor_shape(), _weights.info().tensor_shape(), _conv_info); // Output auto inizialitation if not yet initialized - arm_compute::auto_init_if_empty(*out->info(), output_shape, 1, in->info()->data_type(), in->info()->fixed_point_position()); + arm_compute::auto_init_if_empty(*out->info(), output_shape, 1, in->info()->data_type(), in->info()->fixed_point_position(), + (_out_quant_info.empty()) ? in->info()->quantization_info() : _out_quant_info); // Create appropriate convolution function if(_num_groups == 1) |