diff options
Diffstat (limited to 'src/graph/backends/NEON/NEFunctionFactory.cpp')
| -rw-r--r-- | src/graph/backends/NEON/NEFunctionFactory.cpp | 32 |
1 files changed, 24 insertions, 8 deletions
diff --git a/src/graph/backends/NEON/NEFunctionFactory.cpp b/src/graph/backends/NEON/NEFunctionFactory.cpp index 228af9ca6f..906378c565 100644 --- a/src/graph/backends/NEON/NEFunctionFactory.cpp +++ b/src/graph/backends/NEON/NEFunctionFactory.cpp @@ -140,10 +140,16 @@ std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *weights = get_backing_tensor(node.input(1)); - ITensor *biases = get_backing_tensor(node.input(2)); - ITensor *output = get_backing_tensor(node.output(0)); + ITensor *input = get_backing_tensor(node.input(0)); + ITensor *weights = get_backing_tensor(node.input(1)); + ITensor *biases = get_backing_tensor(node.input(2)); + ITensor *output = get_backing_tensor(node.output(0)); + + if(is_data_type_quantized_asymmetric(input->info()->data_type())) + { + biases->info()->set_data_type(DataType::S32); + } + const PadStrideInfo conv_info = node.convolution_info(); const ConvolutionMethod conv_algorithm = node.convolution_method(); @@ -175,6 +181,8 @@ std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, // Log info ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name << " Data Type: " << input->info()->data_type() + << " Input QuantInfo: " << input->info()->quantization_info() + << " Weights QuantInfo: " << weights->info()->quantization_info() << " Input shape: " << input->info()->tensor_shape() << " Weights shape: " << weights->info()->tensor_shape() << " Output shape: " << output->info()->tensor_shape() @@ -234,10 +242,16 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *weights = get_backing_tensor(node.input(1)); - ITensor *biases = get_backing_tensor(node.input(2)); - ITensor *output = get_backing_tensor(node.output(0)); + ITensor *input = get_backing_tensor(node.input(0)); + ITensor *weights = get_backing_tensor(node.input(1)); + ITensor *biases = get_backing_tensor(node.input(2)); + ITensor *output = get_backing_tensor(node.output(0)); + + if(is_data_type_quantized_asymmetric(input->info()->data_type())) + { + biases->info()->set_data_type(DataType::S32); + } + const PadStrideInfo conv_info = node.convolution_info(); const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method(); @@ -258,6 +272,8 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti // Log info ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name << " Data Type: " << input->info()->data_type() + << " Input QuantInfo: " << input->info()->quantization_info() + << " Weights QuantInfo: " << weights->info()->quantization_info() << " Input shape: " << input->info()->tensor_shape() << " Weights shape: " << weights->info()->tensor_shape() << " Output shape: " << output->info()->tensor_shape() |