diff options
Diffstat (limited to 'arm_compute/graph/backends/FunctionHelpers.h')
| -rw-r--r-- | arm_compute/graph/backends/FunctionHelpers.h | 11 |
1 files changed, 7 insertions, 4 deletions
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h index a1cadcbf4c..1968ec3923 100644 --- a/arm_compute/graph/backends/FunctionHelpers.h +++ b/arm_compute/graph/backends/FunctionHelpers.h @@ -397,8 +397,10 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti biases->info()->set_data_type(DataType::S32); } - const PadStrideInfo conv_info = node.convolution_info(); - const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method(); + const PadStrideInfo conv_info = node.convolution_info(); + const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method(); + const unsigned int depth_multiplier = 1; + const ActivationLayerInfo fused_act = node.fused_activation(); // Create and configure function (we assume that functions have been validated before creation) std::unique_ptr<IFunction> func; @@ -407,13 +409,13 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti { std::tie(func, func_name) = create_named_function<typename DepthwiseConvolutionLayerFunctions::DepthwiseConvolutionLayer3x3>( std::string("DepthwiseConvolutionLayer3x3"), - input, weights, biases, output, conv_info); + input, weights, biases, output, conv_info, depth_multiplier, fused_act); } else { std::tie(func, func_name) = create_named_function<typename DepthwiseConvolutionLayerFunctions::GenericDepthwiseConvolutionLayer>( std::string("DepthwiseConvolutionLayer"), - input, weights, biases, output, conv_info); + input, weights, biases, output, conv_info, depth_multiplier, fused_act); } // Log info @@ -431,6 +433,7 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti << " Input shape: " << input->info()->tensor_shape() << " Weights shape: " << weights->info()->tensor_shape() << " Output shape: " << output->info()->tensor_shape() + << (fused_act.enabled() ? " " + to_string(fused_act.activation()) : "") << std::endl); return func; } |