diff options
Diffstat (limited to 'arm_compute/graph/backends/FunctionHelpers.h')
-rw-r--r-- | arm_compute/graph/backends/FunctionHelpers.h | 10 |
1 files changed, 8 insertions, 2 deletions
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h index 5739773dfc..4a3f001671 100644 --- a/arm_compute/graph/backends/FunctionHelpers.h +++ b/arm_compute/graph/backends/FunctionHelpers.h @@ -265,6 +265,7 @@ std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, } const PadStrideInfo conv_info = node.convolution_info(); + const unsigned int num_groups = node.num_groups(); const ConvolutionMethod conv_algorithm = node.convolution_method(); const bool fast_math = node.fast_math_hint() == FastMathHint::Enabled; @@ -275,12 +276,14 @@ std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, if(conv_algorithm == ConvolutionMethod::Winograd) { + ARM_COMPUTE_ERROR_ON_MSG(num_groups != 1, "WinogradConvolutionLayer does not support grouping!"); std::tie(func, func_name) = create_named_memory_managed_function<typename ConvolutionLayerFunctions::WinogradConvolutionLayer>( std::string("WinogradConvolutionLayer"), mm, input, weights, biases, output, conv_info, ActivationLayerInfo(), fast_math); } else if(conv_algorithm == ConvolutionMethod::Direct) { + ARM_COMPUTE_ERROR_ON_MSG(num_groups != 1, "DirectConvolutionLayer does not support grouping!"); std::tie(func, func_name) = create_named_function<typename ConvolutionLayerFunctions::DirectConvolutionLayer>( std::string("DirectConvolutionLayer"), input, weights, biases, output, conv_info); @@ -289,19 +292,22 @@ std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, { std::tie(func, func_name) = create_named_memory_managed_function<typename ConvolutionLayerFunctions::GEMMConvolutionLayer>( std::string("GEMMConvolutionLayer"), mm, - input, weights, biases, output, conv_info); + input, weights, biases, output, conv_info, + WeightsInfo(), Size2D(1U, 1U), ActivationLayerInfo(), num_groups); } else { std::tie(func, func_name) = create_named_memory_managed_function<typename ConvolutionLayerFunctions::GenericConvolutionLayer>( std::string("GenericConvolutionLayer"), mm, - input, weights, biases, output, conv_info, WeightsInfo(), Size2D(1U, 1U), ActivationLayerInfo(), fast_math); + input, weights, biases, output, conv_info, + WeightsInfo(), Size2D(1U, 1U), ActivationLayerInfo(), fast_math, num_groups); } // Log info ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name << " Target " << TargetInfo::TargetType << " Data Type: " << input->info()->data_type() + << " Groups: " << num_groups << " Input QuantInfo: " << input->info()->quantization_info() << " Weights QuantInfo: " << weights->info()->quantization_info() << " Input shape: " << input->info()->tensor_shape() |