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path: root/src/graph/backends/CL/CLFunctionsFactory.cpp
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Diffstat (limited to 'src/graph/backends/CL/CLFunctionsFactory.cpp')
-rw-r--r--src/graph/backends/CL/CLFunctionsFactory.cpp32
1 files changed, 24 insertions, 8 deletions
diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp
index 1b448fefd2..ad73a797e3 100644
--- a/src/graph/backends/CL/CLFunctionsFactory.cpp
+++ b/src/graph/backends/CL/CLFunctionsFactory.cpp
@@ -154,10 +154,16 @@ std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node,
ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1);
// Extract IO and info
- ICLTensor *input = get_backing_tensor(node.input(0));
- ICLTensor *weights = get_backing_tensor(node.input(1));
- ICLTensor *biases = get_backing_tensor(node.input(2));
- ICLTensor *output = get_backing_tensor(node.output(0));
+ ICLTensor *input = get_backing_tensor(node.input(0));
+ ICLTensor *weights = get_backing_tensor(node.input(1));
+ ICLTensor *biases = get_backing_tensor(node.input(2));
+ ICLTensor *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();
@@ -190,6 +196,8 @@ 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()
@@ -251,10 +259,16 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti
ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1);
// Extract IO and info
- ICLTensor *input = get_backing_tensor(node.input(0));
- ICLTensor *weights = get_backing_tensor(node.input(1));
- ICLTensor *biases = get_backing_tensor(node.input(2));
- ICLTensor *output = get_backing_tensor(node.output(0));
+ ICLTensor *input = get_backing_tensor(node.input(0));
+ ICLTensor *weights = get_backing_tensor(node.input(1));
+ ICLTensor *biases = get_backing_tensor(node.input(2));
+ ICLTensor *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();
@@ -275,6 +289,8 @@ 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()