COMPMID-1740: Fuse batch normalization with Convolution Layer at graph level
Change-Id: I77ca51c2c72783cc26a099a6a9c3210cdbbe822d
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/797
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 7242bc6..d0035d9 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -28,6 +28,7 @@
#include "arm_compute/graph/Tensor.h"
#include "arm_compute/graph/TypePrinter.h"
#include "arm_compute/graph/Types.h"
+#include "arm_compute/graph/backends/FusedConvolutionBatchNormalizationFunction.h"
#include "arm_compute/graph/backends/Utils.h"
#include "arm_compute/graph/nodes/Nodes.h"
@@ -135,11 +136,12 @@
validate_node<TargetInfo>(node, 5 /* expected inputs */, 1 /* expected outputs */);
// Extract IO and info
- typename TargetInfo::TensorType *input = get_backing_tensor<TargetInfo>(node.input(0));
- typename TargetInfo::TensorType *mean = get_backing_tensor<TargetInfo>(node.input(1));
- typename TargetInfo::TensorType *var = get_backing_tensor<TargetInfo>(node.input(2));
- typename TargetInfo::TensorType *beta = get_backing_tensor<TargetInfo>(node.input(3));
- typename TargetInfo::TensorType *gamma = get_backing_tensor<TargetInfo>(node.input(4));
+ typename TargetInfo::TensorType *input = get_backing_tensor<TargetInfo>(node.input(0));
+ typename TargetInfo::TensorType *mean = get_backing_tensor<TargetInfo>(node.input(1));
+ typename TargetInfo::TensorType *var = get_backing_tensor<TargetInfo>(node.input(2));
+ typename TargetInfo::TensorType *beta = get_backing_tensor<TargetInfo>(node.input(3));
+ typename TargetInfo::TensorType *gamma = get_backing_tensor<TargetInfo>(node.input(4));
+
typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0));
const float epsilon = node.epsilon();
const ActivationLayerInfo fused_act = node.fused_activation();
@@ -163,6 +165,61 @@
return std::move(func);
}
+/** Create a backend batch normalization layer function
+ *
+ * @tparam BatchNormalizationLayerFunction Backend batch normalization function
+ * @tparam TargetInfo Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend batch normalization layer function
+ */
+template <typename FusedLayerTypes, typename TargetInfo>
+std::unique_ptr<IFunction> create_fused_convolution_batch_normalization_layer(FusedConvolutionBatchNormalizationNode &node)
+{
+ validate_node<TargetInfo>(node, 7 /* expected inputs */, 1 /* expected outputs */);
+
+ // Extract IO and info
+ typename TargetInfo::TensorType *input = get_backing_tensor<TargetInfo>(node.input(0));
+ typename TargetInfo::TensorType *weights = get_backing_tensor<TargetInfo>(node.input(1));
+ typename TargetInfo::TensorType *biases = get_backing_tensor<TargetInfo>(node.input(2));
+ typename TargetInfo::TensorType *mean = get_backing_tensor<TargetInfo>(node.input(3));
+ typename TargetInfo::TensorType *var = get_backing_tensor<TargetInfo>(node.input(4));
+ typename TargetInfo::TensorType *beta = get_backing_tensor<TargetInfo>(node.input(5));
+ typename TargetInfo::TensorType *gamma = get_backing_tensor<TargetInfo>(node.input(6));
+
+ typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0));
+
+ const PadStrideInfo conv_info = node.convolution_info();
+ const unsigned int num_groups = node.num_groups();
+ const bool fast_math = node.fast_math_hint() == FastMathHint::Enabled;
+ const ActivationLayerInfo fused_act = node.fused_activation();
+ const float epsilon = node.epsilon();
+
+ const bool is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type());
+ if(is_quantized && biases != nullptr)
+ {
+ biases->info()->set_data_type(DataType::S32);
+ }
+
+ // Create and configure function
+ auto func = support::cpp14::make_unique<FusedConvolutionBatchNormalizationFunction<TargetInfo, FusedLayerTypes>>();
+ func->configure(input, weights, biases, output, mean, var, beta, gamma, epsilon, conv_info, num_groups, fast_math, fused_act);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+ << node.name()
+ << " Type: " << node.name()
+ << " Target: " << TargetInfo::TargetType
+ << " Data Type: " << input->info()->data_type()
+ << " 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 std::move(func);
+}
+
/** Create a backend bounding box transform layer function
*
* @tparam BoundingBoxTransformLayerFunction Backend bounding box transform function