COMPMID-2452: Add mnist example

* Add small-mnist example
* Add PrintAccessor
* Add DequantizationLayer graph node

Change-Id: I7bc8011e5a602f40fa3c47b231a2a69c804e78c2
Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2274
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 38 insertions, 0 deletions

diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 02bfe9dc22..960011c1e2 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -607,6 +607,44 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti
     return func;
 }
 
+/** Create a backend dequantize layer function
+ *
+ * @tparam DequantizationLayer Function Backend dequantize function
+ * @tparam TargetInfo          Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend dequantize layer function
+ */
+template <typename DequantizationLayerFunction, typename TargetInfo>
+std::unique_ptr<IFunction> create_dequantization_layer(DequantizationLayerNode &node)
+{
+    validate_node<TargetInfo>(node, 1 /* expected inputs */, 1 /* expected outputs */);
+
+    // Extract IO and info
+    typename TargetInfo::TensorType *input  = get_backing_tensor<TargetInfo>(node.input(0));
+    typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0));
+
+    ARM_COMPUTE_ERROR_ON(input == nullptr);
+    ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+    // Create and configure function
+    auto func = support::cpp14::make_unique<DequantizationLayerFunction>();
+    func->configure(input, output);
+
+    // Log info
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+                               << node.name()
+                               << " Type: " << node.type()
+                               << " Target: " << TargetInfo::TargetType
+                               << " Data Type: " << input->info()->data_type()
+                               << " Input shape: " << input->info()->tensor_shape()
+                               << " Input quantization info: " << output->info()->quantization_info()
+                               << " Output shape: " << output->info()->tensor_shape()
+                               << std::endl);
+
+    return std::move(func);
+}
 /** Create a backend detection output layer function
  *
  * @tparam DetectionOutputLayer Function Backend detection output function