IVGCVSW-5826 Change weights layout for depthwise to [1,H,W,I*M]

 * This change is necessary because tflite uses a [1,H,W,I*M] format
   and uses the I*M dimension for per axis quantization. Our previous
   layout [M,I,H,W] can't handle the correlating quantization scales.
 * Updates Onnx-, TfLiteParser and TfliteDelegate
 * Updates the CpuRef, CpuAcc and GpuAcc backends
 * Adjusts unit tests
 * Adds test to ensure models with old layout can still be read and
   executed
 * Adds conversion function to previous layout [1,H,W,I*M] --> [M,I,H,W]
   which can be used by backend developers

!android-nn-driver:5553

Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: Ifef23368b8c3702cf315a5838d214f7dc13c0152

1 files changed, 2 insertions, 2 deletions

diff --git a/src/armnn/test/OptimizerTests.cpp b/src/armnn/test/OptimizerTests.cpp
index e68546c9dd..d4e2d499d5 100644
--- a/src/armnn/test/OptimizerTests.cpp
+++ b/src/armnn/test/OptimizerTests.cpp
@@ -340,7 +340,7 @@ TEST_CASE("DepthwiseConv2dValidateTensorShapesFromInputs")
 {
     Graph graph;
     const unsigned int inputShape[] = { 1, 2, 3, 3 };
-    const unsigned int weightsShape[] = { 1, 2, 3, 3 };
+    const unsigned int weightsShape[] = { 1, 3, 3, 2 };
     const unsigned int outputShape[] = { 1, 2, 1, 1 };
     CreateDepthwiseConvolution2dGraph(graph, inputShape, weightsShape, outputShape);
 
@@ -351,7 +351,7 @@ TEST_CASE("DepthwiseConv2dValidateTensorShapesFromInputsNhwc")
 {
     Graph graph;
     const unsigned int inputShape[] = { 1, 3, 3, 2 };
-    const unsigned int weightsShape[] = { 1, 2, 3, 3 };
+    const unsigned int weightsShape[] = { 1, 3, 3, 2 };
     const unsigned int outputShape[] = { 1, 1, 1, 2 };
     CreateDepthwiseConvolution2dGraph(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);