From 5b8093c17044e8eaaaa42d96ba4902dee5791be4 Mon Sep 17 00:00:00 2001
From: Cathal Corbett <cathal.corbett@arm.com>
Date: Fri, 22 Oct 2021 11:12:07 +0100
Subject: IVGCVSW-6420: Constant flag in tensor info is not set correctly

!android-nn-driver:6532
!armnn-internal-tests:372451

  * Made fix to 2 out of 3 ConstTensor() constructors in Tensor.hpp to
    throw InvalidArgumentException when TensorInfo isConstant parameter
    is false.
  * Added new ConstTensor() constructor in Tensor.cpp to accept vector<>.data()
    using template<typename MemoryType>.
  * Fixed runtime->GetOutputTensorInfo()/GetInputTensorInfo() methods and
    called submethods to return TensorInfo& rather than TensorInfo.
  * Fixed all failing unit tests for CpuRef/CpuAcc/GpuAcc to ensure any
    ConstTensor created has it's TensorInfo isConstant set to true.
  * Added unit tests in TensorTest.cpp to ensure ConstTensor constructors
    throw InvalidArgumentException when TensorInfo isConstat parameter is
    false.
  * Added unit test to ensure an empty ConstTensor constructor will set
    TensorInfo isConatant to true.
  * Indentation fixes.
  * Fix to arm_tensor.i to add isConstant parameter to TensorInfo
    constructor. Added methods IsConstant() and SetConstant().
  * Fix to const_tensor.py to throw ValueError when TensorInfo
    isConstant is set to false when constructing a ConstTensor.
  * Fixed PyArmnn unit tests to set TensorInfo isConstant to
    True when ConstTensor is used.
  * Added unit tests in test_const_tensor.py to ensure ConstTensor
    constructors throw ValueError when TensorInfo isConstat parameter
    is false.

Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: I44e440dd0422c366d31bbdbc77ad2b4db0bde148
---
 src/armnn/test/ShapeInferenceTests.cpp | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

(limited to 'src/armnn/test/ShapeInferenceTests.cpp')

diff --git a/src/armnn/test/ShapeInferenceTests.cpp b/src/armnn/test/ShapeInferenceTests.cpp
index d3c928fec1..f808a0e349 100644
--- a/src/armnn/test/ShapeInferenceTests.cpp
+++ b/src/armnn/test/ShapeInferenceTests.cpp
@@ -233,14 +233,14 @@ TEST_CASE("ConcatTest")
     CreateGraphAndRunTest<ConcatLayer>({{ 1, 2, 1 }, { 1, 2, 1 }}, {{ 2, 2, 1 }}, descriptor, "concat");
 }
 
-TEST_CASE("ConstantTesst")
+TEST_CASE("ConstantTest")
 {
     Graph graph;
     TensorShape outputShape{ 1, 1, 3, 3 };
     auto layer = BuildGraph<ConstantLayer>(&graph, {}, "constant");
 
     const float Datum = 0.0f;
-    ConstTensor output0({outputShape, DataType::Float32}, &Datum);
+    ConstTensor output0({outputShape, DataType::Float32, 0.0f, 0, true}, &Datum);
     layer->m_LayerOutput = std::make_unique<ScopedTensorHandle>(output0);
 
     layer->GetOutputSlot(0).SetTensorInfo({{1, 1, 3, 3}, DataType::Float32});
@@ -294,7 +294,7 @@ TEST_CASE("Convolution2dTest")
                                                  "conv2d");
 
     const float Datum = 0.0f;
-    ConstTensor weights({{1, 1, 3, 3}, DataType::Float32}, &Datum);
+    ConstTensor weights({{1, 1, 3, 3}, DataType::Float32, 0.0f, 0, true}, &Datum);
     layer->m_Weight = std::make_unique<ScopedTensorHandle>(weights);
 
     RunShapeInferenceTest<Convolution2dLayer>(layer, {{ 1, 1, 4, 4 }});
@@ -339,7 +339,7 @@ TEST_CASE("DepthwiseConvolutionTest")
                                                         "depthwiseconv2d");
 
     const float Datum = 0.0f;
-    ConstTensor weights({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);
+    ConstTensor weights({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum);
     layer->m_Weight = std::make_unique<ScopedTensorHandle>(weights);
 
     RunShapeInferenceTest<DepthwiseConvolution2dLayer>(layer, {{ 8, 18, 1, 2 }});
@@ -371,7 +371,7 @@ TEST_CASE("DetectionPostProcessTest")
     descriptor.m_ScaleW = 5.0;
 
     const float Datum = 0.0f;
-    ConstTensor anchorsTensor({{1, 1, 3, 3}, DataType::Float32}, &Datum);
+    ConstTensor anchorsTensor({{1, 1, 3, 3}, DataType::Float32, 0.0f, 0, true}, &Datum);
 
     Graph graph;
 
@@ -460,7 +460,7 @@ TEST_CASE("LstmTest")
     auto layer = BuildGraph<LstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, descriptor, "lstm");
 
     float Datum = 0.0f;
-    ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);
+    ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum);
 
     layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(constTensor);
     layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(constTensor);
@@ -548,7 +548,7 @@ TEST_CASE("QLstmTest")
     auto layer = BuildGraph<QLstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, descriptor, "qlstm");
 
     float Datum = 0.0f;
-    ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);
+    ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum);
 
     layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(constTensor);
     layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(constTensor);
@@ -576,7 +576,7 @@ TEST_CASE("QuantizedLstmTest")
     auto layer = BuildGraph<QuantizedLstmLayer>(&graph, {inputShape, inputCellState, inputCellState},  "quatizedlstm");
 
     float Datum = 0.0f;
-    ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);
+    ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum);
 
     layer->m_QuantizedLstmParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(constTensor);
     layer->m_QuantizedLstmParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(constTensor);
-- 
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