IVGCVSW-3639 Add 5d tensor support
* Increased MaxNumOfTensorDimensions and fixed issues related to its use
* Fixed issues caused by assuming 5d tensors are invalid
* Updated ArmComputeTensorUtils for 5d tensors
* Added 5d tensor unit tests for add, mul, stack and reshape (needed by IVGCVSW-3527)
Signed-off-by: Matthew Jackson <matthew.jackson@arm.com>
Change-Id: I5bcd64942d0d04efcc6c5acb240ad4b88e010743
diff --git a/src/armnnTfLiteParser/test/InputOutputTensorNames.cpp b/src/armnnTfLiteParser/test/InputOutputTensorNames.cpp
index d42ae2e..d7a4371 100644
--- a/src/armnnTfLiteParser/test/InputOutputTensorNames.cpp
+++ b/src/armnnTfLiteParser/test/InputOutputTensorNames.cpp
@@ -61,12 +61,12 @@
"operator_codes": [ ],
"subgraphs": [{
"tensors": [ {
- "shape": [ 1, 1, 1, 1, 1 ],
+ "shape": [ 1, 1, 1, 1, 1, 1 ],
"type": "FLOAT32",
"name": "In",
"buffer": 0
}, {
- "shape": [ 1, 1, 1, 1, 1 ],
+ "shape": [ 1, 1, 1, 1, 1, 1 ],
"type": "FLOAT32",
"name": "Out",
"buffer": 1
@@ -81,6 +81,7 @@
BOOST_FIXTURE_TEST_CASE(InvalidTensorsThrowException, InvalidTensorsFixture)
{
// Tensor numDimensions must be less than or equal to MaxNumOfTensorDimensions
+ static_assert(armnn::MaxNumOfTensorDimensions == 5, "Please update InvalidTensorsFixture");
BOOST_CHECK_THROW(Setup(), armnn::InvalidArgumentException);
}
diff --git a/src/armnnTfLiteParser/test/Squeeze.cpp b/src/armnnTfLiteParser/test/Squeeze.cpp
index 7f6fb27..13261fa 100644
--- a/src/armnnTfLiteParser/test/Squeeze.cpp
+++ b/src/armnnTfLiteParser/test/Squeeze.cpp
@@ -106,11 +106,12 @@
struct SqueezeFixtureWithInvalidInput : SqueezeFixture
{
- SqueezeFixtureWithInvalidInput() : SqueezeFixture("[ 1, 2, 2, 1, 2 ]", "[ 1, 2, 2, 1 ]", "[ ]") {}
+ SqueezeFixtureWithInvalidInput() : SqueezeFixture("[ 1, 2, 2, 1, 2, 2 ]", "[ 1, 2, 2, 1, 2 ]", "[ ]") {}
};
BOOST_FIXTURE_TEST_CASE(ParseSqueezeInvalidInput, SqueezeFixtureWithInvalidInput)
{
+ static_assert(armnn::MaxNumOfTensorDimensions == 5, "Please update SqueezeFixtureWithInvalidInput");
BOOST_CHECK_THROW((SetupSingleInputSingleOutput("inputTensor", "outputTensor")),
armnn::InvalidArgumentException);
}