commit f2ed1b84caccb05c9e00e18b2cb2d2a2875b43fd
author Teresa Charlin <teresa.charlinreyes@arm.com> Tue Nov 24 15:11:54 2020 +0000
committer Teresa Charlin <teresa.charlinreyes@arm.com> Fri Nov 27 09:30:46 2020 +0000
tree 7424d1c413279b850679c31ba9ec0c9e6fdbc5e5
parent 98427a19b7e820283909d3e4ae00bc9447e461fc

IVGCVSW-5499 Missing validation for zero stride

* Convolution
* Depthwise Convolution

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I61b356fbffb176e9a05e08d9b6867d082b6712c8

src/backends/backendsCommon/WorkloadData.cpp

diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index 530dc48..d795e32 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -1260,6 +1260,14 @@
         ValidateBiasTensorQuantization(biasTensorInfo, inputTensorInfo, weightTensorInfo, descriptorName);
     }
 
+    if (m_Parameters.m_StrideX <= 0 || m_Parameters.m_StrideY <= 0  )
+    {
+        throw InvalidArgumentException(
+            fmt::format("{}: strideX (provided {}) and strideY (provided {}) "
+                        "cannot be either negative or 0.",
+                        descriptorName, m_Parameters.m_StrideX, m_Parameters.m_StrideY));
+    }
+
     ValidatePerAxisQuantization(inputTensorInfo,
                                 outputTensorInfo,
                                 weightTensorInfo,
@@ -1320,6 +1328,14 @@
                         descriptorName, m_Parameters.m_DilationX, m_Parameters.m_DilationX));
     }
 
+    if (m_Parameters.m_StrideX <= 0 || m_Parameters.m_StrideY <= 0  )
+    {
+        throw InvalidArgumentException(
+            fmt::format("{}: strideX (provided {}) and strideY (provided {}) "
+                        "cannot be either negative or 0.",
+                        descriptorName, m_Parameters.m_StrideX, m_Parameters.m_StrideY));
+    }
+
     const unsigned int channelIndex = (m_Parameters.m_DataLayout == DataLayout::NCHW) ? 1 : 3;
 
     // Expected weight shape: [ M, I, H, W ] - This shape does NOT depend on the data layout