commit ac2770a4bb6461bfbddec928bb6208f26f898f02
author Narumol Prangnawarat <narumol.prangnawarat@arm.com> Wed Apr 01 16:51:23 2020 +0100
committer Narumol Prangnawarat <narumol.prangnawarat@arm.com> Mon Apr 06 09:06:01 2020 +0100
tree c72f67f648b7aca2f4bccf69b05d185bf5f9ccad
parent 7ee5d2c3b3cee5a924ed6347fef613ee07b5aca7

IVGCVSW-4485 Remove Boost assert

 * Change boost assert to armnn assert
 * Change include file to armnn assert
 * Fix ARMNN_ASSERT_MSG issue with multiple conditions
 * Change BOOST_ASSERT to BOOST_TEST where appropriate
 * Remove unused include statements

Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I5d0fa3a37b7c1c921216de68f0073aa34702c9ff

src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp

diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
index 50ad667..c66027e 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -169,9 +169,9 @@
 void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset,
     const std::vector<B>& bias, float bScale, int32_t bOffset, uint32_t w, uint32_t h)
 {
-    BOOST_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()),
+    ARMNN_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()),
                      "Invalid type and parameter combination.");
-    BOOST_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()),
+    ARMNN_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()),
                      "Invalid type and parameter combination.");
 
     // Note we need to dequantize and re-quantize the image value and the bias.
@@ -183,7 +183,7 @@
             for (uint32_t x = 0; x < w; ++x)
             {
                 uint32_t offset = (i * h + y) * w + x;
-                BOOST_ASSERT(offset < v.size());
+                ARMNN_ASSERT(offset < v.size());
                 T& outRef = v[offset];
                 float dOutput = SelectiveDequantize(outRef, vScale, vOffset);
                 outRef = SelectiveQuantize<T>(dOutput + dBias, vScale, vOffset);
@@ -236,11 +236,11 @@
     bool biasEnabled = bias.size() > 0;
 
     // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches).
-    BOOST_ASSERT(inputNum == 1);
-    BOOST_ASSERT(outputNum == 1);
+    ARMNN_ASSERT(inputNum == 1);
+    ARMNN_ASSERT(outputNum == 1);
 
     // If a bias is used, its size must equal the number of output channels.
-    BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels);
+    ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels);
 
 
     // Note these tensors will use two (identical) batches.
@@ -1627,7 +1627,7 @@
 
     // If a bias is used, its size must equal the number of output channels.
     bool biasEnabled = bias.size() > 0;
-    BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels);
+    ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels);
 
     // Creates the tensors.
     armnn::TensorInfo inputTensorInfo =
@@ -2135,11 +2135,11 @@
     bool biasEnabled = bias.size() > 0;
 
     // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches).
-    BOOST_ASSERT(inputNum == 1);
-    BOOST_ASSERT(outputNum == 1);
+    ARMNN_ASSERT(inputNum == 1);
+    ARMNN_ASSERT(outputNum == 1);
 
     // If a bias is used, its size must equal the number of output channels.
-    BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels);
+    ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels);
 
 
     // Note these tensors will use two (identical) batches.