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author | Michalis Spyrou <michalis.spyrou@arm.com> | 2019-10-10 14:33:47 +0100 |
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committer | Michalis Spyrou <michalis.spyrou@arm.com> | 2019-10-16 12:04:25 +0000 |
commit | 7c60c990fbed62aab1369c0e4462c4081dc3cfeb (patch) | |
tree | 94329c7a6214b1385b15bc5225c198fd77cec5c9 /src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp | |
parent | a07ce151674e28a3e755f1c48785b599f1d34827 (diff) | |
download | ComputeLibrary-7c60c990fbed62aab1369c0e4462c4081dc3cfeb.tar.gz |
COMPMID-2486: Remove disabled compiler warnings
Removed the following flags:
-Wno-format-nonliteral: This had a side effect on
Error.h that resulted in rewriting most of the macros. Since
I was at it I removed all the va_args in order to comply
with DCL50-CPP.
-Wno-deprecated-increment-bool
-Wno-vla-extension
-Wno-mismatched-tags
-Wno-redundant-move
Change-Id: I7c593854ecc3b7d595b8edcbd6a86d3c2563c6bd
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2069
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp')
-rw-r--r-- | src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp index 7b4f7b97c4..0addb0ead3 100644 --- a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp +++ b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp @@ -46,16 +46,16 @@ Status validate_arguments(const ITensorInfo *input_box_encoding, const ITensorIn ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_box_encoding->num_dimensions() > 3, "The location input tensor shape should be [4, N, kBatchSize]."); if(input_box_encoding->num_dimensions() > 2) { - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_box_encoding->dimension(2) != kBatchSize, "The third dimension of the input box_encoding tensor should be equal to %d.", kBatchSize); + ARM_COMPUTE_RETURN_ERROR_ON_MSG_VAR(input_box_encoding->dimension(2) != kBatchSize, "The third dimension of the input box_encoding tensor should be equal to %d.", kBatchSize); } - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_box_encoding->dimension(0) != kNumCoordBox, "The first dimension of the input box_encoding tensor should be equal to %d.", kNumCoordBox); + ARM_COMPUTE_RETURN_ERROR_ON_MSG_VAR(input_box_encoding->dimension(0) != kNumCoordBox, "The first dimension of the input box_encoding tensor should be equal to %d.", kNumCoordBox); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_class_score->dimension(0) != (info.num_classes() + 1), "The first dimension of the input class_prediction should be equal to the number of classes plus one."); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_anchors->num_dimensions() > 3, "The anchors input tensor shape should be [4, N, kBatchSize]."); if(input_anchors->num_dimensions() > 2) { - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_anchors->dimension(0) != kNumCoordBox, "The first dimension of the input anchors tensor should be equal to %d.", kNumCoordBox); + ARM_COMPUTE_RETURN_ERROR_ON_MSG_VAR(input_anchors->dimension(0) != kNumCoordBox, "The first dimension of the input anchors tensor should be equal to %d.", kNumCoordBox); } ARM_COMPUTE_RETURN_ERROR_ON_MSG((input_box_encoding->dimension(1) != input_class_score->dimension(1)) || (input_box_encoding->dimension(1) != input_anchors->dimension(1)), |