From d2a8b90f35beba65128ecf24adae3ae8caab1ff9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Gr=C3=A9goire=20KUBLER?= <gregoire.kubler@proton.me>
Date: Tue, 17 Dec 2024 17:46:28 +0100
Subject: [PATCH] fix : [Conv] added check to ensure that dilation & stride
values were all >= 1
Also better warning message for conv operator constructor
---
include/aidge/operator/Conv.hpp | 13 ++++++++++---
src/operator/Conv.cpp | 15 +++++++++++++++
2 files changed, 25 insertions(+), 3 deletions(-)
diff --git a/include/aidge/operator/Conv.hpp b/include/aidge/operator/Conv.hpp
index 283d0136e..0db1e8343 100644
--- a/include/aidge/operator/Conv.hpp
+++ b/include/aidge/operator/Conv.hpp
@@ -12,6 +12,7 @@
#ifndef AIDGE_CORE_OPERATOR_CONV_H_
#define AIDGE_CORE_OPERATOR_CONV_H_
+#include <algorithm>
#include <array>
#include <cstddef> // std::size_t
#include <string>
@@ -234,10 +235,16 @@ std::shared_ptr<Node> Conv(DimSize_t inChannels,
bool noBias = false);
/**
- * @brief Helper function for Conv with C-style arrays.
+ * @brief Perform a convolution on the input Tensor.
*
- * This helper function allows automatic template deduction of the number of dimensions (DIM)
- * based on the kernel dimensions provided.
+ * @tparam DIM Number of dimensions for the feature map.
+ * @param inChannels Number of input channels.
+ * @param outChannels Number of output channels.
+ * @param kernelDims Dimensions of the kernel. Must be the same number of dimensions as the feature map.
+ * @param name Name of the operator.
+ * @param strideDims Dimensions of the stride attribute. Must be the same number of dimensions as the feature map.
+ * @param dilationDims Dimensions of the dilation attribute. Must be the same number of dimensions as the feature map.
+ * @return std::shared_ptr<Node> A Node containing the operator.
*/
template <DimSize_t DIM>
std::shared_ptr<Node> Conv(
diff --git a/src/operator/Conv.cpp b/src/operator/Conv.cpp
index 8d5f33322..3abd144f8 100644
--- a/src/operator/Conv.cpp
+++ b/src/operator/Conv.cpp
@@ -237,6 +237,21 @@ std::shared_ptr<Aidge::Node> Aidge::Conv(
const std::array<Aidge::DimSize_t, DIM> &dilationDims,
bool noBias)
{
+ AIDGE_ASSERT(DIM<=MaxDim,"{}: Too many kernel dimensions required, maximum allowed : {} ", Conv_Op<DIM>::Type, MaxDim);
+ AIDGE_ASSERT(!std::any_of(dilationDims.cbegin(),
+ dilationDims.cend(),
+ [](DimSize_t val) { return val == 0; }),
+ "Conv : at least of of the dilation dimension is 0, expecting "
+ "strictly positive values. Got {}",
+ Conv_Op<DIM>::Type,
+ dilationDims);
+ AIDGE_ASSERT(!std::any_of(strideDims.cbegin(),
+ strideDims.cend(),
+ [](DimSize_t val) { return val == 0; }),
+ "{}: at least one of the stride dimension is 0, expecting "
+ "strictly positive values. Got {}.",
+ Conv_Op<DIM>::Type,
+ strideDims);
static_assert(DIM<=MaxDim,"Too many kernel dimensions required by Conv, not supported");
return Conv(inChannels, outChannels, to_array(kernelDims), name, strideDims, dilationDims, noBias);
}
--
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