diff --git a/include/aidge/data/Tensor.hpp b/include/aidge/data/Tensor.hpp
index 108f1f2b4af12b3501dbb247d17052e42ebb70ed..b4c5de2ebe5c18e91da8fe4474ea74cf338b0fa6 100644
--- a/include/aidge/data/Tensor.hpp
+++ b/include/aidge/data/Tensor.hpp
@@ -639,6 +639,7 @@ public:
      * the remaining coordinates are assumed to be 0.
      * Beware: the contiguous index will only correspond to the storage index
      * if the tensor is contiguous!
+     * Note that the coordIdx may be an empty vector.
      *
      * @param coordIdx Coordinate to an element in the tensor
      * @return DimSize_t Contiguous index
@@ -646,12 +647,13 @@ public:
     std::size_t getIdx(const std::vector<std::size_t>& coordIdx) const {
         AIDGE_ASSERT(coordIdx.size() <= mDims.size(), "Coordinates does not match number of dimensions");
         std::size_t flatIdx = 0;
-        std::size_t i = 0;
-        for(; i < coordIdx.size() - 1; ++i) {
-            AIDGE_ASSERT(coordIdx[i] < mDims[i], "Coordinates dimensions does not fit the dimensions of the tensor");
-            flatIdx = (flatIdx + coordIdx[i]) * mDims[i + 1];
+        for(std::size_t i = 0; i < mDims.size(); ++i) {
+            auto coord = i < coordIdx.size() ? coordIdx[i]: 0;
+            AIDGE_ASSERT(coord < mDims[i], "Coordinates dimensions does not fit the dimensions of the tensor");
+            auto nextDimSize  = i + 1 < mDims.size() ? mDims[i + 1]: 1;
+            flatIdx = (flatIdx + coord) * nextDimSize;
         }
-        return flatIdx + coordIdx[i];
+        return flatIdx;
     }
 
     /**
@@ -663,10 +665,10 @@ public:
      * @return DimSize_t Storage index
      */
     std::size_t getStorageIdx(const std::vector<std::size_t>& coordIdx) const {
+        AIDGE_ASSERT(coordIdx.size() <= mDims.size(), "Coordinates does not match number of dimensions");
         for(std::size_t i = 0; i < coordIdx.size(); ++i) {
             AIDGE_ASSERT(coordIdx[i] < mDims[i], "Coordinates dimensions does not fit the dimensions of the tensor");
         }
-        AIDGE_ASSERT(coordIdx.size() <= mDims.size(), "Coordinates does not match number of dimensions");
         return std::inner_product(coordIdx.cbegin(), coordIdx.cend(), mStrides.cbegin(), DimSize_t(0));
     }
 
diff --git a/unit_tests/data/Test_Tensor.cpp b/unit_tests/data/Test_Tensor.cpp
index a536f113f7d11eb8cec81b5fdbf57909bd70611d..d5cd8cdcfb88beee9aab2393b0c5591c79a70b80 100644
--- a/unit_tests/data/Test_Tensor.cpp
+++ b/unit_tests/data/Test_Tensor.cpp
@@ -298,6 +298,73 @@ TEST_CASE("[core/data] Tensor(other)", "[Tensor][extract][zeros][print]") {
         }
     }
 
+    SECTION("Tensor set/get") {
+        // Test set with idx and get with idx and coords on different tensors ranks (including 0-rank)
+        // with different coords ranks (including 0-rank).
+        for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
+            // Test tensors of rank 0 to 3
+            for (std::size_t nb_dims = 0; nb_dims <= 3; ++nb_dims) {
+                std::vector<std::size_t> dims(nb_dims);
+                for (std::size_t dim = 0; dim < nb_dims; ++dim) {
+                    dims[dim] = dimsDist(gen);
+                }
+
+                size_t size = std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>());
+                std::vector<float> values(size);
+                for (auto& valref : values) {
+                    valref = valueDist(gen);
+                }
+
+                std::unique_ptr<float[]> x_array(new float[size]);
+                for (std::size_t i = 0; i < size; ++i) {
+                    x_array[i] = values[i];
+                }
+
+                // Initialize Tensor with a host backend
+                Tensor x{dims};
+                x.setDataType(DataType::Float32);
+                x.setBackend("cpu");
+                x.getImpl()->setRawPtr(x_array.get(), x.size());
+                REQUIRE(x.getImpl()->hostPtr() != nullptr);
+                REQUIRE(x.isContiguous());
+
+                // Test get() and set() values by index
+                for (std::size_t i = 0; i < size; ++i) {
+                    REQUIRE_NOTHROW(x.set(i, values[i]));
+                }
+                for (std::size_t i = 0; i < size; ++i) {
+                    float val;
+                    REQUIRE_NOTHROW(val = x.get<float>(i));
+                    REQUIRE(val == values[i]);
+                }
+
+                // Test get() and set() by coords
+                // We create coords of rank 0 to the number of dimensions
+                for (std::size_t coord_size = 0; coord_size < dims.size(); ++coord_size) {
+                    std::vector<std::size_t> coords(coord_size);
+                    for (std::size_t coord_idx = 0; coord_idx < coord_size; ++coord_idx) {
+                        std::size_t dim_idx = (dimsDist(gen)-1) % dims[coord_idx];
+                        coords[coord_idx] = dim_idx;
+                    }
+                    std::size_t flat_idx, flat_storage_idx;
+                    // As it is continuous we have getIdx() == getStorageIdx()
+                    REQUIRE_NOTHROW(flat_idx = x.getIdx(coords));
+                    REQUIRE_NOTHROW(flat_storage_idx = x.getStorageIdx(coords));
+                    REQUIRE(flat_storage_idx == flat_idx);
+                    float val, val_flat;
+                    // Test get() by index and by coords
+                    REQUIRE_NOTHROW(val_flat = x.get<float>(flat_idx));
+                    REQUIRE_NOTHROW(val = x.get<float>(coords));
+                    REQUIRE(val == val_flat);
+                    REQUIRE(val == values[flat_idx]);
+                    // Test set() by coords, also update the reference array
+                    REQUIRE_NOTHROW(x.set(coords, val + 1));
+                    values[flat_idx] += 1;
+                }
+            }
+        }
+    }
+
     SECTION("Tensor extract") {
         bool equal;