Merge branch 'dev' into test_env

src/operator/GlobalAveragePooling.cpp

@@ -44,8 +44,10 @@ bool Aidge::GlobalAveragePooling_Op::forwardDims(bool /*allowDataDependency*/) {
         // Global average pooling takes each filter, averages its values and uses
         // it as an output(Much like a fancier flatten). 1st dim is batch 2nd is
         // number of filter
-        mOutputs[0]->resize({getInput(0)->dims().at(0),
-                             getInput(0)->dims().at(1)});
+        std::vector<DimSize_t> outputDims(getInput(0)->nbDims(), 1);
+        outputDims[0] = getInput(0)->dims()[0];
+        outputDims[1] = getInput(0)->dims()[1];
+        mOutputs[0]->resize(outputDims);
         return true;
     }
 

unit_tests/operator/Test_GlobalAveragePooling_Op.cpp

@@ -70,12 +70,14 @@ TEST_CASE("[core/operator] GlobalAveragePooling_Op(forwardDims)",
           for (uint16_t i = 0; i < nb_dims; ++i) {
             dims[i] = dimsDist(gen) + 1;
           }
-          std::vector<DimSize_t> dims_out{dims[0], dims[1]};
+          std::vector<DimSize_t> dims_out(nb_dims, 1);
+          dims_out[0] = dims[0];
+          dims_out[1] = dims[1];
           input_T->resize(dims);
           op->setInput(0, input_T);
           REQUIRE_NOTHROW(op->forwardDims());
           REQUIRE(op->getOutput(0)->dims() == dims_out);
-          REQUIRE((op->getOutput(0)->dims().size()) == static_cast<size_t>(2));
+          REQUIRE((op->getOutput(0)->dims().size()) == nb_dims);
         }
       }
     }