fix failed onnx tests

Context

This MR is intended to fix the failed onnx tests encountered in issue aidge_onnx#50 and issue aidge_onnx#46.

This includes the following problems:

• Flatten: missing python binding.
• And/Equal: A mistake was made, the operator Equal was named And.
• AvgPooling: unsupported attrs dilations and ceil_mode
• MaxPooling: unsupported attr dilations

Detailed major modifications

The following modifications were made:

• Add python binding for flatten
• Add Equal operator
• Add dilations attr to Maxpooling
• Add dilations and ceil_mode to AvgPooling

TODO

This MR would only fix the following:

• Add Flatten binding
• Add Equal Op
• AvgPooling: add dilations and ceil_mode attrs
• MaxPooling: add dilationsattr

include/aidge/operator/MetaOperatorDefs.hpp

@@ -173,7 +173,8 @@ extern std::shared_ptr<Node> PaddedAvgPooling(const std::array<DimSize_t, DIM> &
                                   const std::string& name = "",
                                   const std::array<DimSize_t, DIM> &stride_dims = create_array<DimSize_t,DIM>(1),
                                   const std::array<DimSize_t, DIM> &dilations = create_array<DimSize_t,DIM>(1),
-                                  const std::array<DimSize_t, 2*DIM> &padding_dims = create_array<DimSize_t,2*DIM>(0));
+                                  const std::array<DimSize_t, 2*DIM> &padding_dims = create_array<DimSize_t,2*DIM>(0),
+                                  bool ceil_mode = false);
 
 /**
  * @brief Creates a padded average pooling operation as a MetaOperator.
@@ -190,7 +191,8 @@ template <std::array<DimSize_t, 1>::size_type DIM>
 extern std::shared_ptr<MetaOperator_Op> PaddedAvgPooling_Op(const std::array<DimSize_t, DIM> &kernel_dims,
                                   const std::array<DimSize_t, DIM> &stride_dims = create_array<DimSize_t,DIM>(1),
                                   const std::array<DimSize_t, DIM> &dilations = create_array<DimSize_t,DIM>(1),
-                                  const std::array<DimSize_t, 2*DIM> &padding_dims = create_array<DimSize_t,2*DIM>(0));
+                                  const std::array<DimSize_t, 2*DIM> &padding_dims = create_array<DimSize_t,2*DIM>(0),
+                                  bool ceil_mode = false);
 
 // Helper function for average pooling with C-style array for kernel_dims, enabling automatic DIM deduction.
 template <DimSize_t DIM>
@@ -202,7 +204,8 @@ PaddedAvgPooling(DimSize_t const (&kernel_dims)[DIM],
                  const std::array<DimSize_t, DIM> &dilations =
                      create_array<DimSize_t, DIM>(1),
                  const std::array<DimSize_t, 2 * DIM> &padding_dims =
-                     create_array<DimSize_t, 2 * DIM>(0));
+                     create_array<DimSize_t, 2 * DIM>(0),
+                bool ceil_mode = false);
 
 ////////////////////////////////////////////////////////////////////////////////
 
@@ -268,7 +271,7 @@ inline std::shared_ptr<Node> PaddedMaxPooling(
     const std::array<DimSize_t, DIM> &dilations = create_array<DimSize_t,DIM>(1),
     const std::array<DimSize_t, 2*DIM> &padding_dims = create_array<DimSize_t,2*DIM>(0),
     bool ceil_mode= false) {
-    return PaddedMaxPooling(to_array(kernel_dims), name, stride_dims, padding_dims, dilations, ceil_mode);
+    return PaddedMaxPooling(to_array(kernel_dims), name, stride_dims, dilations, padding_dims, ceil_mode);
 }
 
 /**