[mlir][CAPI][python] expose the python bindings for linalg::isaConvolutionOpInterface and linalg::inferConvolutionDims (#135253)

This PR is mainly about exposing the python bindings for
`linalg::isaConvolutionOpInterface` and `linalg::inferConvolutionDims`.

---------

Signed-off-by: Bangtian Liu <[email protected]>

Author: bangtianliu

DialectLinalg.cpp

@@ -28,6 +28,26 @@ InferContractionDimensions(MlirOperation op) {
   return dims;
 }
 
+static std::optional<MlirLinalgConvolutionDimensions>
+InferConvolutionDimensions(MlirOperation op) {
+  MlirLinalgConvolutionDimensions dims =
+      mlirLinalgInferConvolutionDimensions(op);
+
+  // Detect "empty" result. This occurs when `op` is not a convolution op,
+  // or when `linalg::inferConvolutionDims` fails.
+  if (mlirAttributeIsNull(dims.batch) &&
+      mlirAttributeIsNull(dims.outputImage) &&
+      mlirAttributeIsNull(dims.outputChannel) &&
+      mlirAttributeIsNull(dims.filterLoop) &&
+      mlirAttributeIsNull(dims.inputChannel) &&
+      mlirAttributeIsNull(dims.depth) && mlirAttributeIsNull(dims.strides) &&
+      mlirAttributeIsNull(dims.dilations)) {
+    return std::nullopt;
+  }
+
+  return dims;
+}
+
 static void populateDialectLinalgSubmodule(nb::module_ m) {
   m.def(
       "fill_builtin_region",
@@ -36,7 +56,7 @@ static void populateDialectLinalgSubmodule(nb::module_ m) {
       "Fill the region for `op`, which is assumed to be a builtin named Linalg "
       "op.");
 
-  m.def("isa_contraction_op", &mlirLinalgIsContractionOp,
+  m.def("isa_contraction_op", &mlirLinalgIsAContractionOp,
         "Checks if the given operation is a Linalg contraction operation.",
         nb::arg("op"));
 
@@ -59,6 +79,47 @@ static void populateDialectLinalgSubmodule(nb::module_ m) {
         "Infers contraction dimensions (batch/m/n/k) for a Linalg contraction "
         "op.",
         nb::arg("op"));
+
+  m.def("isa_convolution_op", &mlirLinalgIsAConvolutionOp,
+        "Checks if the given operation is a Linalg convolution operation.",
+        nb::arg("op"));
+
+  nb::class_<MlirLinalgConvolutionDimensions>(m, "ConvolutionDimensions")
+      .def_prop_ro("batch",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.batch;
+                   })
+      .def_prop_ro("output_image",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.outputImage;
+                   })
+      .def_prop_ro("output_channel",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.outputChannel;
+                   })
+      .def_prop_ro("filter_loop",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.filterLoop;
+                   })
+      .def_prop_ro("input_channel",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.inputChannel;
+                   })
+      .def_prop_ro("depth",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.depth;
+                   })
+      .def_prop_ro("strides",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.strides;
+                   })
+      .def_prop_ro("dilations",
+                   [](const MlirLinalgConvolutionDimensions &self) {
+                     return self.dilations;
+                   });
+
+  m.def("infer_convolution_dimensions", &InferConvolutionDimensions,
+        "Infers convolution dimensions", nb::arg("op"));
 }
 
 NB_MODULE(_mlirDialectsLinalg, m) {