[mlir][py] Add NVGPU's TensorMapDescriptorType in py bindings

mlir/include/mlir-c/Dialect/NVGPU.h

@@ -11,13 +11,24 @@
 #define MLIR_C_DIALECT_NVGPU_H
 
 #include "mlir-c/IR.h"
+#include "mlir-c/Support.h"
 
 #ifdef __cplusplus
 extern "C" {
 #endif
 
 MLIR_DECLARE_CAPI_DIALECT_REGISTRATION(NVGPU, nvgpu);
 
+//===---------------------------------------------------------------------===//
+// TensorMapDescriptorType
+//===---------------------------------------------------------------------===//
+
+MLIR_CAPI_EXPORTED bool mlirTypeIsANVGPUTensorMapDescriptorType(MlirType type);
+
+MLIR_CAPI_EXPORTED MlirType mlirNVGPUTensorMapDescriptorTypeGet(
+    MlirContext ctx, MlirType tensorMemrefType, int swizzle, int l2promo,
+    int oobFill, int interleave);
+
 #ifdef __cplusplus
 }
 #endif

mlir/lib/Bindings/Python/DialectNVGPU.cpp

@@ -0,0 +1,41 @@
+//===--- DialectNvgpu.cpp - Pybind module for Nvgpu dialect API support ---===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir-c/Dialect/NVGPU.h"
+#include "mlir-c/IR.h"
+#include "mlir/Bindings/Python/PybindAdaptors.h"
+#include <pybind11/pybind11.h>
+
+namespace py = pybind11;
+using namespace llvm;
+using namespace mlir;
+using namespace mlir::python;
+using namespace mlir::python::adaptors;
+
+static void populateDialectNvgpuSubmodule(const pybind11::module &m) {
+  auto nvgpuTensorMapDescriptorType = mlir_type_subclass(
+      m, "TensorMapDescriptorType", mlirTypeIsANVGPUTensorMapDescriptorType);
+
+  nvgpuTensorMapDescriptorType.def_classmethod(
+      "get",
+      [](py::object cls, MlirType tensorMemrefType, int swizzle, int l2promo,
+         int oobFill, int interleave, MlirContext ctx) {
+        return cls(mlirNVGPUTensorMapDescriptorTypeGet(
+            ctx, tensorMemrefType, swizzle, l2promo, oobFill, interleave));
+      },
+      "Gets an instance of TensorMapDescriptorType in the same context",
+      py::arg("cls"), py::arg("tensor_type"), py::arg("swizzle"),
+      py::arg("l2promo"), py::arg("oob_fill"), py::arg("interleave"),
+      py::arg("ctx") = py::none());
+}
+
+PYBIND11_MODULE(_mlirDialectsNvgpu, m) {
+  m.doc() = "MLIR NVGPU dialect.";
+
+  populateDialectNvgpuSubmodule(m);
+}

mlir/lib/CAPI/Dialect/NVGPU.cpp

@@ -9,5 +9,23 @@
 #include "mlir-c/Dialect/NVGPU.h"
 #include "mlir/CAPI/Registration.h"
 #include "mlir/Dialect/NVGPU/IR/NVGPUDialect.h"
+#include "mlir/IR/BuiltinTypes.h"
+
+using namespace mlir;
+using namespace mlir::nvgpu;
 
 MLIR_DEFINE_CAPI_DIALECT_REGISTRATION(NVGPU, nvgpu, mlir::nvgpu::NVGPUDialect)
+
+bool mlirTypeIsANVGPUTensorMapDescriptorType(MlirType type) {
+  return isa<nvgpu::TensorMapDescriptorType>(unwrap(type));
+}
+
+MlirType mlirNVGPUTensorMapDescriptorTypeGet(MlirContext ctx,
+                                             MlirType tensorMemrefType,
+                                             int swizzle, int l2promo,
+                                             int oobFill, int interleave) {
+  return wrap(nvgpu::TensorMapDescriptorType::get(
+      unwrap(ctx), cast<MemRefType>(unwrap(tensorMemrefType)),
+      TensorMapSwizzleKind(swizzle), TensorMapL2PromoKind(l2promo),
+      TensorMapOOBKind(oobFill), TensorMapInterleaveKind(interleave)));
+}

mlir/python/CMakeLists.txt

@@ -524,6 +524,19 @@ declare_mlir_python_extension(MLIRPythonExtension.Dialects.Quant.Pybind
     MLIRCAPIQuant
 )
 
+declare_mlir_python_extension(MLIRPythonExtension.Dialects.NVGPU.Pybind
+  MODULE_NAME _mlirDialectsNvgpu
+  ADD_TO_PARENT MLIRPythonSources.Dialects.nvgpu
+  ROOT_DIR "${PYTHON_SOURCE_DIR}"
+  SOURCES
+    DialectNVGPU.cpp
+  PRIVATE_LINK_LIBS
+    LLVMSupport
+  EMBED_CAPI_LINK_LIBS
+    MLIRCAPIIR
+    MLIRCAPINVGPU
+)
+
 declare_mlir_python_extension(MLIRPythonExtension.Dialects.PDL.Pybind
   MODULE_NAME _mlirDialectsPDL
   ADD_TO_PARENT MLIRPythonSources.Dialects.pdl

mlir/python/mlir/dialects/nvgpu.py

@@ -4,3 +4,4 @@
 
 from ._nvgpu_ops_gen import *
 from ._nvgpu_enum_gen import *
+from .._mlir_libs._mlirDialectsNvgpu import *

mlir/test/python/dialects/nvgpu.py

@@ -15,6 +15,23 @@ def constructAndPrintInModule(f):
     return f
 
 
+# CHECK-LABEL: testTypes
+@constructAndPrintInModule
+def testTypes():
+    tensorMemrefType = MemRefType.get(
+        (128, 64), F16Type.get(), memory_space=Attribute.parse("3")
+    )
+    # CHECK: !nvgpu.tensormap.descriptor<tensor = memref<128x64xf16, 3>, swizzle = swizzle_128b, l2promo = l2promo_256b, oob = nan, interleave = none>
+    tma_desc = nvgpu.TensorMapDescriptorType.get(
+        tensorMemrefType,
+        nvgpu.TensorMapSwizzleKind.SWIZZLE_128B,
+        nvgpu.TensorMapL2PromoKind.L2PROMO_256B,
+        nvgpu.TensorMapOOBKind.OOB_NAN,
+        nvgpu.TensorMapInterleaveKind.INTERLEAVE_NONE,
+    )
+    print(tma_desc)
+
+
 # CHECK-LABEL: testSmoke
 @constructAndPrintInModule
 def testSmoke():