Add python side Numpy dialect wrapper.

python/npcomp/dialect/Numpy.py

@@ -0,0 +1,51 @@
+#  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
+
+from npcomp.native.mlir.ir import *
+
+__all__ = [
+  "load_builtin_module",
+]
+
+
+def load_builtin_module(context = None):
+  """Loads a module populated with numpy built-ins.
+
+  This is not a long-term solution but overcomes some bootstrapping
+  issues.
+
+    >>> m = load_builtin_module()
+    >>> op = m.region(0).blocks.front.operations.front
+    >>> print(op.name)
+    numpy.generic_ufunc
+
+  Args:
+    context: The MLIRContext to use (None to create a new one).
+  Returns:
+    A ModuleOp.
+  """
+  if context is None: context = MLIRContext()
+  return context.parse_asm(_BUILTIN_MODULE_ASM)
+
+
+_BUILTIN_MODULE_ASM = r"""
+  numpy.generic_ufunc @numpy.add (
+    // CHECK-SAME: overload(%arg0: i32, %arg1: i32) -> i32 {
+    overload(%arg0: i32, %arg1: i32) -> i32 {
+      // CHECK: addi
+      %0 = addi %arg0, %arg1 : i32
+      numpy.ufunc_return %0 : i32
+    },
+    // CHECK: overload(%arg0: f32, %arg1: f32) -> f32 {
+    overload(%arg0: f32, %arg1: f32) -> f32 {
+      // CHECK: addf
+      %0 = addf %arg0, %arg1 : f32
+      numpy.ufunc_return %0 : f32
+    }
+  )
+"""
+
+if __name__ == "__main__":
+  import doctest
+  doctest.testmod()

python/npcomp/mlir_ir.cpp

@@ -28,6 +28,9 @@ static OwningModuleRef parseMLIRModuleFromString(StringRef contents,
 
 //===----------------------------------------------------------------------===//
 // Internal only template definitions
+// Since it is only legal to use explicit instantiations of templates in
+// mlir_ir.h, implementations are kept in this module to keep things scoped
+// well for the compiler.
 //===----------------------------------------------------------------------===//
 
 template <typename ListTy, typename ItemWrapperTy>
@@ -45,6 +48,9 @@ void PyIpListWrapper<ListTy, ItemWrapperTy>::bind(py::module m,
   };
 
   py::class_<ThisTy>(m, className)
+      .def_property_readonly(
+          "front",
+          [](ThisTy &self) { return ItemWrapperTy(self.list.front()); })
       .def("__len__", [](ThisTy &self) { return self.list.size(); })
       .def("__iter__",
            [](ThisTy &self) {

python/run_tests.py

@@ -7,6 +7,7 @@ import sys
 
 TEST_MODULES = (
   "npcomp.mlir_ir_test",
+  "npcomp.dialect.Numpy",
   "npcomp.edsc_test",
   "npcomp.tracing.context",
   "npcomp.tracing.mlir_trace",