[Mlir-commits] [mlir] [mlir][python] Support Arbitrary Precision Integers in MLIR C API and Python Bindings (PR #177733)

[Maksim Levental]

================
@@ -343,8 +343,50 @@ void PyFloatAttribute::bindDerived(ClassTy &c) {
 void PyIntegerAttribute::bindDerived(ClassTy &c) {
   c.def_static(
       "get",
-      [](PyType &type, int64_t value) {
-        MlirAttribute attr = mlirIntegerAttrGet(type, value);
+      [](PyType &type, nb::object value) {
+        // Handle IndexType - it doesn't have a bit width or signedness.
+        if (mlirTypeIsAIndex(type)) {
+          int64_t intValue = nb::cast<int64_t>(value);
+          MlirAttribute attr = mlirIntegerAttrGet(type, intValue);
+          return PyIntegerAttribute(type.getContext(), attr);
+        }
+
+        // Get the bit width of the integer type.
+        unsigned bitWidth = mlirIntegerTypeGetWidth(type);
+
+        // Try to use the fast path for small integers.
+        if (bitWidth <= 64) {
+          int64_t intValue = nb::cast<int64_t>(value);
+          MlirAttribute attr = mlirIntegerAttrGet(type, intValue);
+          return PyIntegerAttribute(type.getContext(), attr);
+        }
+
+        // For larger integers, convert Python int to array of 64-bit words.
+        unsigned numWords = (bitWidth + 63) / 64;
+        std::vector<uint64_t> words(numWords, 0);
+
+        // Extract words from Python integer (little-endian order).
+        nb::object mask = nb::int_(0xFFFFFFFFFFFFFFFFULL);
+        nb::object shift = nb::int_(64);
+        nb::object current = value;
+
+        // Handle negative numbers for signed types by converting to two's
+        // complement representation.
+        if (mlirIntegerTypeIsSigned(type)) {
+          nb::object zero = nb::int_(0);
+          if (nb::cast<bool>(current < zero)) {
+            nb::object twoToTheBitWidth = nb::int_(1) << nb::int_(bitWidth);
+            current = current + twoToTheBitWidth;
----------------
makslevental wrote:

sorry i'm not familiar with this - why do you need to do this?

https://github.com/llvm/llvm-project/pull/177733