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Reapply "[mlir][python] allow DenseIntElementsAttr for index type (#118947)" #124804
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…vm#118947)" This reverts commit 1b729c3 and adapts to nanobind.
@llvm/pr-subscribers-mlir Author: Matthias Gehre (mgehre-amd) ChangesThis reapplies #118947 and adapts to nanobind. Full diff: https://github.com/llvm/llvm-project/pull/124804.diff 6 Files Affected:
diff --git a/mlir/include/mlir-c/BuiltinAttributes.h b/mlir/include/mlir-c/BuiltinAttributes.h
index 7c8c84e55b962f..1d0edf9ea809d2 100644
--- a/mlir/include/mlir-c/BuiltinAttributes.h
+++ b/mlir/include/mlir-c/BuiltinAttributes.h
@@ -556,6 +556,8 @@ MLIR_CAPI_EXPORTED int64_t
mlirDenseElementsAttrGetInt64Value(MlirAttribute attr, intptr_t pos);
MLIR_CAPI_EXPORTED uint64_t
mlirDenseElementsAttrGetUInt64Value(MlirAttribute attr, intptr_t pos);
+MLIR_CAPI_EXPORTED uint64_t
+mlirDenseElementsAttrGetIndexValue(MlirAttribute attr, intptr_t pos);
MLIR_CAPI_EXPORTED float mlirDenseElementsAttrGetFloatValue(MlirAttribute attr,
intptr_t pos);
MLIR_CAPI_EXPORTED double
diff --git a/mlir/lib/Bindings/Python/IRAttributes.cpp b/mlir/lib/Bindings/Python/IRAttributes.cpp
index 7bc21a31c3c84c..d3ceb3d435c1c0 100644
--- a/mlir/lib/Bindings/Python/IRAttributes.cpp
+++ b/mlir/lib/Bindings/Python/IRAttributes.cpp
@@ -1372,13 +1372,19 @@ class PyDenseIntElementsAttribute
MlirType type = mlirAttributeGetType(*this);
type = mlirShapedTypeGetElementType(type);
- assert(mlirTypeIsAInteger(type) &&
- "expected integer element type in dense int elements attribute");
+ // Index type can also appear as a DenseIntElementsAttr and therefore can be
+ // casted to integer.
+ assert(mlirTypeIsAInteger(type) ||
+ mlirTypeIsAIndex(type) && "expected integer/index element type in "
+ "dense int elements attribute");
// Dispatch element extraction to an appropriate C function based on the
// elemental type of the attribute. nb::int_ is implicitly constructible
// from any C++ integral type and handles bitwidth correctly.
// TODO: consider caching the type properties in the constructor to avoid
// querying them on each element access.
+ if (mlirTypeIsAIndex(type)) {
+ return nb::int_(mlirDenseElementsAttrGetIndexValue(*this, pos));
+ }
unsigned width = mlirIntegerTypeGetWidth(type);
bool isUnsigned = mlirIntegerTypeIsUnsigned(type);
if (isUnsigned) {
diff --git a/mlir/lib/CAPI/IR/BuiltinAttributes.cpp b/mlir/lib/CAPI/IR/BuiltinAttributes.cpp
index 11d1ade552f5a2..8d57ab6b59e79c 100644
--- a/mlir/lib/CAPI/IR/BuiltinAttributes.cpp
+++ b/mlir/lib/CAPI/IR/BuiltinAttributes.cpp
@@ -758,6 +758,9 @@ int64_t mlirDenseElementsAttrGetInt64Value(MlirAttribute attr, intptr_t pos) {
uint64_t mlirDenseElementsAttrGetUInt64Value(MlirAttribute attr, intptr_t pos) {
return llvm::cast<DenseElementsAttr>(unwrap(attr)).getValues<uint64_t>()[pos];
}
+uint64_t mlirDenseElementsAttrGetIndexValue(MlirAttribute attr, intptr_t pos) {
+ return llvm::cast<DenseElementsAttr>(unwrap(attr)).getValues<uint64_t>()[pos];
+}
float mlirDenseElementsAttrGetFloatValue(MlirAttribute attr, intptr_t pos) {
return llvm::cast<DenseElementsAttr>(unwrap(attr)).getValues<float>()[pos];
}
diff --git a/mlir/test/python/dialects/builtin.py b/mlir/test/python/dialects/builtin.py
index 18ebba61e7fea8..973a0eaeca2cdb 100644
--- a/mlir/test/python/dialects/builtin.py
+++ b/mlir/test/python/dialects/builtin.py
@@ -246,3 +246,7 @@ def testDenseElementsAttr():
# CHECK{LITERAL}: dense<[[0, 1], [2, 3]]> : tensor<2x2xi32>
print(DenseElementsAttr.get(values, type=VectorType.get((2, 2), i32)))
# CHECK{LITERAL}: dense<[[0, 1], [2, 3]]> : vector<2x2xi32>
+ idx_values = np.arange(4, dtype=np.int64)
+ idx_type = IndexType.get()
+ print(DenseElementsAttr.get(idx_values, type=VectorType.get([4], idx_type)))
+ # CHECK{LITERAL}: dense<[0, 1, 2, 3]> : vector<4xindex>
diff --git a/mlir/test/python/ir/array_attributes.py b/mlir/test/python/ir/array_attributes.py
index 256a69a939658d..ef1d835fc64012 100644
--- a/mlir/test/python/ir/array_attributes.py
+++ b/mlir/test/python/ir/array_attributes.py
@@ -572,6 +572,10 @@ def testGetDenseElementsIndex():
print(arr)
# CHECK: True
print(arr.dtype == np.int64)
+ array = np.array([1, 2, 3], dtype=np.int64)
+ attr = DenseIntElementsAttr.get(array, type=VectorType.get([3], idx_type))
+ # CHECK: [1, 2, 3]
+ print(list(DenseIntElementsAttr(attr)))
# CHECK-LABEL: TEST: testGetDenseResourceElementsAttr
diff --git a/mlir/test/python/ir/attributes.py b/mlir/test/python/ir/attributes.py
index 00c3e1b4decdb7..2f3c4460d3f590 100644
--- a/mlir/test/python/ir/attributes.py
+++ b/mlir/test/python/ir/attributes.py
@@ -366,6 +366,10 @@ def testDenseIntAttr():
# CHECK: i1
print(ShapedType(a.type).element_type)
+ shape = Attribute.parse("dense<[0, 1, 2, 3]> : vector<4xindex>")
+ # CHECK: attr: dense<[0, 1, 2, 3]>
+ print("attr:", shape)
+
@run
def testDenseArrayGetItem():
|
makslevental
approved these changes
Jan 29, 2025
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LGTM
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This reapplies #118947 and adapts to nanobind.