Revert "[mlir][py] better support for arith.constant construction"

[joker-eph]

Reverts #83259

This broke an integration test on Windows

[llvmbot]

@llvm/pr-subscribers-mlir

Author: Mehdi Amini (joker-eph)

Changes

Reverts llvm/llvm-project#83259

This broke an integration test on Windows

---

Full diff: https://github.com/llvm/llvm-project/pull/84103.diff

2 Files Affected:

• (modified) mlir/python/mlir/dialects/arith.py (+2-21)
• (modified) mlir/test/python/dialects/arith_dialect.py (-38)

diff --git a/mlir/python/mlir/dialects/arith.py b/mlir/python/mlir/dialects/arith.py
index 83a50c7ef244f1..61c6917393f1f9 100644
--- a/mlir/python/mlir/dialects/arith.py
+++ b/mlir/python/mlir/dialects/arith.py
@@ -5,8 +5,6 @@
 from ._arith_ops_gen import *
 from ._arith_ops_gen import _Dialect
 from ._arith_enum_gen import *
-from array import array as _array
-from typing import overload
 
 try:
     from ..ir import *
@@ -45,30 +43,13 @@ def _is_float_type(type: Type):
 class ConstantOp(ConstantOp):
     """Specialization for the constant op class."""
 
-    @overload
-    def __init__(self, value: Attribute, *, loc=None, ip=None):
-        ...
-
-    @overload
     def __init__(
-        self, result: Type, value: Union[int, float, _array], *, loc=None, ip=None
+        self, result: Type, value: Union[int, float, Attribute], *, loc=None, ip=None
     ):
-        ...
-
-    def __init__(self, result, value, *, loc=None, ip=None):
-        if value is None:
-            assert isinstance(result, Attribute)
-            super().__init__(result, loc=loc, ip=ip)
-            return
-
         if isinstance(value, int):
             super().__init__(IntegerAttr.get(result, value), loc=loc, ip=ip)
         elif isinstance(value, float):
             super().__init__(FloatAttr.get(result, value), loc=loc, ip=ip)
-        elif isinstance(value, _array) and value.typecode in ["i", "l"]:
-            super().__init__(DenseIntElementsAttr.get(value, type=result))
-        elif isinstance(value, _array) and value.typecode in ["f", "d"]:
-            super().__init__(DenseFPElementsAttr.get(value, type=result))
         else:
             super().__init__(value, loc=loc, ip=ip)
 
@@ -98,6 +79,6 @@ def literal_value(self) -> Union[int, float]:
 
 
 def constant(
-    result: Type, value: Union[int, float, Attribute, _array], *, loc=None, ip=None
+    result: Type, value: Union[int, float, Attribute], *, loc=None, ip=None
 ) -> Value:
     return _get_op_result_or_op_results(ConstantOp(result, value, loc=loc, ip=ip))
diff --git a/mlir/test/python/dialects/arith_dialect.py b/mlir/test/python/dialects/arith_dialect.py
index ef0e1620bba990..8bb80eed2b8105 100644
--- a/mlir/test/python/dialects/arith_dialect.py
+++ b/mlir/test/python/dialects/arith_dialect.py
@@ -4,7 +4,6 @@
 from mlir.ir import *
 import mlir.dialects.arith as arith
 import mlir.dialects.func as func
-from array import array
 
 
 def run(f):
@@ -93,40 +92,3 @@ def __str__(self):
             b = a * a
             # CHECK: ArithValue(%2 = arith.mulf %cst_1, %cst_1 : f64)
             print(b)
-
-
-# CHECK-LABEL: TEST: testArrayConstantConstruction
-@run
-def testArrayConstantConstruction():
-    with Context(), Location.unknown():
-        module = Module.create()
-        with InsertionPoint(module.body):
-            i32_array = array("i", [1, 2, 3, 4])
-            i32 = IntegerType.get_signless(32)
-            vec_i32 = VectorType.get([2, 2], i32)
-            arith.constant(vec_i32, i32_array)
-            arith.ConstantOp(vec_i32, DenseIntElementsAttr.get(i32_array, type=vec_i32))
-
-            i64_array = array("l", [5, 6, 7, 8])
-            i64 = IntegerType.get_signless(64)
-            vec_i64 = VectorType.get([1, 4], i64)
-            arith.constant(vec_i64, i64_array)
-            arith.ConstantOp(vec_i64, DenseIntElementsAttr.get(i64_array, type=vec_i64))
-
-            f32_array = array("f", [1.0, 2.0, 3.0, 4.0])
-            f32 = F32Type.get()
-            vec_f32 = VectorType.get([4, 1], f32)
-            arith.constant(vec_f32, f32_array)
-            arith.ConstantOp(vec_f32, DenseFPElementsAttr.get(f32_array, type=vec_f32))
-
-            f64_array = array("d", [1.0, 2.0, 3.0, 4.0])
-            f64 = F64Type.get()
-            vec_f64 = VectorType.get([2, 1, 2], f64)
-            arith.constant(vec_f64, f64_array)
-            arith.ConstantOp(vec_f64, DenseFPElementsAttr.get(f64_array, type=vec_f64))
-
-        # CHECK-COUNT-2: arith.constant dense<[{{\[}}1, 2], [3, 4]]> : vector<2x2xi32>
-        # CHECK-COUNT-2: arith.constant dense<[{{\[}}5, 6, 7, 8]]> : vector<1x4xi64>
-        # CHECK-COUNT-2: arith.constant dense<[{{\[}}1.000000e+00], [2.000000e+00], [3.000000e+00], [4.000000e+00]]> : vector<4x1xf32>
-        # CHECK-COUNT-2: arith.constant dense<[{{\[}}[1.000000e+00, 2.000000e+00]], [{{\[}}3.000000e+00, 4.000000e+00]]]> : vector<2x1x2xf64>
-        print(module)