Fix array attribute in bindings for linalg.init_tensor

[ftynse]

Could we add a test to mlir/test/python/dialects/linalg/ops.py? Something along the lines of "op = linalg.InitTensorOp(...); print(op.static_sizes)" + "CHECK:" line?

mlir/python/mlir/dialects/_linalg_ops_ext.py

if sizes and isinstance(sizes[0], Value):
       operands.extend(sizes)
       static_size_ints = [-1] * len(sizes)
       result_type = RankedTensorType.get(static_size_ints, element_type)
     else:
       # Static sizes.
       result_type = RankedTensorType.get(sizes, element_type)
       static_size_ints = sizes
 
-    index_type = IndexType.get(context)
+    i64_type = IntegerType.get_signless(64)
     attributes["static_sizes"] = ArrayAttr.get(
-        [IntegerAttr.get(index_type, s) for s in static_size_ints],
+        [IntegerAttr.get(i64_type, s) for s in static_size_ints],
         context=context)
     op = self.build_generic(results=[result_type],
                             operands=operands,
                             attributes=attributes,
                             loc=loc,
                             ip=ip)
     OpView.__init__(self, op)
 

mlir/test/python/dialects/linalg/ops.py

with InsertionPoint(module.body):
       # CHECK-LABEL: func @zero_d
       # CHECK: %0 = linalg.init_tensor [] : tensor<f32>
       @builtin.FuncOp.from_py_func()
       def zero_d():
         return linalg.InitTensorOp([], f32)
 
   print(module)
 
+# CHECK-LABEL: TEST: testInitTensorStaticSizesAttribute
+@run
+def testInitTensorStaticSizesAttribute():
+  with Context() as ctx, Location.unknown():
+    module = Module.create()
+    f32 = F32Type.get()
+    with InsertionPoint(module.body):
+      op = linalg.InitTensorOp([3, 4], f32)
+      # CHECK: [3, 4]
+      print(op.attributes['static_sizes'])
+
 # CHECK-LABEL: TEST: testFill
 @run
 def testFill():
   with Context() as ctx, Location.unknown():
     module = Module.create()
     f32 = F32Type.get()
     with InsertionPoint(module.body):
       # CHECK-LABEL: func @fill_tensor
with InsertionPoint(module.body):
                                    RankedTensorType.get((16, 8), f32))
       def named_form(lhs, rhs):
         init_result = linalg.InitTensorOp([4, 8], f32)
         #      CHECK: "linalg.matmul"(%{{.*}})
         # CHECK-NEXT:  ^bb0(%{{.*}}: f32, %{{.*}}: f32, %{{.*}}: f32):
         # CHECK-NEXT:    std.mulf{{.*}} (f32, f32) -> f32
         # CHECK-NEXT:    std.addf{{.*}} (f32, f32) -> f32
         # CHECK-NEXT:    linalg.yield{{.*}} (f32) -> ()
-        # CHECK-NEXT:    {linalg.memoized_indexing_maps{{.*}}operand_segment_sizes = dense<[2, 1]> : vector<2xi32>} : 
+        # CHECK-NEXT:    {linalg.memoized_indexing_maps{{.*}}operand_segment_sizes = dense<[2, 1]> : vector<2xi32>} :
         # CHECK-SAME: (tensor<4x16xf32>, tensor<16x8xf32>, tensor<4x8xf32>) -> tensor<4x8xf32>
         return linalg.matmul(lhs, rhs, outs=[init_result.result])
 
   module.operation.print(print_generic_op_form=True)
 
 # CHECK-LABEL: TEST: testNamedStructuredAsGenericOp
 @run
 def testNamedStructuredAsGenericOp():