STY: Small changes to the `PyUFunc_ReduceWrapper`

These changes are simply designed to lower the churn of the larger
PR that has to follow eventually.

1 files changed, 16 insertions, 30 deletions

diff --git a/numpy/core/src/umath/reduction.c b/numpy/core/src/umath/reduction.c
index f1423d8b9..86cc20eb1 100644
--- a/numpy/core/src/umath/reduction.c
+++ b/numpy/core/src/umath/reduction.c
@@ -166,7 +166,7 @@ PyArray_CopyInitialReduceValues(
  * identity    : If Py_None, PyArray_CopyInitialReduceValues is used, otherwise
  *               this value is used to initialize the result to
  *               the reduction's unit.
- * loop        : The loop which does the reduction.
+ * loop        : `reduce_loop` from `ufunc_object.c`.  TODO: Refactor
  * data        : Data which is passed to the inner loop.
  * buffersize  : Buffer size for the iterator. For the default, pass in 0.
  * funcname    : The name of the reduction function, for error messages.
@@ -182,18 +182,15 @@ PyArray_CopyInitialReduceValues(
  * generalized ufuncs!)
  */
 NPY_NO_EXPORT PyArrayObject *
-PyUFunc_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out,
-                      PyArrayObject *wheremask,
-                      PyArray_Descr *operand_dtype,
-                      PyArray_Descr *result_dtype,
-                      NPY_CASTING casting,
-                      npy_bool *axis_flags, int reorderable,
-                      int keepdims,
-                      PyObject *identity,
-                      PyArray_ReduceLoopFunc *loop,
-                      void *data, npy_intp buffersize, const char *funcname,
-                      int errormask)
+PyUFunc_ReduceWrapper(
+        PyArrayObject *operand, PyArrayObject *out, PyArrayObject *wheremask,
+        PyArray_Descr *operand_dtype, PyArray_Descr *result_dtype,
+        NPY_CASTING casting,
+        npy_bool *axis_flags, int reorderable, int keepdims,
+        PyObject *identity, PyArray_ReduceLoopFunc *loop,
+        void *data, npy_intp buffersize, const char *funcname, int errormask)
 {
+    assert(loop != NULL);
     PyArrayObject *result = NULL;
     npy_intp skip_first_count = 0;
 
@@ -201,7 +198,7 @@ PyUFunc_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out,
     NpyIter *iter = NULL;
     PyArrayObject *op[3];
     PyArray_Descr *op_dtypes[3];
-    npy_uint32 flags, op_flags[3];
+    npy_uint32 it_flags, op_flags[3];
 
     /* More than one axis means multiple orders are possible */
     if (!reorderable && count_axes(PyArray_NDIM(operand), axis_flags) > 1) {
@@ -227,7 +224,7 @@ PyUFunc_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out,
     op_dtypes[0] = result_dtype;
     op_dtypes[1] = operand_dtype;
 
-    flags = NPY_ITER_BUFFERED |
+    it_flags = NPY_ITER_BUFFERED |
             NPY_ITER_EXTERNAL_LOOP |
             NPY_ITER_GROWINNER |
             NPY_ITER_DONT_NEGATE_STRIDES |
@@ -293,7 +290,7 @@ PyUFunc_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out,
         }
     }
 
-    iter = NpyIter_AdvancedNew(wheremask == NULL ? 2 : 3, op, flags,
+    iter = NpyIter_AdvancedNew(wheremask == NULL ? 2 : 3, op, it_flags,
                                NPY_KEEPORDER, casting,
                                op_flags,
                                op_dtypes,
@@ -304,11 +301,14 @@ PyUFunc_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out,
 
     result = NpyIter_GetOperandArray(iter)[0];
 
+    int needs_api = NpyIter_IterationNeedsAPI(iter);
+    /* Start with the floating-point exception flags cleared */
+    npy_clear_floatstatus_barrier((char*)&iter);
+
     /*
      * Initialize the result to the reduction unit if possible,
      * otherwise copy the initial values and get a view to the rest.
      */
-
     if (identity != Py_None) {
         if (PyArray_FillWithScalar(result, identity) < 0) {
             goto fail;
@@ -331,15 +331,11 @@ PyUFunc_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out,
         goto fail;
     }
 
-    /* Start with the floating-point exception flags cleared */
-    npy_clear_floatstatus_barrier((char*)&iter);
-
     if (NpyIter_GetIterSize(iter) != 0) {
         NpyIter_IterNextFunc *iternext;
         char **dataptr;
         npy_intp *strideptr;
         npy_intp *countptr;
-        int needs_api;
 
         iternext = NpyIter_GetIterNext(iter, NULL);
         if (iternext == NULL) {
@@ -349,16 +345,6 @@ PyUFunc_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out,
         strideptr = NpyIter_GetInnerStrideArray(iter);
         countptr = NpyIter_GetInnerLoopSizePtr(iter);
 
-        needs_api = NpyIter_IterationNeedsAPI(iter);
-
-        /* Straightforward reduction */
-        if (loop == NULL) {
-            PyErr_Format(PyExc_RuntimeError,
-                    "reduction operation %s did not supply an "
-                    "inner loop function", funcname);
-            goto fail;
-        }
-
         if (loop(iter, dataptr, strideptr, countptr,
                         iternext, needs_api, skip_first_count, data) < 0) {
             goto fail;