Cleanup elemwise_cgen.py

pytensor/tensor/elemwise_cgen.py

+from textwrap import dedent, indent
+
 from pytensor.configdefaults import config
 
 
@@ -8,12 +10,10 @@ def make_declare(loop_orders, dtypes, sub):
     """
     decl = ""
     for i, (loop_order, dtype) in enumerate(zip(loop_orders, dtypes)):
-        var = sub[f"lv{int(i)}"]  # input name corresponding to ith loop variable
+        var = sub[f"lv{i}"]  # input name corresponding to ith loop variable
         # we declare an iteration variable
         # and an integer for the number of dimensions
-        decl += f"""
-        {dtype}* {var}_iter;
-        """
+        decl += f"{dtype}* {var}_iter;\n"
         for j, value in enumerate(loop_order):
             if value != "x":
                 # If the dimension is not broadcasted, we declare
@@ -21,17 +21,15 @@ def make_declare(loop_orders, dtypes, sub):
                 # the stride in that dimension,
                 # and the jump from an iteration to the next
                 decl += f"""
-                npy_intp {var}_n{int(value)};
-                ssize_t {var}_stride{int(value)};
-                int {var}_jump{int(value)}_{int(j)};
+                npy_intp {var}_n{value};
+                ssize_t {var}_stride{value};
+                int {var}_jump{value}_{j};
                 """
 
             else:
                 # if the dimension is broadcasted, we only need
                 # the jump (arbitrary length and stride = 0)
-                decl += f"""
-                int {var}_jump{value}_{int(j)};
-                """
+                decl += f"int {var}_jump{value}_{j};\n"
 
     return decl
 
@@ -39,7 +37,7 @@ def make_declare(loop_orders, dtypes, sub):
 def make_checks(loop_orders, dtypes, sub):
     init = ""
     for i, (loop_order, dtype) in enumerate(zip(loop_orders, dtypes)):
-        var = f"%(lv{int(i)})s"
+        var = sub[f"lv{i}"]
         # List of dimensions of var that are not broadcasted
         nonx = [x for x in loop_order if x != "x"]
         if nonx:
@@ -47,12 +45,14 @@ def make_checks(loop_orders, dtypes, sub):
             # this is a check that the number of dimensions of the
             # tensor is as expected.
             min_nd = max(nonx) + 1
-            init += f"""
+            init += dedent(
+                f"""
                 if (PyArray_NDIM({var}) < {min_nd}) {{
                     PyErr_SetString(PyExc_ValueError, "Not enough dimensions on input.");
-                %(fail)s
+                    {indent(sub["fail"], " " * 12)}
                 }}
                 """
+            )
 
         # In loop j, adjust represents the difference of values of the
         # data pointer between the beginning and the end of the
@@ -75,9 +75,7 @@ def make_checks(loop_orders, dtypes, sub):
                 adjust = f"{var}_n{index}*{var}_stride{index}"
             else:
                 jump = f"-({adjust})"
-                init += f"""
-                {var}_jump{index}_{j} = {jump};
-                """
+                init += f"{var}_jump{index}_{j} = {jump};\n"
                 adjust = "0"
     check = ""
 
@@ -101,34 +99,36 @@ def make_checks(loop_orders, dtypes, sub):
 
         j0, x0 = to_compare[0]
         for j, x in to_compare[1:]:
-            check += f"""
-            if (%(lv{j0})s_n{x0} != %(lv{j})s_n{x})
+            check += dedent(
+                f"""
+                if ({sub[f"lv{j0}"]}_n{x0} != {sub[f"lv{j}"]}_n{x})
                 {{
-                if (%(lv{j0})s_n{x0} == 1 || %(lv{j})s_n{x} == 1)
+                    if ({sub[f"lv{j0}"]}_n{x0} == 1 || {sub[f"lv{j}"]}_n{x} == 1)
                     {{
                         PyErr_Format(PyExc_ValueError, "{runtime_broadcast_error_msg}",
                        {j0},
                        {x0},
-                   (long long int) %(lv{j0})s_n{x0},
+                       (long long int) {sub[f"lv{j0}"]}_n{x0},
                        {j},
                        {x},
-                   (long long int) %(lv{j})s_n{x}
+                       (long long int) {sub[f"lv{j}"]}_n{x}
                         );
                     }} else {{
                         PyErr_Format(PyExc_ValueError, "Input dimension mismatch: (input[%%i].shape[%%i] = %%lld, input[%%i].shape[%%i] = %%lld)",
                            {j0},
                            {x0},
-                       (long long int) %(lv{j0})s_n{x0},
+                           (long long int) {sub[f"lv{j0}"]}_n{x0},
                            {j},
                            {x},
-                       (long long int) %(lv{j})s_n{x}
+                           (long long int) {sub[f"lv{j}"]}_n{x}
                         );
                     }}
-                %(fail)s
+                    {sub["fail"]}
                 }}
             """
+            )
 
-    return init % sub + check % sub
+    return init + check
 
 
 def compute_output_dims_lengths(array_name: str, loop_orders, sub) -> str:
@@ -144,7 +144,7 @@ def compute_output_dims_lengths(array_name: str, loop_orders, sub) -> str:
         # Borrow the length of the first non-broadcastable input dimension
         for j, candidate in enumerate(candidates):
             if candidate != "x":
-                var = sub[f"lv{int(j)}"]
+                var = sub[f"lv{j}"]
                 dims_c_code += f"{array_name}[{i}] = {var}_n{candidate};\n"
                 break
         # If none is non-broadcastable, the output dimension has a length of 1
@@ -177,13 +177,14 @@ def make_alloc(loop_orders, dtype, sub, fortran="0"):
     # way that its contiguous dimensions match one of the input's
     # contiguous dimensions, or the dimension with the smallest
     # stride. Right now, it is allocated to be C_CONTIGUOUS.
-    return f"""
+    return dedent(
+        f"""
         {{
             npy_intp dims[{nd}];
-        //npy_intp* dims = (npy_intp*)malloc({nd} * sizeof(npy_intp));
             {init_dims}
             if (!{olv}) {{
-            {olv} = (PyArrayObject*)PyArray_EMPTY({nd}, dims,
+                {olv} = (PyArrayObject*)PyArray_EMPTY({nd},
+                                                      dims,
                                                       {type},
                                                       {fortran});
             }}
@@ -206,6 +207,7 @@ def make_alloc(loop_orders, dtype, sub, fortran="0"):
             }}
         }}
         """
+    )
 
 
 def make_loop(loop_orders, dtypes, loop_tasks, sub, openmp=None):
@@ -235,11 +237,11 @@ def make_loop(loop_orders, dtypes, loop_tasks, sub, openmp=None):
     """
 
     def loop_over(preloop, code, indices, i):
-        iterv = f"ITER_{int(i)}"
+        iterv = f"ITER_{i}"
         update = ""
         suitable_n = "1"
         for j, index in enumerate(indices):
-            var = sub[f"lv{int(j)}"]
+            var = sub[f"lv{j}"]
             dtype = dtypes[j]
             update += f"{dtype} &{var}_i = * ( {var}_iter + {iterv} * {var}_jump{index}_{i} );\n"
 
@@ -305,13 +307,13 @@ def make_reordered_loop(
     nnested = len(init_loop_orders[0])
 
     # This is the var from which we'll get the loop order
-    ovar = sub[f"lv{int(olv_index)}"]
+    ovar = sub[f"lv{olv_index}"]
 
     # The loops are ordered by (decreasing) absolute values of ovar's strides.
     # The first element of each pair is the absolute value of the stride
     # The second element correspond to the index in the initial loop order
     order_loops = f"""
-    std::vector< std::pair<int, int> > {ovar}_loops({int(nnested)});
+    std::vector< std::pair<int, int> > {ovar}_loops({nnested});
     std::vector< std::pair<int, int> >::iterator {ovar}_loops_it = {ovar}_loops.begin();
     """
 
@@ -319,7 +321,7 @@ def make_reordered_loop(
     for i, index in enumerate(init_loop_orders[olv_index]):
         if index != "x":
             order_loops += f"""
-            {ovar}_loops_it->first = abs(PyArray_STRIDES({ovar})[{int(index)}]);
+            {ovar}_loops_it->first = abs(PyArray_STRIDES({ovar})[{index}]);
             """
         else:
             # Stride is 0 when dimension is broadcastable
@@ -328,7 +330,7 @@ def make_reordered_loop(
             """
 
         order_loops += f"""
-        {ovar}_loops_it->second = {int(i)};
+        {ovar}_loops_it->second = {i};
         ++{ovar}_loops_it;
         """
 
@@ -352,7 +354,7 @@ def make_reordered_loop(
 
     for i in range(nnested):
         declare_totals += f"""
-        int TOTAL_{int(i)} = init_totals[{ovar}_loops_it->second];
+        int TOTAL_{i} = init_totals[{ovar}_loops_it->second];
         ++{ovar}_loops_it;
         """
 
@@ -365,7 +367,7 @@ def make_reordered_loop(
         specified loop_order.
 
         """
-        var = sub[f"lv{int(i)}"]
+        var = sub[f"lv{i}"]
         r = []
         for index in loop_order:
             # Note: the stride variable is not declared for broadcasted variables
@@ -383,7 +385,7 @@ def make_reordered_loop(
     )
 
     declare_strides = f"""
-    int init_strides[{int(nvars)}][{int(nnested)}] = {{
+    int init_strides[{nvars}][{nnested}] = {{
         {strides}
     }};"""
 
@@ -394,33 +396,33 @@ def make_reordered_loop(
     """
 
     for i in range(nvars):
-        var = sub[f"lv{int(i)}"]
+        var = sub[f"lv{i}"]
         declare_strides += f"""
         {ovar}_loops_rit = {ovar}_loops.rbegin();"""
         for j in reversed(range(nnested)):
             declare_strides += f"""
-            int {var}_stride_l{int(j)} = init_strides[{int(i)}][{ovar}_loops_rit->second];
+            int {var}_stride_l{j} = init_strides[{i}][{ovar}_loops_rit->second];
             ++{ovar}_loops_rit;
             """
 
     declare_iter = ""
     for i, dtype in enumerate(dtypes):
-        var = sub[f"lv{int(i)}"]
+        var = sub[f"lv{i}"]
         declare_iter += f"{var}_iter = ({dtype}*)(PyArray_DATA({var}));\n"
 
     pointer_update = ""
     for j, dtype in enumerate(dtypes):
-        var = sub[f"lv{int(j)}"]
+        var = sub[f"lv{j}"]
         pointer_update += f"{dtype} &{var}_i = * ( {var}_iter"
         for i in reversed(range(nnested)):
-            iterv = f"ITER_{int(i)}"
-            pointer_update += f"+{var}_stride_l{int(i)}*{iterv}"
+            iterv = f"ITER_{i}"
+            pointer_update += f"+{var}_stride_l{i}*{iterv}"
         pointer_update += ");\n"
 
     loop = inner_task
     for i in reversed(range(nnested)):
-        iterv = f"ITER_{int(i)}"
-        total = f"TOTAL_{int(i)}"
+        iterv = f"ITER_{i}"
+        total = f"TOTAL_{i}"
         update = ""
         forloop = ""
         # The pointers are defined only in the most inner loop
@@ -434,36 +436,14 @@ def make_reordered_loop(
 
         loop = f"""
         {forloop}
-        {{ // begin loop {int(i)}
+        {{ // begin loop {i}
             {update}
             {loop}
-        }} // end loop {int(i)}
+        }} // end loop {i}
         """
 
-    return f"{{\n{order_loops}\n{declare_totals}\n{declare_strides}\n{declare_iter}\n{loop}\n}}\n"
-
-
-# print make_declare(((0, 1, 2, 3), ('x', 1, 0, 3), ('x', 'x', 'x', 0)),
-#                    ('double', 'int', 'float'),
-#                    dict(lv0='x', lv1='y', lv2='z', fail="FAIL;"))
-
-# print make_checks(((0, 1, 2, 3), ('x', 1, 0, 3), ('x', 'x', 'x', 0)),
-#                   ('double', 'int', 'float'),
-#                   dict(lv0='x', lv1='y', lv2='z', fail="FAIL;"))
-
-# print make_alloc(((0, 1, 2, 3), ('x', 1, 0, 3), ('x', 'x', 'x', 0)),
-#                  'double',
-#                  dict(olv='out', lv0='x', lv1='y', lv2='z', fail="FAIL;"))
-
-# print make_loop(((0, 1, 2, 3), ('x', 1, 0, 3), ('x', 'x', 'x', 0)),
-#                 ('double', 'int', 'float'),
-#                 (("C00;", "C%01;"), ("C10;", "C11;"), ("C20;", "C21;"), ("C30;", "C31;"),"C4;"),
-#                 dict(lv0='x', lv1='y', lv2='z', fail="FAIL;"))
-
-# print make_loop(((0, 1, 2, 3), (3, 'x', 0, 'x'), (0, 'x', 'x', 'x')),
-#                 ('double', 'int', 'float'),
-#                 (("C00;", "C01;"), ("C10;", "C11;"), ("C20;", "C21;"), ("C30;", "C31;"),"C4;"),
-#                 dict(lv0='x', lv1='y', lv2='z', fail="FAIL;"))
+    code = "\n".join((order_loops, declare_totals, declare_strides, declare_iter, loop))
+    return f"{{\n{code}\n}}\n"
 
 
 ##################