Fix RUF005

Automated fixes by RUF, and update of the TensorConstructorType
type in scan/op.py because mypy didn't like something there.

Author: Armavica

pytensor/breakpoint.py

@@ -92,7 +92,7 @@ def make_node(self, condition, *monitored_vars):
             new_op.inp_types.append(monitored_vars[i].type)
 
         # Build the Apply node
-        inputs = [condition] + list(monitored_vars)
+        inputs = [condition, *list(monitored_vars)]
         outputs = [inp.type() for inp in monitored_vars]
         return Apply(op=new_op, inputs=inputs, outputs=outputs)
 
@@ -142,7 +142,7 @@ def perform(self, node, inputs, output_storage):
                 output_storage[i][0] = inputs[i + 1]
 
     def grad(self, inputs, output_gradients):
-        return [DisconnectedType()()] + output_gradients
+        return [DisconnectedType()(), *output_gradients]
 
     def infer_shape(self, fgraph, inputs, input_shapes):
         # Return the shape of every input but the condition (first input)

pytensor/compile/debugmode.py

@@ -892,9 +892,9 @@ def _get_preallocated_maps(
 
         # Use the same step on all dimensions before the last check_ndim.
         if all(s == 1 for s in out_shape[:-check_ndim]):
-            step_signs_list = [(1,)] + step_signs_list
+            step_signs_list = [(1,), *step_signs_list]
         else:
-            step_signs_list = [(-1, 1)] + step_signs_list
+            step_signs_list = [(-1, 1), *step_signs_list]
 
         for step_signs in itertools_product(*step_signs_list):
             for step_size in (1, 2):

pytensor/compile/sharedvalue.py

@@ -209,7 +209,7 @@ def shared(value, name=None, strict=False, allow_downcast=None, **kwargs):
         add_tag_trace(var)
         return var
     except MemoryError as e:
-        e.args = e.args + ("Consider using `pytensor.shared(..., borrow=True)`",)
+        e.args = (*e.args, "Consider using `pytensor.shared(..., borrow=True)`")
         raise
 
 

pytensor/configdefaults.py

@@ -1382,7 +1382,8 @@ def add_caching_dir_configvars():
     "fft_tiling",
     "winograd",
     "winograd_non_fused",
-) + SUPPORTED_DNN_CONV_ALGO_RUNTIME
+    *SUPPORTED_DNN_CONV_ALGO_RUNTIME,
+)
 
 SUPPORTED_DNN_CONV_ALGO_BWD_DATA = (
     "none",
@@ -1391,7 +1392,8 @@ def add_caching_dir_configvars():
     "fft_tiling",
     "winograd",
     "winograd_non_fused",
-) + SUPPORTED_DNN_CONV_ALGO_RUNTIME
+    *SUPPORTED_DNN_CONV_ALGO_RUNTIME,
+)
 
 SUPPORTED_DNN_CONV_ALGO_BWD_FILTER = (
     "none",
@@ -1400,7 +1402,8 @@ def add_caching_dir_configvars():
     "small",
     "winograd_non_fused",
     "fft_tiling",
-) + SUPPORTED_DNN_CONV_ALGO_RUNTIME
+    *SUPPORTED_DNN_CONV_ALGO_RUNTIME,
+)
 
 SUPPORTED_DNN_CONV_PRECISION = (
     "as_input_f32",

pytensor/gradient.py

@@ -1972,7 +1972,7 @@ def inner_function(*args):
     jacobs, updates = pytensor.scan(
         inner_function,
         sequences=pytensor.tensor.arange(expression.shape[0]),
-        non_sequences=[expression] + wrt,
+        non_sequences=[expression, *wrt],
     )
     assert not updates, "Scan has returned a list of updates; this should not happen."
     return as_list_or_tuple(using_list, using_tuple, jacobs)

pytensor/graph/features.py

@@ -508,11 +508,13 @@ def consistent_(self, fgraph):
 
 
 class ReplaceValidate(History, Validator):
-    pickle_rm_attr = (
-        ["replace_validate", "replace_all_validate", "replace_all_validate_remove"]
-        + History.pickle_rm_attr
-        + Validator.pickle_rm_attr
-    )
+    pickle_rm_attr = [
+        "replace_validate",
+        "replace_all_validate",
+        "replace_all_validate_remove",
+        *History.pickle_rm_attr,
+        *Validator.pickle_rm_attr,
+    ]
 
     def on_attach(self, fgraph):
         for attr in (

pytensor/graph/rewriting/basic.py

@@ -405,7 +405,7 @@ def print_profile(cls, stream, prof, level=0):
             else:
                 name = rewrite.name
             idx = rewrites.index(rewrite)
-            ll.append((name, rewrite.__class__.__name__, idx) + nb_n)
+            ll.append((name, rewrite.__class__.__name__, idx, *nb_n))
         lll = sorted(zip(prof, ll), key=lambda a: a[0])
 
         for t, rewrite in lll[::-1]:
@@ -1138,7 +1138,8 @@ def decorator(f):
         req = requirements
         if inplace:
             dh_handler = dh.DestroyHandler
-            req = tuple(requirements) + (
+            req = (
+                *tuple(requirements),
                 lambda fgraph: fgraph.attach_feature(dh_handler()),
             )
         rval = FromFunctionNodeRewriter(f, tracks, req)

pytensor/graph/rewriting/db.py

@@ -73,7 +73,7 @@ def register(
 
         if use_db_name_as_tag:
             if self.name is not None:
-                tags = tags + (self.name,)
+                tags = (*tags, self.name)
 
         rewriter.name = name
         # This restriction is there because in many place we suppose that

pytensor/graph/utils.py

@@ -171,7 +171,7 @@ def __init__(self, *args, **kwargs):
             assert list(kwargs.keys()) == ["variable"]
             error_msg = get_variable_trace_string(kwargs["variable"])
             if error_msg:
-                args = args + (error_msg,)
+                args = (*args, error_msg)
         s = "\n".join(args)  # Needed to have the new line print correctly
         super().__init__(s)
 

pytensor/ifelse.py

@@ -227,7 +227,7 @@ def make_node(self, condition: "TensorLike", *true_false_branches: Any):
 
         return Apply(
             self,
-            [condition] + new_inputs_true_branch + new_inputs_false_branch,
+            [condition, *new_inputs_true_branch, *new_inputs_false_branch],
             output_vars,
         )
 
@@ -275,11 +275,11 @@ def grad(self, ins, grads):
         # condition + epsilon always triggers the same branch as condition
         condition_grad = condition.zeros_like().astype(config.floatX)
 
-        return (
-            [condition_grad]
-            + if_true_op(*inputs_true_grad, return_list=True)
-            + if_false_op(*inputs_false_grad, return_list=True)
-        )
+        return [
+            condition_grad,
+            *if_true_op(*inputs_true_grad, return_list=True),
+            *if_false_op(*inputs_false_grad, return_list=True),
+        ]
 
     def make_thunk(self, node, storage_map, compute_map, no_recycling, impl=None):
         cond = node.inputs[0]
@@ -397,7 +397,7 @@ def ifelse(
 
     new_ifelse = IfElse(n_outs=len(then_branch), as_view=False, name=name)
 
-    ins = [condition] + list(then_branch) + list(else_branch)
+    ins = [condition, *list(then_branch), *list(else_branch)]
     rval = new_ifelse(*ins, return_list=True)
 
     if rval_type is None:
@@ -611,7 +611,7 @@ def apply(self, fgraph):
                 mn_fs = merging_node.inputs[1:][merging_node.op.n_outs :]
                 pl_ts = proposal.inputs[1:][: proposal.op.n_outs]
                 pl_fs = proposal.inputs[1:][proposal.op.n_outs :]
-                new_ins = [merging_node.inputs[0]] + mn_ts + pl_ts + mn_fs + pl_fs
+                new_ins = [merging_node.inputs[0], *mn_ts, *pl_ts, *mn_fs, *pl_fs]
                 mn_name = "?"
                 if merging_node.op.name:
                     mn_name = merging_node.op.name
@@ -673,7 +673,7 @@ def cond_remove_identical(fgraph, node):
 
     new_ifelse = IfElse(n_outs=len(nw_ts), as_view=op.as_view, name=op.name)
 
-    new_ins = [node.inputs[0]] + nw_ts + nw_fs
+    new_ins = [node.inputs[0], *nw_ts, *nw_fs]
     new_outs = new_ifelse(*new_ins, return_list=True)
 
     rval = []
@@ -711,7 +711,7 @@ def cond_merge_random_op(fgraph, main_node):
             mn_fs = merging_node.inputs[1:][merging_node.op.n_outs :]
             pl_ts = proposal.inputs[1:][: proposal.op.n_outs]
             pl_fs = proposal.inputs[1:][proposal.op.n_outs :]
-            new_ins = [merging_node.inputs[0]] + mn_ts + pl_ts + mn_fs + pl_fs
+            new_ins = [merging_node.inputs[0], *mn_ts, *pl_ts, *mn_fs, *pl_fs]
             mn_name = "?"
             if merging_node.op.name:
                 mn_name = merging_node.op.name