[pre-commit.ci] pre-commit autoupdate (#666)

.pre-commit-config.yaml

@@ -23,13 +23,13 @@ repos:
           )$
       - id: check-merge-conflict
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.2.2
+    rev: v0.3.2
     hooks:
       - id: ruff
         args: ["--fix", "--output-format=full"]
       - id: ruff-format
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.8.0
+    rev: v1.9.0
     hooks:
       - id: mypy
         language: python

pytensor/__init__.py

@@ -18,7 +18,6 @@ To learn more, check out:
 
 """
 
-
 __docformat__ = "restructuredtext en"
 
 # Set a default logger. It is important to do this before importing some other

pytensor/compile/builders.py

 """Define new Ops from existing Ops"""
+
 from collections import OrderedDict
 from collections.abc import Sequence
 from copy import copy

pytensor/compile/compiledir.py

@@ -2,6 +2,7 @@
 This module contains housekeeping functions for cleaning/purging the "compiledir".
 It is used by the "pytensor-cache" CLI tool, located in the /bin folder of the repository.
 """
+
 import logging
 import os
 import pickle

pytensor/compile/compilelock.py

@@ -2,6 +2,7 @@
 Locking mechanism to ensure no two compilations occur simultaneously
 in the same compilation directory (which can cause crashes).
 """
+
 import os
 import threading
 from contextlib import contextmanager

pytensor/compile/debugmode.py

@@ -5,7 +5,6 @@ TODO: add support for IfElse Op, LazyLinker, etc.
 
 """
 
-
 import copy
 import gc
 import logging
@@ -2317,10 +2316,7 @@ class DebugMode(Mode):
             raise ValueError("DebugMode has to check at least one of c and py code")
 
     def __str__(self):
-        return "DebugMode(linker={}, optimizer={})".format(
-            self.provided_linker,
-            self.provided_optimizer,
-        )
+        return f"DebugMode(linker={self.provided_linker}, optimizer={self.provided_optimizer})"
 
 
 register_mode("DEBUG_MODE", DebugMode(optimizer="fast_run"))

pytensor/compile/function/pfunc.py

@@ -35,8 +35,7 @@ def rebuild_collect_shared(
         list[Variable],
         list[SharedVariable],
     ],
-]:
-    ...
+]: ...
 
 
 @overload
@@ -58,8 +57,7 @@ def rebuild_collect_shared(
         list[Variable],
         list[SharedVariable],
     ],
-]:
-    ...
+]: ...
 
 
 @overload
@@ -81,8 +79,7 @@ def rebuild_collect_shared(
         list[Variable],
         list[SharedVariable],
     ],
-]:
-    ...
+]: ...
 
 
 @overload
@@ -104,8 +101,7 @@ def rebuild_collect_shared(
         list[Variable],
         list[SharedVariable],
     ],
-]:
-    ...
+]: ...
 
 
 def rebuild_collect_shared(

pytensor/compile/io.py

@@ -3,7 +3,6 @@ Define `SymbolicInput`, `SymbolicOutput`, `In`, `Out`.
 
 """
 
-
 import logging
 
 from pytensor.link.basic import Container

pytensor/d3viz/d3viz.py

@@ -3,7 +3,6 @@
 Author: Christof Angermueller <cangermueller@gmail.com>
 """
 
-
 import json
 import os
 import shutil

pytensor/d3viz/formatting.py

@@ -2,6 +2,7 @@
 
 Author: Christof Angermueller <cangermueller@gmail.com>
 """
+
 import os
 from functools import reduce
 

pytensor/graph/basic.py

 """Core graph classes."""
+
 import abc
 import warnings
 from collections import deque
@@ -643,8 +644,7 @@ class AtomicVariable(Variable[_TypeType, None]):
         super().__init__(type=type, owner=None, index=None, name=name, **kwargs)
 
     @abc.abstractmethod
-    def signature(self):
-        ...
+    def signature(self): ...
 
     def merge_signature(self):
         return self.signature()
@@ -1309,8 +1309,7 @@ def general_toposort(
     compute_deps_cache: Callable[[T], Optional[Union[OrderedSet, list[T]]]],
     deps_cache: Optional[dict[T, list[T]]],
     clients: Optional[dict[T, list[T]]],
-) -> list[T]:
-    ...
+) -> list[T]: ...
 
 
 @overload
@@ -1320,8 +1319,7 @@ def general_toposort(
     compute_deps_cache: None,
     deps_cache: None,
     clients: Optional[dict[T, list[T]]],
-) -> list[T]:
-    ...
+) -> list[T]: ...
 
 
 def general_toposort(

pytensor/graph/destroyhandler.py

@@ -3,6 +3,7 @@ Classes and functions for validating graphs that contain view
 and inplace operations.
 
 """
+
 import itertools
 from collections import OrderedDict, deque
 

pytensor/graph/fg.py

 """A container for specifying and manipulating a graph with distinct inputs and outputs."""
+
 import time
 from collections import OrderedDict
 from collections.abc import Iterable, Sequence

pytensor/graph/replace.py

@@ -40,8 +40,7 @@ def clone_replace(
     output: Sequence[Variable],
     replace: Optional[ReplaceTypes] = None,
     **rebuild_kwds,
-) -> list[Variable]:
-    ...
+) -> list[Variable]: ...
 
 
 @overload
@@ -51,8 +50,7 @@ def clone_replace(
         Union[Iterable[tuple[Variable, Variable]], dict[Variable, Variable]]
     ] = None,
     **rebuild_kwds,
-) -> Variable:
-    ...
+) -> Variable: ...
 
 
 def clone_replace(
@@ -95,8 +93,7 @@ def graph_replace(
     replace: Optional[ReplaceTypes] = None,
     *,
     strict=True,
-) -> Variable:
-    ...
+) -> Variable: ...
 
 
 @overload
@@ -105,8 +102,7 @@ def graph_replace(
     replace: Optional[ReplaceTypes] = None,
     *,
     strict=True,
-) -> list[Variable]:
-    ...
+) -> list[Variable]: ...
 
 
 def graph_replace(
@@ -229,16 +225,14 @@ def _vectorize_not_needed(op, node, *batched_inputs):
 def vectorize_graph(
     outputs: Variable,
     replace: Mapping[Variable, Variable],
-) -> Variable:
-    ...
+) -> Variable: ...
 
 
 @overload
 def vectorize_graph(
     outputs: Sequence[Variable],
     replace: Mapping[Variable, Variable],
-) -> Sequence[Variable]:
-    ...
+) -> Sequence[Variable]: ...
 
 
 def vectorize_graph(

pytensor/graph/rewriting/basic.py

 """This module defines the base classes for graph rewriting."""
+
 import abc
 import copy
 import functools
@@ -123,8 +124,7 @@ class GraphRewriter(Rewriter):
         """Rewrite a `FunctionGraph`."""
         return self.rewrite(fgraph)
 
-    def add_requirements(self, fgraph):
-        ...
+    def add_requirements(self, fgraph): ...
 
     def print_summary(self, stream=sys.stdout, level=0, depth=-1):
         name = getattr(self, "name", None)
@@ -1683,9 +1683,8 @@ class PatternNodeRewriter(NodeRewriter):
             else:
                 return str(pattern)
 
-        return "{} -> {}".format(
-            pattern_to_str(self.in_pattern),
-            pattern_to_str(self.out_pattern),
+        return (
+            f"{pattern_to_str(self.in_pattern)} -> {pattern_to_str(self.out_pattern)}"
         )
 
     def __repr__(self):

pytensor/link/c/basic.py

@@ -2,6 +2,7 @@
 Defines Linkers that deal with C implementations.
 
 """
+
 import logging
 import sys
 from collections import defaultdict
@@ -1566,16 +1567,16 @@ class CLinker(Linker):
 
             # Static methods that can run and destroy the struct built by
             # instantiate.
-            static = """
-        static int {struct_name}_executor({struct_name} *self) {{
+            static = f"""
+        static int {self.struct_name}_executor({self.struct_name} *self) {{
             return self->run();
         }}
 
-        static void {struct_name}_destructor(PyObject *capsule) {{
-            {struct_name} *self = ({struct_name} *)PyCapsule_GetContext(capsule);
+        static void {self.struct_name}_destructor(PyObject *capsule) {{
+            {self.struct_name} *self = ({self.struct_name} *)PyCapsule_GetContext(capsule);
             delete self;
         }}
-    """.format(struct_name=self.struct_name)
+    """
 
             # We add all the support code, compile args, headers and libs we need.
             for support_code in self.support_code() + self.c_support_code_apply:

pytensor/link/c/cmodule.py

@@ -2,6 +2,7 @@
 Generate and compile C modules for Python.
 
 """
+
 import atexit
 import importlib
 import logging

pytensor/link/c/params_type.py

@@ -113,7 +113,6 @@ for more info about enumeration aliases).
 
 """
 
-
 import hashlib
 import re
 

pytensor/link/utils.py

@@ -503,14 +503,8 @@ def raise_with_op(
                 detailed_err_msg += f", TotalSize: {item[3]} Byte(s)\n"
             else:
                 detailed_err_msg += "\n"
-        detailed_err_msg += " TotalSize: {} Byte(s) {:.3f} GB\n".format(
-            total_size,
-            total_size / 1024 / 1024 / 1024,
-        )
-        detailed_err_msg += " TotalSize inputs: {} Byte(s) {:.3f} GB\n".format(
-            total_size_inputs,
-            total_size_inputs / 1024 / 1024 / 1024,
-        )
+        detailed_err_msg += f" TotalSize: {total_size} Byte(s) {total_size / 1024 / 1024 / 1024:.3f} GB\n"
+        detailed_err_msg += f" TotalSize inputs: {total_size_inputs} Byte(s) {total_size_inputs / 1024 / 1024 / 1024:.3f} GB\n"
 
     else:
         hints.append(

pytensor/link/vm.py

@@ -5,6 +5,7 @@ A VM is not actually different from a Linker, we just decided
 VM was a better name at some point.
 
 """
+
 import platform
 import sys
 import time

pytensor/misc/may_share_memory.py

@@ -3,7 +3,6 @@ Function to detect memory sharing for ndarray AND sparse type.
 numpy version support only ndarray.
 """
 
-
 import numpy as np
 
 from pytensor.tensor.type import TensorType

pytensor/misc/safe_asarray.py

@@ -2,7 +2,6 @@
 Helper function to safely convert an array to a new data type.
 """
 
-
 import numpy as np
 
 from pytensor.configdefaults import config

pytensor/printing.py

@@ -646,13 +646,7 @@ def _debugprint(
             tot_time_percent = (tot_time_dict[node] / profile.fct_call_time) * 100
 
             print(
-                "{} --> {:8.2e}s {:4.1f}% {:8.2e}s {:4.1f}%".format(
-                    var_output,
-                    op_time,
-                    op_time_percent,
-                    tot_time,
-                    tot_time_percent,
-                ),
+                f"{var_output} --> {op_time:8.2e}s {op_time_percent:4.1f}% {tot_time:8.2e}s {tot_time_percent:4.1f}%",
                 file=file,
             )
         else:
@@ -1157,14 +1151,14 @@ if use_ascii:
         epsilon="\\epsilon",
     )
 else:
-    special = dict(middle_dot="\u00B7", big_sigma="\u03A3")
+    special = dict(middle_dot="\u00b7", big_sigma="\u03a3")
 
     greek = dict(
-        alpha="\u03B1",
-        beta="\u03B2",
-        gamma="\u03B3",
-        delta="\u03B4",
-        epsilon="\u03B5",
+        alpha="\u03b1",
+        beta="\u03b2",
+        gamma="\u03b3",
+        delta="\u03b4",
+        epsilon="\u03b5",
     )
 
 

pytensor/scalar/basic.py

@@ -273,7 +273,6 @@ def convert(x, dtype=None):
 
 
 class ScalarType(CType, HasDataType, HasShape):
-
     """
     Internal class, should not be used by clients.
 

pytensor/scan/__init__.py

@@ -33,7 +33,6 @@ functions: ``scan()``, ``map()``, ``reduce()``, ``foldl()``,
 
 """
 
-
 __docformat__ = "restructedtext en"
 __authors__ = (
     "Razvan Pascanu "

pytensor/scan/op.py

@@ -3368,13 +3368,7 @@ def profile_printer(
                     total_scan_fct_time += scan_fct_time
                     total_scan_op_time += scan_op_time
                     print(
-                        "      {:5.1f}s  {:5.1f}s  {:5.1f}s  {:5.1f}%  {:5.1f}%".format(
-                            v,
-                            scan_fct_time,
-                            scan_op_time,
-                            scan_fct_time / v * 100,
-                            scan_op_time / v * 100,
-                        ),
+                        f"      {v:5.1f}s  {scan_fct_time:5.1f}s  {scan_op_time:5.1f}s  {scan_fct_time / v * 100:5.1f}%  {scan_op_time / v * 100:5.1f}%",
                         node,
                         file=file,
                     )
@@ -3388,13 +3382,7 @@ def profile_printer(
             print("  No scan have its inner profile enabled.", file=file)
         else:
             print(
-                "total {:5.1f}s  {:5.1f}s  {:5.1f}s  {:5.1f}%  {:5.1f}%".format(
-                    total_super_scan_time,
-                    total_scan_fct_time,
-                    total_scan_op_time,
-                    total_scan_fct_time / total_super_scan_time * 100,
-                    total_scan_op_time / total_super_scan_time * 100,
-                ),
+                f"total {total_super_scan_time:5.1f}s  {total_scan_fct_time:5.1f}s  {total_scan_op_time:5.1f}s  {total_scan_fct_time / total_super_scan_time * 100:5.1f}%  {total_scan_op_time / total_super_scan_time * 100:5.1f}%",
                 file=file,
             )
 

pytensor/scan/scan_perform_ext.py

@@ -5,6 +5,7 @@ To update the `Scan` Cython code you must
 - update the version value in this file and in `scan_perform.pyx`
 
 """
+
 from pytensor.scan.scan_perform import get_version, perform  # noqa: F401
 
 

pytensor/sparse/basic.py

@@ -7,6 +7,7 @@ http://www-users.cs.umn.edu/~saad/software/SPARSKIT/paper.ps
 TODO: Automatic methods for determining best sparse format?
 
 """
+
 from typing import Literal
 from warnings import warn
 
@@ -486,13 +487,7 @@ class SparseConstant(TensorConstant, _sparse_py_operators):
         return SparseConstantSignature((self.type, self.data))
 
     def __str__(self):
-        return "{}{{{},{},shape={},nnz={}}}".format(
-            self.__class__.__name__,
-            self.format,
-            self.dtype,
-            self.data.shape,
-            self.data.nnz,
-        )
+        return f"{self.__class__.__name__}{{{self.format},{self.dtype},shape={self.data.shape},nnz={self.data.nnz}}}"
 
     def __repr__(self):
         return str(self)

pytensor/tensor/blas.py

@@ -767,10 +767,7 @@ class GemmRelated(COp):
 
     def build_gemm_call(self):
         if hasattr(self, "inplace"):
-            setup_z_Nz_Sz = "if(%(params)s->inplace){{{}}}else{{{}}}".format(
-                self.setup_z_Nz_Sz_inplace,
-                self.setup_z_Nz_Sz_outplace,
-            )
+            setup_z_Nz_Sz = f"if(%(params)s->inplace){{{self.setup_z_Nz_Sz_inplace}}}else{{{self.setup_z_Nz_Sz_outplace}}}"
         else:
             setup_z_Nz_Sz = self.setup_z_Nz_Sz
 

pytensor/tensor/blas_headers.py

-""" Header text for the C and Fortran BLAS interfaces.
+"""Header text for the C and Fortran BLAS interfaces.
 
 There is no standard name or location for this header, so we just insert it
 ourselves into the C code.

pytensor/tensor/conv/abstract_conv.py

@@ -2,7 +2,6 @@
 Abstract conv interface
 """
 
-
 import logging
 import sys
 import warnings
@@ -2175,8 +2174,8 @@ class BaseAbstractConv(Op):
                     )
                 ):
                     raise ValueError(
-                        "invalid border mode {}. The tuple can only contain integers "
-                        " or pairs of integers".format(border_mode)
+                        f"invalid border mode {border_mode}. The tuple can only contain integers "
+                        " or pairs of integers"
                     )
                 if isinstance(mode, tuple):
                     if convdim != 2:
@@ -2348,29 +2347,29 @@ class BaseAbstractConv(Op):
                         for n in range(output_channel_offset):
                             for im0 in range(input_channel_offset):
                                 if unshared:
-                                    out[
-                                        b, g * output_channel_offset + n, ...
-                                    ] += self.unshared2d(
-                                        img[b, g * input_channel_offset + im0, ...],
-                                        dilated_kern[
-                                            g * output_channel_offset + n, im0, ...
-                                        ],
-                                        out_shape[2:],
-                                        direction,
+                                    out[b, g * output_channel_offset + n, ...] += (
+                                        self.unshared2d(
+                                            img[b, g * input_channel_offset + im0, ...],
+                                            dilated_kern[
+                                                g * output_channel_offset + n, im0, ...
+                                            ],
+                                            out_shape[2:],
+                                            direction,
+                                        )
                                     )
                                 else:
                                     # some cast generates a warning here
-                                    out[
-                                        b, g * output_channel_offset + n, ...
-                                    ] += _convolve2d(
-                                        img[b, g * input_channel_offset + im0, ...],
-                                        dilated_kern[
-                                            g * output_channel_offset + n, im0, ...
-                                        ],
-                                        1,
-                                        val,
-                                        bval,
-                                        0,
+                                    out[b, g * output_channel_offset + n, ...] += (
+                                        _convolve2d(
+                                            img[b, g * input_channel_offset + im0, ...],
+                                            dilated_kern[
+                                                g * output_channel_offset + n, im0, ...
+                                            ],
+                                            1,
+                                            val,
+                                            bval,
+                                            0,
+                                        )
                                     )
 
         elif self.convdim == 3:
@@ -2550,10 +2549,8 @@ class AbstractConv(BaseAbstractConv):
             )
             if kern.shape[1 : 1 + self.convdim] != out_shape[2 : 2 + self.convdim]:
                 raise ValueError(
-                    "Kernel shape {} does not match " "computed output size {}".format(
-                        kern.shape[1 : 1 + self.convdim],
-                        out_shape[2 : 2 + self.convdim],
-                    )
+                    f"Kernel shape {kern.shape[1 : 1 + self.convdim]} does not match "
+                    f"computed output size {out_shape[2 : 2 + self.convdim]}"
                 )
             if any(self.subsample[i] > 1 for i in range(self.convdim)):
                 # Expand regions in kernel to correct for subsampling
@@ -3236,10 +3233,8 @@ class AbstractConv_gradInputs(BaseAbstractConv):
         if tuple(expected_topgrad_shape) != tuple(topgrad.shape):
             raise ValueError(
                 "invalid input_shape for gradInputs: the given input_shape "
-                "would produce an output of shape {}, but the given topgrad "
-                "has shape {}".format(
-                    tuple(expected_topgrad_shape), tuple(topgrad.shape)
-                )
+                f"would produce an output of shape {tuple(expected_topgrad_shape)}, but the given topgrad "
+                f"has shape {tuple(topgrad.shape)}"
             )
         if any(self.subsample[i] > 1 for i in range(self.convdim)):
             new_shape = (

pytensor/tensor/io.py

@@ -49,10 +49,8 @@ class LoadFromDisk(Op):
         out[0][0] = result
 
     def __str__(self):
-        return "Load{{dtype: {}, shape: {}, mmep: {}}}".format(
-            self.dtype,
-            self.shape,
-            self.mmap_mode,
+        return (
+            f"Load{{dtype: {self.dtype}, shape: {self.shape}, mmep: {self.mmap_mode}}}"
         )
 
 

pytensor/tensor/rewriting/basic.py

-""" Tensor optimizations addressing the ops in basic.py.
+"""Tensor optimizations addressing the ops in basic.py.
 
 Notes
 -----

pytensor/tensor/type_other.py

@@ -100,12 +100,7 @@ class SliceConstant(Constant):
         return (SliceConstant, self.data.start, self.data.stop, self.data.step)
 
     def __str__(self):
-        return "{}{{{}, {}, {}}}".format(
-            self.__class__.__name__,
-            self.data.start,
-            self.data.stop,
-            self.data.step,
-        )
+        return f"{self.__class__.__name__}{{{self.data.start}, {self.data.stop}, {self.data.step}}}"
 
 
 SliceType.constant_type = SliceConstant

pytensor/updates.py

-"""Defines Updates object for storing a (SharedVariable, new_value) mapping.
+"""Defines Updates object for storing a (SharedVariable, new_value) mapping."""
 
-"""
 import logging
 import warnings
 from collections import OrderedDict

scripts/run_mypy.py

@@ -8,6 +8,7 @@ Usage
 -----
 python scripts/run_mypy.py [--verbose]
 """
+
 import argparse
 import importlib
 import os

tests/link/c/test_cmodule.py

@@ -4,6 +4,7 @@ We don't have real tests for the cache, but it would be great to make them!
 But this one tests a current behavior that isn't good: the c_code isn't
 deterministic based on the input type and the op.
 """
+
 import multiprocessing
 import os
 import re
@@ -369,8 +370,9 @@ def test_cache_race_condition():
 
         # The module cache must (initially) be `None` for all processes so that
         # `ModuleCache.refresh` is called
-        with patch.object(compiledir_prop, "val", dir_name, create=True), patch.object(
-            pytensor.link.c.cmodule, "_module_cache", None
+        with (
+            patch.object(compiledir_prop, "val", dir_name, create=True),
+            patch.object(pytensor.link.c.cmodule, "_module_cache", None),
         ):
             assert pytensor.config.compiledir == dir_name
 

tests/scan/test_basic.py

 """
-  Questions and notes about scan that should be answered :
+Questions and notes about scan that should be answered :
 
-   * Scan seems to do copies of every input variable. Is that needed?
-   answer : probably not, but it doesn't hurt also ( what we copy is
-   pytensor variables, which just cary information about the type / dimension
-   of the data)
+ * Scan seems to do copies of every input variable. Is that needed?
+ answer : probably not, but it doesn't hurt also ( what we copy is
+ pytensor variables, which just cary information about the type / dimension
+ of the data)
 
-   * There is some of scan functionality that is not well documented
+ * There is some of scan functionality that is not well documented
 """
 
 import os

tests/tensor/conv/c_conv3d_corr3d_ref.py

@@ -160,13 +160,7 @@ class BaseCorr3dMM(OpenMPOp, _NoPythonOp):
     padD = property(lambda self: self.pad[2])
 
     def __str__(self):
-        return "{}{{{}, {}, {}, {}}}".format(
-            self.__class__.__name__,
-            self.border_mode,
-            str(self.subsample),
-            str(self.filter_dilation),
-            str(self.num_groups),
-        )
+        return f"{self.__class__.__name__}{{{self.border_mode}, {self.subsample!s}, {self.filter_dilation!s}, {self.num_groups!s}}}"
 
     @staticmethod
     def as_common_dtype(in1, in2):

tests/tensor/conv/c_conv_corr_ref.py

@@ -109,8 +109,8 @@ class BaseCorrMM(OpenMPOp, _NoPythonOp):
                     border += ((int(mode), int(mode)),)
                 else:
                     raise ValueError(
-                        "invalid border mode {}. The tuple can only contain "
-                        "integers or tuples of length 2".format(border_mode)
+                        f"invalid border mode {border_mode}. The tuple can only contain "
+                        "integers or tuples of length 2"
                     )
             border_mode = border
         elif border_mode not in ("valid", "full", "half"):
@@ -176,14 +176,7 @@ class BaseCorrMM(OpenMPOp, _NoPythonOp):
     padW_r = property(lambda self: self.pad[1][1])
 
     def __str__(self):
-        return "{}{{{}, {}, {}, {} {}}}".format(
-            self.__class__.__name__,
-            self.border_mode,
-            str(self.subsample),
-            str(self.filter_dilation),
-            str(self.num_groups),
-            str(self.unshared),
-        )
+        return f"{self.__class__.__name__}{{{self.border_mode}, {self.subsample!s}, {self.filter_dilation!s}, {self.num_groups!s} {self.unshared!s}}}"
 
     @staticmethod
     def as_common_dtype(in1, in2):

tests/tensor/test_basic.py

@@ -912,8 +912,9 @@ def test_infer_static_shape():
     with pytest.raises(TypeError, match="^Shapes must be scalar integers.*"):
         infer_static_shape([constant(1.0)])
 
-    with config.change_flags(exception_verbosity="high"), pytest.raises(
-        TypeError, match=r"A\. x"
+    with (
+        config.change_flags(exception_verbosity="high"),
+        pytest.raises(TypeError, match=r"A\. x"),
     ):
         infer_static_shape([dscalar("x")])
 

tests/tensor/test_type_other.py

-""" This file don't test everything. It only test one past crash error."""
+"""This file don't test everything. It only test one past crash error."""
 
 import pytensor
 from pytensor import as_symbolic

tests/tensor/utils.py

@@ -473,8 +473,9 @@ def makeTester(
                     f = inplace_func(inputrs, node.outputs, mode=mode, name="test_good")
                 except Exception as exc:
                     err_msg = (
-                        "Test {}::{}: Error occurred while" " trying to make a Function"
-                    ).format(self.op, testname)
+                        f"Test {self.op}::{testname}: Error occurred while"
+                        " trying to make a Function"
+                    )
                     exc.args += (err_msg,)
                     raise
                 if isinstance(self.expected, dict) and testname in self.expected:
@@ -513,29 +514,17 @@ def makeTester(
                         or not np.allclose(variable, expected, atol=eps, rtol=eps)
                     )
                     assert not condition, (
-                        "Test {}::{}: Output {} gave the wrong"
-                        " value. With inputs {}, expected {} (dtype {}),"
-                        " got {} (dtype {}). eps={:f}"
-                        " np.allclose returns {} {}"
-                    ).format(
-                        self.op,
-                        testname,
-                        i,
-                        inputs,
-                        expected,
-                        expected.dtype,
-                        variable,
-                        variable.dtype,
-                        eps,
-                        np.allclose(variable, expected, atol=eps, rtol=eps),
-                        np.allclose(variable, expected),
+                        f"Test {self.op}::{testname}: Output {i} gave the wrong"
+                        f" value. With inputs {inputs}, expected {expected} (dtype {expected.dtype}),"
+                        f" got {variable} (dtype {variable.dtype}). eps={eps:f}"
+                        f" np.allclose returns {np.allclose(variable, expected, atol=eps, rtol=eps)} {np.allclose(variable, expected)}"
                     )
 
                 for description, check in self.checks.items():
                     assert check(inputs, variables), (
-                        "Test {}::{}: Failed check: {} (inputs"
-                        " were {}, outputs were {})"
-                    ).format(self.op, testname, description, inputs, variables)
+                        f"Test {self.op}::{testname}: Failed check: {description} (inputs"
+                        f" were {inputs}, outputs were {variables})"
+                    )
 
         @pytest.mark.skipif(skip, reason="Skipped")
         def test_bad_build(self):
@@ -569,8 +558,9 @@ def makeTester(
                     )
                 except Exception as exc:
                     err_msg = (
-                        "Test {}::{}: Error occurred while trying" " to make a Function"
-                    ).format(self.op, testname)
+                        f"Test {self.op}::{testname}: Error occurred while trying"
+                        " to make a Function"
+                    )
                     exc.args += (err_msg,)
                     raise
 

tests/test_config.py

 """Test config options."""
+
 import configparser as stdlib_configparser
 import io
 import pickle

tests/test_printing.py

 """
 Tests of printing functionality
 """
+
 import logging
 from io import StringIO
 from textwrap import dedent

tests/test_rop.py

@@ -11,7 +11,6 @@ the docstring of the functions: check_mat_rop_lop, check_rop_lop,
 check_nondiff_rop,
 """
 
-
 import numpy as np
 import pytest