[BE]: Merge startswith calls - rule PIE810 (#96754)

Merges startswith, endswith calls to into a single call that feeds in a tuple. Not only are these calls more readable, but it will be more efficient as it iterates through each string only once.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/96754
Approved by: https://github.com/ezyang

caffe2/python/memonger.py

@@ -41,8 +41,7 @@ def share_grad_blobs(
         name = str(b)
         # Note: need to look at _{namescope} pattern as it matches
         # to handle the auto-split gradients
-        return name.endswith("_grad") and (name.startswith(namescope) or
+        return name.endswith("_grad") and (name.startswith((namescope, "_" + namescope))) and name not in param_grads
-            name.startswith("_" + namescope)) and name not in param_grads
 
     def is_grad_op(op):
         # TODO: something smarter

scripts/release_notes/commitlist.py

@@ -199,7 +199,7 @@ class CommitList:
         else:
             # Below are some extra quick checks that aren't necessarily file-path related,
             # but I found that to catch a decent number of extra commits.
-            if len(files_changed) > 0 and all([f_name.endswith('.cu') or f_name.endswith('.cuh') for f_name in files_changed]):
+            if len(files_changed) > 0 and all([f_name.endswith(('.cu', '.cuh')) for f_name in files_changed]):
                 category = 'cuda'
             elif '[PyTorch Edge]' in title:
                 category = 'mobile'

test/cpp_api_parity/module_impl_check.py

@@ -172,7 +172,7 @@ def test_forward_backward(unit_test_class, test_params):
                     param_name = key[:-len(suffix)]
                     break
             assert param_name is not None
-            sparsity_str = 'sparse' if key.endswith('_grad_indices') or key.endswith('_grad_values') else 'dense'
+            sparsity_str = 'sparse' if key.endswith(('_grad_indices', '_grad_values')) else 'dense'
 
             unit_test_class.assertTrue(
                 key in cpp_grad_dict,

test/distributed/_tensor/test_api.py

@@ -161,7 +161,7 @@ class DTensorAPITest(DTensorTestBase):
         dist_module = distribute_module(module_to_distribute, device_mesh, shard_fn)
         for name, param in dist_module.named_parameters():
             self.assertIsInstance(param, DTensor)
-            if name.startswith("seq.0") or name.startswith("seq.8"):
+            if name.startswith(("seq.0", "seq.8")):
                 self.assertEqual(param.placements, shard_spec)
             else:
                 self.assertEqual(param.placements, replica_spec)

tools/linter/adapters/testowners_linter.py

@@ -80,11 +80,7 @@ def check_labels(
                 )
             )
 
-        if (
+        if label.startswith(("module:", "oncall:")) or label in ACCEPTABLE_OWNER_LABELS:
-            label.startswith("module:")
-            or label.startswith("oncall:")
-            or label in ACCEPTABLE_OWNER_LABELS
-        ):
             continue
 
         lint_messages.append(

torch/onnx/errors.py

@@ -53,11 +53,7 @@ class UnsupportedOperatorError(OnnxExporterError):
             msg = diagnostic_rule.format_message(name, version, supported_version)
             diagnostics.diagnose(diagnostic_rule, diagnostics.levels.ERROR, msg)
         else:
-            if (
+            if name.startswith(("aten::", "prim::", "quantized::")):
-                name.startswith("aten::")
-                or name.startswith("prim::")
-                or name.startswith("quantized::")
-            ):
                 diagnostic_rule = diagnostics.rules.missing_standard_symbolic_function
                 msg = diagnostic_rule.format_message(
                     name, version, _constants.PYTORCH_GITHUB_ISSUES_URL

torch/onnx/utils.py

@@ -1352,7 +1352,7 @@ def unconvertible_ops(
     unsupported_ops = []
     for node in graph.nodes():
         domain_op = node.kind()
-        if domain_op.startswith("onnx::") or domain_op.startswith("prim::"):
+        if domain_op.startswith(("onnx::", "prim::")):
             # We consider onnx and prim ops as supported ops, even though some "prim"
             # ops are not implemented as symbolic functions, because they may be
             # eliminated in the conversion passes. Users may still see errors caused
@@ -1455,7 +1455,6 @@ def _reset_trace_module_map():
 
 @_beartype.beartype
 def _get_module_attributes(module):
-
     annotations = typing.get_type_hints(type(module))
     base_m_annotations = typing.get_type_hints(torch.nn.Module)
     [annotations.pop(k, None) for k in base_m_annotations]
@@ -1800,7 +1799,6 @@ def _need_symbolic_context(symbolic_fn: Callable) -> bool:
 def _symbolic_context_handler(symbolic_fn: Callable) -> Callable:
     """Decorator that provides the symbolic context to the symbolic function if needed."""
     if _need_symbolic_context(symbolic_fn):
-
         # TODO(justinchuby): Update the module name of GraphContext when it is public
         warnings.warn(
             "The first argument to symbolic functions is deprecated in 1.13 and will be "
@@ -1824,7 +1822,6 @@ def _symbolic_context_handler(symbolic_fn: Callable) -> Callable:
 
 @_beartype.beartype
 def _get_aten_op_overload_name(n: _C.Node) -> str:
-
     # Returns `overload_name` attribute to ATen ops on non-Caffe2 builds
     schema = n.schema()
     if not schema.startswith("aten::") or symbolic_helper.is_caffe2_aten_fallback():

torch/testing/_internal/check_kernel_launches.py

@@ -107,7 +107,7 @@ def check_file(filename):
     Returns:
         The number of unsafe kernel launches in the file
     """
-    if not (filename.endswith(".cu") or filename.endswith(".cuh")):
+    if not (filename.endswith((".cu", ".cuh"))):
         return 0
     if should_exclude_file(filename):
         return 0

torch/testing/_internal/common_device_type.py

@@ -957,7 +957,7 @@ def largeTensorTest(size, device=None):
     In other tests, the `device=` argument needs to be specified.
     """
     if isinstance(size, str):
-        assert size.endswith("GB") or size.endswith("gb"), "only bytes or GB supported"
+        assert size.endswith(('GB', 'gb')), "only bytes or GB supported"
         size = 1024 ** 3 * int(size[:-2])
 
     def inner(fn):

torch/utils/cpp_extension.py

@@ -552,7 +552,7 @@ class BuildExtension(build_ext):
             _ccbin = os.getenv("CC")
             if (
                 _ccbin is not None
-                and not any([flag.startswith('-ccbin') or flag.startswith('--compiler-bindir') for flag in cflags])
+                and not any([flag.startswith(('-ccbin', '--compiler-bindir')) for flag in cflags])
             ):
                 cflags.extend(['-ccbin', _ccbin])
 

torch/utils/hipify/hipify_python.py

@@ -799,14 +799,14 @@ def preprocessor(
             f = m.group(1)
             dirpath, filename = os.path.split(f)
             if (
-                f.startswith("ATen/cuda")
+                f.startswith(("ATen/cuda",
-                or f.startswith("ATen/native/cuda")
+                              "ATen/native/cuda",
-                or f.startswith("ATen/native/nested/cuda")
+                              "ATen/native/nested/cuda",
-                or f.startswith("ATen/native/quantized/cuda")
+                              "ATen/native/quantized/cuda",
-                or f.startswith("ATen/native/sparse/cuda")
+                              "ATen/native/sparse/cuda",
-                or f.startswith("ATen/native/transformers/cuda")
+                              "ATen/native/transformers/cuda",
-                or f.startswith("THC/")
+                              "THC/")) or
-                or (f.startswith("THC") and not f.startswith("THCP"))
+                (f.startswith("THC") and not f.startswith("THCP"))
             ):
                 return templ.format(get_hip_file_path(m.group(1), is_pytorch_extension))
             # if filename is one of the files being hipified for this extension
@@ -858,7 +858,7 @@ def preprocessor(
         output_source = processKernelLaunches(output_source, stats)
 
     # Replace std:: with non-std:: versions
-    if (filepath.endswith(".cu") or filepath.endswith(".cuh")) and "PowKernel" not in filepath:
+    if (filepath.endswith((".cu", ".cuh"))) and "PowKernel" not in filepath:
         output_source = replace_math_functions(output_source)
 
     # Include header if device code is contained.

torch/utils/model_dump/__init__.py

@@ -123,9 +123,7 @@ def hierarchical_pickle(data):
     if isinstance(data, torch.utils.show_pickle.FakeObject):
         typename = f"{data.module}.{data.name}"
         if (
-            typename.startswith("__torch__.") or
+            typename.startswith(('__torch__.', 'torch.jit.LoweredWrapper.', 'torch.jit.LoweredModule.'))
-            typename.startswith("torch.jit.LoweredWrapper.") or
-            typename.startswith("torch.jit.LoweredModule.")
         ):
             assert data.args == ()
             return {