[6/N] Remove unused loop variables in tests (#166785)

cyyever · pytorchmergebot · commit 392acee68a5c · 2025-11-03T03:52:52.000Z
This PR removes unused loop variables in tests. Pull Request resolved: #166785 Approved by: https://github.com/Skylion007, https://github.com/mlazos
diff --git a/test/distributed/_composable/fsdp/test_fully_shard_state_dict.py b/test/distributed/_composable/fsdp/test_fully_shard_state_dict.py
@@ -438,8 +438,8 @@ def test_rank0_offload_full_state_dict(self):
         if self.rank == 0:
             self.assertEqual(len(full_sd), len(ref_full_sd))
             self.assertEqual(list(full_sd.keys()), list(ref_full_sd.keys()))
-            for (param_name, param), ref_param in zip(
-                full_sd.items(), ref_full_sd.values()
+            for param, ref_param in zip(
+                full_sd.values(), ref_full_sd.values(), strict=True
             ):
                 self.assertEqual(param.device, torch.device("cpu"))
                 self.assertEqual(param.device, ref_param.device)
diff --git a/test/distributed/fsdp/test_checkpoint_wrapper.py b/test/distributed/fsdp/test_checkpoint_wrapper.py
@@ -303,7 +303,7 @@ def check_fn(l):
                     )
 
                 inp = torch.randn(4, 10, requires_grad=True)
-                for i in range(6):
+                for _ in range(6):
                     # Kwarg input
                     loss = model(x=inp).sum()
                     self.assertTrue(loss.requires_grad)
diff --git a/test/distributed/test_c10d_ops_nccl.py b/test/distributed/test_c10d_ops_nccl.py
@@ -278,7 +278,7 @@ def test_alltoall_ops_with_cudafree_race(self):
                 tmp.append(torch.rand(10 ** (3 + i), device=local_device))
             race_tensors.append(tmp)
 
-        for i in range(10):
+        for _ in range(10):
             race_tensors.pop()
             work = pg.alltoall_base(output, input, [], [], opts)
             # this triggers cudaFree
diff --git a/test/dynamo/test_subgraphs.py b/test/dynamo/test_subgraphs.py
@@ -580,7 +580,7 @@ def fn(x, it):
 
     def test_enumerate_not_break_graph(self):
         def fn(a, b):
-            for i, x in enumerate(a.shape):
+            for _, x in enumerate(a.shape):
                 b = b + x
             for i, x in enumerate(b.shape, 8):
                 b = b + x * i
diff --git a/test/functorch/test_control_flow.py b/test/functorch/test_control_flow.py
@@ -742,7 +742,7 @@ def forward(self, pred_1, x_1):
 
     def test_cond_in_forloop(self):
         def for_loop_fake(x):
-            for i in range(3):
+            for _ in range(3):
                 x = x * x + 1
             return x
 
diff --git a/test/inductor/test_compile_worker.py b/test/inductor/test_compile_worker.py
@@ -104,7 +104,7 @@ def doit():
 
         t = Timer(0.1, doit)
         t.sleep_time = 0.1
-        for i in range(10):
+        for _ in range(10):
             t.record_call()
             self.assertTrue(done.wait(4))
             done.clear()
@@ -130,7 +130,7 @@ def doit():
 
         t = Timer(1, doit)
         t.sleep_time = 0.1
-        for i in range(400):
+        for _ in range(400):
             t.record_call()
         self.assertTrue(done.wait(4))
         t.quit()
diff --git a/test/jit/test_module_containers.py b/test/jit/test_module_containers.py
@@ -300,7 +300,7 @@ def forward(self, inputs):
 
                 # note: unable to index moduledict with a string variable currently
                 i = 0
-                for key in self.moduledict:
+                for _ in self.moduledict:
                     i += 1
                 assert i == len(self.moduledict), "iteration failing for ModuleDict"
 
diff --git a/test/profiler/test_profiler.py b/test/profiler/test_profiler.py
@@ -2124,7 +2124,7 @@ def test_cpu_annotation_overlap(self):
                 adjust_profiler_step=True
             ),
         ) as prof:
-            for i in range(5):
+            for _ in range(5):
                 self._step_helper_func(prof)
         with TemporaryFileName(mode="w+") as fname:
             prof.export_chrome_trace(fname)
diff --git a/test/quantization/fx/test_quantize_fx.py b/test/quantization/fx/test_quantize_fx.py
@@ -9435,7 +9435,7 @@ def _test_model_impl(
             criterion = nn.CrossEntropyLoss()
             train_one_epoch(prepared, criterion, optimizer, [(input_value, output_value)], torch.device('cpu'), 1)
         else:
-            for i in range(10):
+            for _ in range(10):
                 prepared(input_value)
 
         # print('after observation root:', prepared.root)
@@ -9480,7 +9480,7 @@ def _test_model_impl(
                 optimizer = torch.optim.SGD(qeager.parameters(), lr=0.0001)
                 train_one_epoch(qeager, criterion, optimizer, [(input_value, output_value)], torch.device('cpu'), 1)
             else:
-                for i in range(10):
+                for _ in range(10):
                     qeager(input_value)
 
             # print('ref after observation:', qeager)
diff --git a/test/test_fx_experimental.py b/test/test_fx_experimental.py
@@ -272,7 +272,7 @@ def forward(self, a, b, offset):
                 x = self.bottom_layers(a)
                 y = []
                 c = []
-                for i in range(len(self.embedding_layers)):
+                for _ in range(len(self.embedding_layers)):
                     temp = torch.randint(10, (8,))
                     c.append(temp + b)
                 for i in range(len(self.embedding_layers)):
diff --git a/test/test_linalg.py b/test/test_linalg.py
@@ -7133,7 +7133,7 @@ def tracker(worker):
         elapsed_ortho_general = 0
         elapsed_scipy = 0
         elapsed_general_scipy = 0
-        for i in range(repeat):
+        for _ in range(repeat):
             start = time.time()
             torch.lobpcg(A1, X=X1, niter=niter, method='ortho', tol=tol)
             end = time.time()
@@ -8769,7 +8769,7 @@ def run_test(*n):
 
             num_matrices = tensors_batch.size(0)
             tensors_list = []
-            for i in range(num_matrices):
+            for _ in range(num_matrices):
                 tensors_list.append(torch.randn(n[-2], n[-1], dtype=dtype, device=device))
 
             for i in range(num_matrices):

Original file line number	Diff line number	Diff line change
`@@ -303,7 +303,7 @@ def check_fn(l):`
`303`	`303`	`)`
`304`	`304`
`305`	`305`	`inp = torch.randn(4, 10, requires_grad=True)`
`306`		`- for i in range(6):`
	`306`	`+ for _ in range(6):`
`307`	`307`	`# Kwarg input`
`308`	`308`	`loss = model(x=inp).sum()`
`309`	`309`	`self.assertTrue(loss.requires_grad)`