diff --git a/torch/_inductor/codegen/wrapper.py b/torch/_inductor/codegen/wrapper.py
index 5fedc0cb99ca..d76f943fde25 100644
--- a/torch/_inductor/codegen/wrapper.py
+++ b/torch/_inductor/codegen/wrapper.py
@@ -1078,7 +1078,7 @@ class PythonWrapperCodegen(CodeGen):
             arg.get_dtype() if isinstance(arg, IRNode) else type(arg)
             for arg in raw_args
         ]
-        # Because generate_kernel_call can be overriden by a subclass, explictly call
+        # Because generate_kernel_call can be overriden by a subclass, explicitly call
         # PythonWrapperCodegen.generate_kernel_call here
         PythonWrapperCodegen.generate_kernel_call(
             self,
@@ -2376,7 +2376,7 @@ class PythonWrapperCodegen(CodeGen):
 
     def codegen_subgraph_prefix(self, subgraph, outer_inputs, outer_outputs):
         # All inputs of hops must be explicitly passed in.
-        # Free tensors and basic symbols should have been explictily lifted as inputs in dynamo.
+        # Free tensors and basic symbols should have been explicitly lifted as inputs in dynamo.
         assert len(outer_inputs) == len(
             subgraph.graph.graph_input_names
         ), f"graph_input_names:{subgraph.graph.graph_input_names}, outer_inputs: {outer_inputs}"
diff --git a/torch/csrc/jit/python/pybind_utils.h b/torch/csrc/jit/python/pybind_utils.h
index 4c108904cc58..273c6acd49ce 100644
--- a/torch/csrc/jit/python/pybind_utils.h
+++ b/torch/csrc/jit/python/pybind_utils.h
@@ -691,7 +691,7 @@ inline IValue toTypeInferredIValue(py::handle input) {
     if (auto mod = as_module(object)) {
       // if obj is already a ScriptModule, just return its ivalue
       auto ptr = mod.value()._ivalue();
-      // explict copy semantics for strong ownership of the resource.
+      // explicit copy semantics for strong ownership of the resource.
       return c10::intrusive_ptr<c10::ivalue::Object>::reclaim_copy(
           ptr.release());
     }
diff --git a/torch/distributed/distributed_c10d.py b/torch/distributed/distributed_c10d.py
index 1b0442c15423..ff89dd79f2d0 100644
--- a/torch/distributed/distributed_c10d.py
+++ b/torch/distributed/distributed_c10d.py
@@ -1811,7 +1811,7 @@ def _shutdown_backend(pg):
     except RuntimeError:
         pass
     if is_nccl_available() and isinstance(backend, ProcessGroupNCCL):
-        # explictly call shutdown to ensure that NCCL resources are released
+        # explicitly call shutdown to ensure that NCCL resources are released
         backend._shutdown()
 
 
diff --git a/torch/distributed/pipelining/_backward.py b/torch/distributed/pipelining/_backward.py
index e2eebf49ad77..a31ee53206ab 100644
--- a/torch/distributed/pipelining/_backward.py
+++ b/torch/distributed/pipelining/_backward.py
@@ -344,7 +344,7 @@ def stage_backward(
         # 2. extract_tensors_with_grads referred to both stage_output_tensors, output_grad_tensors,
         #    and to itself (extract_tensors_with_grads) since it makes a recursive call
         # 3. stage_output_tensors was kept alive by the above refcycle, and it holds activation tensors, which is bad
-        # fix -> explictly pass in the ref to the fn, so there is no gc cycle anymore
+        # fix -> explicitly pass in the ref to the fn, so there is no gc cycle anymore
         extract_tensors_with_grads(
             stage_output, output_grads, extract_tensors_with_grads
         )
diff --git a/torchgen/gen_aoti_c_shim.py b/torchgen/gen_aoti_c_shim.py
index 9846de77b430..da4abab91c83 100644
--- a/torchgen/gen_aoti_c_shim.py
+++ b/torchgen/gen_aoti_c_shim.py
@@ -142,7 +142,7 @@ def convert_arg_type_and_name(  # type: ignore[return]
             new_callsite_exprs,
         )
     elif isinstance(typ, ListType):
-        # Need to explictly pass the list as pointer + length
+        # Need to explicitly pass the list as pointer + length
         c_types, names, aten_types, _ = convert_arg_type_and_name(typ.elem, name)
         assert len(c_types) == 1, "ListType with unsupported element type " + repr(typ)