Fix unused assignments (pytorch#166791)

This PR cleans up unused assignments.

Pull Request resolved: pytorch#166791
Approved by: https://github.com/xmfan

Author: cyyever

test/cpp_extensions/open_registration_extension/torch_openreg/tests/test_ops.py

@@ -246,7 +246,7 @@ def test_scaled_dot_product_fused_attention_overrideable_backward(self):
             max_k,
             philox_seed,
             philox_offset,
-            debug_attn_mask,
+            _debug_attn_mask,
         ) = torch.ops.aten._scaled_dot_product_fused_attention_overrideable(
             q_privateuse1, k_privateuse1, v_privateuse1, attn_bias=attn_mask_privateuse1
         )
@@ -256,25 +256,23 @@ def test_scaled_dot_product_fused_attention_overrideable_backward(self):
         )
         rand_upward_privateuse1 = rand_upward.to("openreg")
         grad_input_mask = [True, True, True, True]
-        grad_q, grad_k, grad_v, grad_attn_mask = (
-            torch.ops.aten._scaled_dot_product_fused_attention_overrideable_backward(
-                rand_upward_privateuse1,
-                q_privateuse1,
-                k_privateuse1,
-                v_privateuse1,
-                attn_mask_privateuse1,
-                grad_input_mask,
-                output,
-                logsumexp,
-                cum_seq_q,
-                cum_seq_k,
-                max_q,
-                max_k,
-                dropout_p=0.0,
-                is_causal=False,
-                philox_seed=philox_seed,
-                philox_offset=philox_offset,
-            )
+        torch.ops.aten._scaled_dot_product_fused_attention_overrideable_backward(
+            rand_upward_privateuse1,
+            q_privateuse1,
+            k_privateuse1,
+            v_privateuse1,
+            attn_mask_privateuse1,
+            grad_input_mask,
+            output,
+            logsumexp,
+            cum_seq_q,
+            cum_seq_k,
+            max_q,
+            max_k,
+            dropout_p=0.0,
+            is_causal=False,
+            philox_seed=philox_seed,
+            philox_offset=philox_offset,
         )
 
 

torch/_dynamo/compiled_autograd.py

@@ -755,7 +755,6 @@ def proxy_call(
         self, fn: Callable[..., Any], args: Any, output_metadata: Sequence[Any]
     ) -> Sequence[torch.Tensor]:
         """Proxies a call to fn(*args) into the graph"""
-        flat_args, _ = pytree.tree_flatten(args)
         proxy_args = pytree.tree_map(lambda e: self.to_proxy(e), args)
         proxy_out = self.fx_tracer.create_proxy(
             "call_function", fn, args=proxy_args, kwargs={}

torch/_dynamo/guards.py

@@ -2120,7 +2120,6 @@ def hooks_ids_fn(
             if not are_inline_hooks(hooks):
                 return None
 
-            pack_hook, unpack_hook = hooks
             return tuple(map(id, hooks))
 
         guard_hooks_ids = hooks_ids_fn(get_hooks())