[ROCm][CI] forward fix kineto submodule bump (#166421)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/166421
Approved by: https://github.com/jeffdaily

Co-authored-by: Jeff Daily <jeff.daily@amd.com>

test/dynamo/test_logging.py

@@ -892,10 +892,16 @@ fn(torch.randn(5))
                 os.remove(
                     file_path
                 )  # Delete temp file manually, due to setup NamedTemporaryFile as delete=False.
-                self.assertEqual(  # process wrap difference: /r/n on Windows, /n on posix.
-                    empty_line_normalizer(lines),
-                    empty_line_normalizer(stderr.decode("utf-8")),
-                )
+                orig_maxDiff = unittest.TestCase.maxDiff
+                unittest.TestCase.maxDiff = None
+                try:
+                    self.assertEqual(  # process wrap difference: /r/n on Windows, /n on posix.
+                        empty_line_normalizer(lines),
+                        empty_line_normalizer(stderr.decode("utf-8")),
+                    )
+                except Exception:
+                    unittest.TestCase.maxDiff = orig_maxDiff
+                    raise
 
     @make_settings_test("torch._dynamo.eval_frame")
     def test_log_traced_frames(self, records):

test/profiler/test_profiler.py

@@ -529,7 +529,7 @@ class TestProfiler(TestCase):
                 found_mm = True
             if "gemm" in e.name.lower() or "Cijk" in e.name:
                 found_gemm = True
-            if "memcpy" in e.name.lower():
+            if "memcpy" in e.name.lower() or "__amd_rocclr_copyBuffer" in e.name:
                 found_memcpy = True
         if use_cuda:
             self.assertTrue(found_gemm)

torch/_dynamo/config.py

@@ -445,7 +445,7 @@ use_numpy_random_stream = False
 enable_cpp_guard_manager = True
 
 # Use C++ guard manager for symbolic shapes
-enable_cpp_symbolic_shape_guards = False
+enable_cpp_symbolic_shape_guards = not is_fbcode()
 
 # Enable tracing through contextlib.contextmanager
 enable_trace_contextlib = True

torch/_inductor/scheduler.py

@@ -409,9 +409,10 @@ class SchedulerDonatedBuffer(SchedulerBuffer):
 
 
 class BaseSchedulerNode:
+    ancestors: OrderedSet[str]
+    debug_device_str: Callable[[BaseSchedulerNode], list[str]]
     group: tuple[torch.device, tuple[tuple[sympy.Expr, ...], ...]]
-    read_writes: dependencies.ReadWrites
-    unmet_dependencies: OrderedSet[Dep]
+    last_usage: OrderedSet[str]
     # .min_order and .max_order are only relevant for "grouped" nodes such as FusedSchedulerNode.
     # e.g. if the FusedSchedulerNode includes nodes (op_1, op_2, op_3), and op_X is X-th node
     # in `self.scheduler.nodes`, then for this FusedSchedulerNode, .min_order is 1 and .max_order is 3.
@@ -420,22 +421,24 @@ class BaseSchedulerNode:
     min_order: int
     max_order: int
     mpi_node: MemoryPlanningInfoForNode
+    mutation_renames: dict[str, str]
+    node: Optional[ir.Operation]
+    outputs: list[SchedulerBuffer]
+    outputs_by_name: dict[str, SchedulerBuffer]
     override_estimated_runtime: Optional[float] = None
+    read_writes: dependencies.ReadWrites
+    unmet_dependencies: OrderedSet[Dep]
 
     def __init__(self, scheduler: Scheduler) -> None:
-        self.scheduler: Scheduler = scheduler
-        self.debug_device_str: Callable[[BaseSchedulerNode], list[str]] = (
-            lambda *args, **kwargs: []
-        )
+        self.scheduler = scheduler
+        self.debug_device_str = lambda *args, **kwargs: []
 
     def _init_from_node(self, node: ir.Operation) -> None:
-        self.node: Optional[ir.Operation] = node
-        self.ancestors: OrderedSet[str] = OrderedSet()
-        self.last_usage = OrderedSet[
-            str
-        ]()  # buffers that won't be used after this kernel
+        self.node = node
+        self.ancestors = OrderedSet()
+        self.last_usage = OrderedSet()  # buffers that won't be used after this kernel
         self.written = False
-        self.outputs: list[SchedulerBuffer] = [
+        self.outputs = [
             SchedulerBuffer(
                 scheduler=self.scheduler,
                 node=output,
@@ -443,16 +446,14 @@ class BaseSchedulerNode:
             )
             for output in node.get_outputs()
         ]
-        self.outputs_by_name: dict[str, SchedulerBuffer] = {
-            buf.get_name(): buf for buf in self.outputs
-        }
+        self.outputs_by_name = {buf.get_name(): buf for buf in self.outputs}
 
         # mutation_renames for the current node. Due to potential
         # more mutations happening later, this can be different
         # to Scheduler.mutation_renames. Also this dict should be small
         # since only mutation information relevant to the deps for this
         # node is stored here.
-        self.mutation_renames: dict[str, str] = {}
+        self.mutation_renames = {}
 
     def __repr__(self) -> str:
         return f"{type(self).__name__}(name={self.get_name()!r})"
@@ -2435,6 +2436,34 @@ def pick_loop_order(
     return order
 
 
+def _replace_operation_buffer(
+    orig_node: ir.MultiTemplateBuffer, new_node: ir.OperationBuffer
+) -> None:
+    replaced_buf_name = new_node.get_name()
+    orig_buf_name = orig_node.get_name()
+    assert isinstance(orig_buf_name, str) and isinstance(replaced_buf_name, str)
+
+    replaced_op_name = new_node.get_operation_name()
+    orig_op_name = orig_node.get_operation_name()
+    assert isinstance(orig_op_name, str) and isinstance(replaced_op_name, str)
+
+    del V.graph.name_to_buffer[replaced_buf_name]
+    new_node.name = orig_buf_name
+
+    del V.graph.name_to_op[replaced_op_name]
+    new_node.operation_name = orig_op_name
+
+    orig = V.graph.buffers.index(orig_node)
+    V.graph.buffers.remove(new_node)
+    V.graph.buffers[orig] = new_node
+    V.graph.name_to_buffer[orig_buf_name] = new_node
+
+    orig = V.graph.operations.index(orig_node)
+    V.graph.operations.remove(new_node)
+    V.graph.operations[orig] = new_node
+    V.graph.name_to_op[orig_op_name] = new_node
+
+
 @dataclasses.dataclass
 class NodeUser:
     node: Union[BaseSchedulerNode, OutputNode]
@@ -3336,33 +3365,6 @@ class Scheduler:
         will force completion of compilation and benchmarking.
         """
 
-        def replace_operation_buffer(
-            orig_node: ir.MultiTemplateBuffer, new_node: ir.OperationBuffer
-        ) -> None:
-            replaced_buf_name = new_node.get_name()
-            orig_buf_name = orig_node.get_name()
-            assert isinstance(orig_buf_name, str) and isinstance(replaced_buf_name, str)
-
-            replaced_op_name = new_node.get_operation_name()
-            orig_op_name = orig_node.get_operation_name()
-            assert isinstance(orig_op_name, str) and isinstance(replaced_op_name, str)
-
-            del V.graph.name_to_buffer[replaced_buf_name]
-            new_node.name = orig_buf_name
-
-            del V.graph.name_to_op[replaced_op_name]
-            new_node.operation_name = orig_op_name
-
-            orig = V.graph.buffers.index(orig_node)
-            V.graph.buffers.remove(new_node)
-            V.graph.buffers[orig] = new_node
-            V.graph.name_to_buffer[orig_buf_name] = new_node
-
-            orig = V.graph.operations.index(orig_node)
-            V.graph.operations.remove(new_node)
-            V.graph.operations[orig] = new_node
-            V.graph.name_to_op[orig_op_name] = new_node
-
         for i, node in enumerate(self.nodes):
             if isinstance(node, SchedulerNode) and isinstance(
                 node.node, ir.MultiTemplateBuffer
@@ -3416,40 +3418,47 @@ class Scheduler:
                     assign_origin_node(out_tensorbox, multi_node.origin_node)
 
                 out_buffer.layout = multi_node.layout
-                replace_operation_buffer(multi_node, out_buffer)
-                new_scheduler_node = self.create_scheduler_node(out_buffer)
+                self._replace_node(out_buffer, multi_node, i, node)
 
-                self.nodes[i] = new_scheduler_node
-                self.name_to_node[node.get_name()] = new_scheduler_node
-                self.name_to_fused_node[node.get_name()] = new_scheduler_node
+    def _replace_node(
+        self,
+        out_buffer: ir.OperationBuffer,
+        multi_node: ir.MultiTemplateBuffer,
+        i: int,
+        node: SchedulerNode,
+    ) -> None:
+        _replace_operation_buffer(multi_node, out_buffer)
+        new_scheduler_node = self.create_scheduler_node(out_buffer)
 
-                # We need to reflect the mutation renames that were recorded in the original node
-                mutation_renames = {}
-                for dep in itertools.chain(
-                    node.read_writes.reads, node.unmet_dependencies
-                ):
-                    if real_name := self.mutation_real_name.get(dep.name, None):
-                        mutation_renames[real_name] = dep.name
+        self.nodes[i] = new_scheduler_node
+        self.name_to_node[node.get_name()] = new_scheduler_node
+        self.name_to_fused_node[node.get_name()] = new_scheduler_node
 
-                def rename_deps(deps: OrderedSet[Dep]) -> OrderedSet[Dep]:
-                    return OrderedSet(dep.rename(mutation_renames) for dep in deps)
+        # We need to reflect the mutation renames that were recorded in the original node
+        mutation_renames = {}
+        for dep in itertools.chain(node.read_writes.reads, node.unmet_dependencies):
+            if real_name := self.mutation_real_name.get(dep.name, None):
+                mutation_renames[real_name] = dep.name
 
-                new_scheduler_node.unmet_dependencies = rename_deps(
-                    new_scheduler_node.unmet_dependencies
-                )
-                new_scheduler_node.read_writes.reads = rename_deps(
-                    new_scheduler_node.read_writes.reads
-                )
+        def rename_deps(deps: OrderedSet[Dep]) -> OrderedSet[Dep]:
+            return OrderedSet(dep.rename(mutation_renames) for dep in deps)
 
-                for new_out, old_out in zip(
-                    new_scheduler_node.get_outputs(), node.get_outputs()
-                ):
-                    self.name_to_buf[old_out.get_name()] = new_out
-                    new_out.users = old_out.users
+        new_scheduler_node.unmet_dependencies = rename_deps(
+            new_scheduler_node.unmet_dependencies
+        )
+        new_scheduler_node.read_writes.reads = rename_deps(
+            new_scheduler_node.read_writes.reads
+        )
 
-                new_scheduler_node.min_order = node.min_order
-                new_scheduler_node.max_order = node.max_order
-                new_scheduler_node.last_usage = node.last_usage
+        for new_out, old_out in zip(
+            new_scheduler_node.get_outputs(), node.get_outputs()
+        ):
+            self.name_to_buf[old_out.get_name()] = new_out
+            new_out.users = old_out.users
+
+        new_scheduler_node.min_order = node.min_order
+        new_scheduler_node.max_order = node.max_order
+        new_scheduler_node.last_usage = node.last_usage
 
     def _any_atomic_add(self, node_list: Sequence[BaseSchedulerNode]) -> bool:
         return any(