fix: Remove input aliasing of builtin ops

py/torch_tensorrt/dynamo/backend/backends.py

@@ -2,17 +2,19 @@
 
 import logging
 import unittest
-from typing import Any, Callable, Dict, Optional, Sequence
+from typing import Any, Callable, Sequence
 
 import torch
 import torch._dynamo as td
-import torch.utils._pytree as pytree
 from torch._dynamo.utils import detect_fake_mode
-from torch._functorch.aot_autograd import _aot_export_function
-from torch._ops import OpOverload
+from torch._functorch.aot_autograd import aot_export_joint_simple
 from torch_tensorrt.dynamo import CompilationSettings
 from torch_tensorrt.dynamo.compile import compile_module
-from torch_tensorrt.dynamo.lowering import apply_lowering_passes, get_decompositions
+from torch_tensorrt.dynamo.lowering import (
+    apply_lowering_passes,
+    get_decompositions,
+    repair_input_aliasing,
+)
 from torch_tensorrt.dynamo.lowering._pre_aot_lowering import pre_aot_substitutions
 from torch_tensorrt.dynamo.utils import parse_dynamo_kwargs, set_log_level
 
@@ -71,10 +73,13 @@ def _pretraced_backend(
         with unittest.mock.patch.object(
             fake_mode, "allow_non_fake_inputs", True
         ), fake_mode:
+            repair_input_aliasing(gm)
+
             # Invoke AOTAutograd to translate operators to aten
-            gm = aot_export_for_compile(
+            gm = aot_export_joint_simple(
                 gm,
                 sample_inputs,
+                trace_joint=False,
                 decompositions=get_decompositions(
                     settings.enable_experimental_decompositions
                 ),
@@ -107,53 +112,3 @@ def _pretraced_backend(
                 + "specify pass_through_build_failures=False."
             )
             raise
-
-
-def aot_export_for_compile(
-    func: torch.fx.GraphModule,
-    args: Sequence[torch.Tensor],
-    *,
-    decompositions: Optional[Dict[OpOverload, Callable[[Any], Any]]] = None,
-) -> torch.fx.GraphModule:
-    """Adapted from:
-    https://github.com/pytorch/pytorch/blob/1a5fdc2458b98697c75c32eb6f4b8b34d76429cf/torch/_functorch/aot_autograd.py#L4084-L4158
-
-    Removed check for input aliasing in resultant subgraph - TRT is functional-only
-
-    Exports the function to ATen for torch compile
-    """
-    # Trace function with input arguments and decompositions
-    with torch.no_grad():
-        fx_g, metadata, in_spec, out_spec = _aot_export_function(
-            func,
-            args,
-            decompositions=decompositions,
-        )
-
-    # No input mutations
-    if (
-        len([x for x in metadata.input_info if x.mutates_data or x.mutates_metadata])
-        != 0
-    ):
-        raise RuntimeError(
-            f"aot_export_joint_simple does not support input mutations. {str(metadata)}"
-        )
-    # No pytrees
-    if type(in_spec) == pytree.LeafSpec:
-        raise RuntimeError(
-            f"aot_export_for_compile requires inputs to be a single list/tuple. in_spec={str(in_spec)}"
-        )
-    if len([x for x in in_spec.children_specs if type(x) != pytree.LeafSpec]) != 0:
-        raise RuntimeError(
-            f"aot_export_for_compile requires individual inputs not to be pytrees. in_spec={str(in_spec)}"
-        )
-    if type(out_spec) == pytree.LeafSpec:
-        raise RuntimeError(
-            f"aot_export_for_compile requires outputs to be a single list/tuple. out_spec={str(out_spec)}"
-        )
-    if len([x for x in out_spec.children_specs if type(x) != pytree.LeafSpec]) != 0:
-        raise RuntimeError(
-            f"aot_export_for_compile requires individual outputs not to be pytrees. out_spec={str(out_spec)}"
-        )
-
-    return fx_g

py/torch_tensorrt/dynamo/lowering/__init__.py

@@ -2,5 +2,6 @@
 from ._fusers import *  # noqa: F401
 from ._pre_aot_lowering import SUBSTITUTION_REGISTRY  # noqa: F401
 from ._pre_aot_lowering import register_substitution  # noqa: F401
+from ._repair_input_aliasing import repair_input_aliasing
 from .passes import apply_lowering_passes
 from .substitutions import *  # noqa: F401

py/torch_tensorrt/dynamo/lowering/_repair_input_aliasing.py

@@ -0,0 +1,38 @@
+import logging
+
+import torch
+from torch_tensorrt.dynamo.lowering.passes.pass_utils import get_tensor_placeholders
+
+logger = logging.getLogger(__name__)
+
+
+def repair_input_aliasing(gm: torch.fx.GraphModule) -> torch.fx.GraphModule:
+    """Inserts clone operators temporarily ahead of every placeholder
+
+    See: https://github.com/pytorch/pytorch/issues/108079
+    Undone by `remove_input_alias_fixing_clones` after tracing
+    """
+    # Extract graph placeholder Tensors
+    placeholders = get_tensor_placeholders(gm)
+
+    for node in placeholders:
+        # Insert clones for placeholder nodes to avoid
+        # input aliasing or mutation
+        with gm.graph.inserting_after(placeholders[-1]):
+            cloned_input = gm.graph.call_function(
+                torch.ops.aten.clone.default,
+                args=(node,),
+            )
+
+        # Replace all uses of the placeholder except the cloned node
+        # with the cloned placeholder
+        node.replace_all_uses_with(
+            cloned_input,
+            delete_user_cb=lambda node: node != cloned_input,
+        )
+
+    gm.graph.lint()
+    gm.recompile()
+    logger.debug(f"Inserted auxiliary clone nodes for placeholders:\n{gm.graph}")
+
+    return gm

py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py

@@ -5,10 +5,12 @@
 
 from .constant_folding import constant_fold
 from .pass_manager import DynamoPassManager
+from .remove_input_alias_fixing_clones import remove_input_alias_fixing_clones
 from .repair_input_as_output import repair_input_as_output
 
 ATEN_LOWERING_PASSES = DynamoPassManager.build_from_passlist(
     [
+        remove_input_alias_fixing_clones,
         constant_fold,
         repair_input_as_output,
     ]

py/torch_tensorrt/dynamo/lowering/passes/constant_folding.py

@@ -2,6 +2,9 @@
 
 import torch
 from torch_tensorrt._utils import sanitized_torch_version
+from torch_tensorrt.dynamo.lowering.passes.pass_utils import (
+    clean_up_graph_after_modifications,
+)
 
 from packaging import version
 
@@ -47,9 +50,7 @@ def constant_fold(gm: torch.fx.GraphModule) -> torch.fx.GraphModule:
     for node in erased_params:
         gm.graph.erase_node(node)
 
-    gm.graph.eliminate_dead_code()
-    gm.graph.lint()
-    gm.recompile()
+    gm = clean_up_graph_after_modifications(gm)
 
     logger.debug(f"Graph after constant folding:\n{gm.graph}")
 

py/torch_tensorrt/dynamo/lowering/passes/pass_utils.py

@@ -0,0 +1,31 @@
+from typing import List
+
+import torch
+
+
+def clean_up_graph_after_modifications(
+    gm: torch.fx.GraphModule,
+) -> torch.fx.GraphModule:
+    """Runs dead-code elimination, linting, and recompilation for graph, in-place"""
+    gm.graph.eliminate_dead_code()
+    gm.graph.lint()
+    gm.recompile()
+    return gm
+
+
+def get_tensor_placeholders(
+    gm: torch.fx.GraphModule,
+) -> List[torch.fx.Node]:
+    """Returns placeholder nodes of GraphModule which are torch.Tensor types"""
+    # Tensor placeholders must be subclasses of torch.Tensor
+    placeholders = [
+        node
+        for node in gm.graph.nodes
+        if (
+            node.op == "placeholder"
+            and isinstance(node.type, type)
+            and issubclass(node.type, torch.Tensor)
+        )
+    ]
+
+    return placeholders

py/torch_tensorrt/dynamo/lowering/passes/remove_input_alias_fixing_clones.py

@@ -0,0 +1,43 @@
+import logging
+
+import torch
+from torch_tensorrt.dynamo.lowering.passes.pass_utils import (
+    clean_up_graph_after_modifications,
+)
+
+logger = logging.getLogger(__name__)
+
+
+# TODO: Delete this lowering pass once aot_export_joint_simple is patched
+def remove_input_alias_fixing_clones(gm: torch.fx.GraphModule) -> torch.fx.GraphModule:
+    """Remove the auxiliary clone nodes inserted to fix input aliasing
+
+    See: https://github.com/pytorch/pytorch/issues/108079
+    """
+    modified_graph = False
+
+    for node in gm.graph.nodes:
+        # If the node is a placeholder and its only user is a clone node
+        # it was modified by the input alias-fixing pass, and the change
+        # needs to be undone
+        if (
+            node.op == "placeholder"
+            and len(node.users) == 1
+            and list(node.users)[0].target == torch.ops.aten.clone.default
+        ):
+            modified_graph = True
+
+            # Replace all uses of the clone with the placholder, delete the clone
+            clone_node = list(node.users)[0]
+            logger.debug(
+                f"Removing node {clone_node} from graph, since it is a clone node which "
+                f"is the only user of placeholder {node} and was inserted by the compiler."
+            )
+            clone_node.replace_all_uses_with(node)
+            gm.graph.erase_node(clone_node)
+
+    if modified_graph:
+        gm = clean_up_graph_after_modifications(gm)
+        logger.debug(f"Removed auxiliary clone nodes for placeholders:\n{gm.graph}")
+
+    return gm

py/torch_tensorrt/dynamo/lowering/passes/repair_input_as_output.py

@@ -1,6 +1,10 @@
 import logging
 
 import torch
+from torch_tensorrt.dynamo.lowering.passes.pass_utils import (
+    clean_up_graph_after_modifications,
+    get_tensor_placeholders,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -13,15 +17,7 @@ def repair_input_as_output(gm: torch.fx.GraphModule) -> torch.fx.GraphModule:
     modified_graph = False
 
     # Extract graph placeholder Tensors
-    placeholders = [
-        node
-        for node in gm.graph.nodes
-        if (
-            node.op == "placeholder"
-            and isinstance(node.type, type)
-            and issubclass(node.type, torch.Tensor)
-        )
-    ]
+    placeholders = get_tensor_placeholders(gm)
 
     for placeholder in placeholders:
         # If any placeholder has any users which are direct graph outputs
@@ -34,7 +30,7 @@ def repair_input_as_output(gm: torch.fx.GraphModule) -> torch.fx.GraphModule:
             direct_outputs = [user for user in placeholder.users if user.op == "output"]
 
             # Insert clone node for placeholder to ensure placeholder is not a direct output
-            with gm.graph.inserting_after(placeholder):
+            with gm.graph.inserting_after(placeholders[-1]):
                 cloned_placeholder = gm.graph.call_function(
                     torch.ops.aten.clone.default,
                     args=(placeholder,),
@@ -45,9 +41,7 @@ def repair_input_as_output(gm: torch.fx.GraphModule) -> torch.fx.GraphModule:
                 output.replace_input_with(placeholder, cloned_placeholder)
 
     if modified_graph:
-        gm.graph.eliminate_dead_code()
-        gm.graph.lint()
-        gm.recompile()
+        gm = clean_up_graph_after_modifications(gm)
         logger.debug(f"Graph after repair_input_as_output:\n{gm.graph}")
 
     return gm