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Move graph_builder and program_builder to executorch.backends.test (#18483) #18483

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953a860
cadence/aot: promote pre-set spec.mem_id to AbsolutePlacementConstrai…
Mar 25, 2026
851825d
Move graph_builder and program_builder to executorch.backends.test (#…
hsharma35 Mar 25, 2026
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56 changes: 34 additions & 22 deletions backends/cadence/aot/BUCK
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Original file line number Diff line number Diff line change
Expand Up @@ -226,8 +226,7 @@ fbcode_target(_kind = runtime.python_library,
],
typing = True,
deps = [
"fbcode//caffe2:torch",
"fbcode//executorch/exir:pass_base",
"//executorch/backends/test:graph_builder",
],
)

Expand All @@ -238,11 +237,7 @@ fbcode_target(_kind = runtime.python_library,
],
typing = True,
deps = [
":graph_builder",
"fbcode//caffe2:torch",
"fbcode//executorch/exir:lib",
"fbcode//executorch/exir:pass_base",
"fbcode//executorch/exir/verification:verifier",
"//executorch/backends/test:program_builder",
],
)

Expand All @@ -253,7 +248,7 @@ fbcode_target(_kind = python_unittest,
],
typing = True,
deps = [
":program_builder",
"//executorch/backends/test:program_builder",
"//caffe2:torch",
"//later:lib",
],
Expand Down Expand Up @@ -397,7 +392,7 @@ fbcode_target(_kind = python_unittest,
":typing_stubs",
":type_dispatch",
"//caffe2:torch",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/exir:pass_base",
"//executorch/exir/dialects:lib",
Expand Down Expand Up @@ -437,7 +432,7 @@ fbcode_target(_kind = python_unittest,
deps = [
":ops_registrations",
"//caffe2:torch",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/exir:pass_base",
"//executorch/exir/dialects:lib",
Expand All @@ -458,7 +453,7 @@ fbcode_target(_kind = python_unittest,
":replace_ops",
"//caffe2:torch",
"//executorch/backends/cadence/aot:compiler",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/exir:pass_base",
"//executorch/exir/dialects:lib",
Expand All @@ -479,7 +474,7 @@ fbcode_target(_kind = python_unittest,
"//caffe2:torch",
":typing_stubs",
"//executorch/backends/cadence/aot:compiler",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/exir:pass_base",
"//executorch/exir/dialects:lib",
Expand All @@ -500,7 +495,7 @@ fbcode_target(_kind = python_unittest,
"//caffe2:torch",
"//executorch/backends/cadence/aot:compiler",
"//executorch/backends/cadence/aot:fuse_ops",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:ops_registrations",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/exir/dialects:lib",
Expand All @@ -521,7 +516,7 @@ fbcode_target(_kind = python_unittest,
":compiler",
"//caffe2:torch",
"//executorch/backends/cadence/aot:compiler",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:ops_registrations",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/backends/cadence/aot:remove_ops",
Expand All @@ -541,7 +536,7 @@ fbcode_target(_kind = python_unittest,
":typing_stubs",
"//caffe2:torch",
"//executorch/backends/cadence/aot:compiler",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:ops_registrations",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/backends/cadence/aot:simplify_ops",
Expand All @@ -561,7 +556,7 @@ fbcode_target(_kind = python_unittest,
"//caffe2:torch",
"//executorch/backends/cadence/aot:compiler",
"//executorch/backends/cadence/aot:fuse_ops",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:ops_registrations",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/backends/cadence/aot:reorder_ops",
Expand All @@ -574,6 +569,7 @@ fbcode_target(_kind = runtime.python_library,
srcs = [
"memory_planning_algo.py",
],
typing = True,
deps = [
":memory_constraints",
":pass_utils",
Expand Down Expand Up @@ -618,6 +614,23 @@ fbcode_target(_kind = runtime.python_library,
],
)

fbcode_target(_kind = python_unittest,
name = "test_memory_planning_algo",
srcs = [
"tests/test_memory_planning_algo.py",
],
supports_static_listing = False,
typing = True,
deps = [
":memory_constraints",
":memory_planning",
":memory_planning_algo",
":utils",
"//caffe2:torch",
"//executorch/exir:tensor",
],
)

fbcode_target(_kind = python_unittest,
name = "test_memory_passes",
srcs = [
Expand All @@ -631,11 +644,11 @@ fbcode_target(_kind = python_unittest,
":typing_stubs",
":ops_registrations",
":pass_utils",
":program_builder",
"//executorch/backends/test:program_builder",
"//caffe2:torch",
"//executorch/exir:memory",
"//executorch/exir/dialects:lib",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/exir/tests:models",
],
)
Expand All @@ -647,8 +660,7 @@ fbcode_target(_kind = python_unittest,
],
typing = True,
deps = [
":program_builder",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot:ops_registrations",
"//executorch/runtime:runtime",
"//later:lib",
Expand Down Expand Up @@ -678,7 +690,7 @@ fbcode_target(_kind = python_unittest,
deps = [
"fbsource//third-party/pypi/parameterized:parameterized",
"//caffe2:torch",
"//executorch/backends/cadence/aot:graph_builder",
"//executorch/backends/test:graph_builder",
"//executorch/backends/cadence/aot/quantizer:quantizer",
"//executorch/exir:pass_base",
"//pytorch/ao:torchao",
Expand All @@ -693,7 +705,7 @@ fbcode_target(_kind = python_unittest,
typing = True,
deps = [
":ops_registrations",
":program_builder",
"//executorch/backends/test:program_builder",
":to_out_var_pass",
"//caffe2:torch",
"//executorch/exir:lib",
Expand Down
137 changes: 4 additions & 133 deletions backends/cadence/aot/graph_builder.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -6,137 +6,8 @@

# pyre-strict

import logging
from typing import Optional, Sequence, Union
# This module has moved to executorch.backends.test.graph_builder.
# This re-export exists for backward compatibility.
from executorch.backends.test.graph_builder import GraphBuilder, single_op_builder

import torch
from executorch.exir.pass_base import (
Argument,
ExportPass,
NodeMetadata,
PassResult,
ProxyValue,
)
from torch._dispatch.python import enable_python_dispatcher
from torch._subclasses import FakeTensor, FakeTensorMode
from torch.fx.node import Target
from torch.utils import _pytree as pytree


class GraphBuilder(ExportPass):
"""Utility class for creating a graph module with user-specified ops.

This class allows us to create test graph modules with any ops we want
directly, rather than relying on decomposition or passes.

Usage:
builder = GraphBuilder()
# To insert placeholders, use builder.placeholder.
x = builder.placeholder("x", torch.randn(1, 3, 224, 224))
# To insert an op, use builder.call_operator.
op = builder.call_operator(
some_op
(x, other_args, ...),
)
# Insert outputs as a list of ProxyValues using builder.output.
builder.output([op])
# Get GraphModule from builder.
gm = builder.get_graph_module()
"""

def __init__(self, fake_tensor_mode: Optional[FakeTensorMode] = None) -> None:
self.exporter = ExportPass()
self.tracer: ExportPass.ExportTracer = self.ExportTracer(
self, torch.fx.graph.CodeGen()
)
self.fake_tensor_mode: FakeTensorMode = fake_tensor_mode or FakeTensorMode(
allow_fallback_kernels=False,
allow_non_fake_inputs=True,
)
self.tracer.fake_tensor_mode = self.fake_tensor_mode

# This will be called to create nodes in tracer.
self.interpreter = torch.fx.Interpreter(
torch.fx.GraphModule(torch.nn.Module(), torch.fx.Graph())
)

# pyre-ignore[14]: Inconsistent override.
def placeholder(
self, target: str, fake_tensor: Union[FakeTensor, torch.Tensor]
) -> ProxyValue:
if not isinstance(fake_tensor, FakeTensor):
fake_tensor = self.fake_tensor_mode.from_tensor(fake_tensor)
logging.debug(f"Creating placeholder {target} => {fake_tensor.shape}")
placeholder = super().placeholder(target, fake_tensor, NodeMetadata({}))
return placeholder

# pyre-ignore[14]: Inconsistent override.
def output(self, results: list[ProxyValue]) -> ProxyValue:
logging.debug(f"Creating outputs {results}")
return super().output(results, NodeMetadata({}))

def get_graph_module(self) -> torch.fx.GraphModule:
return torch.fx.GraphModule(self.tracer.root, self.tracer.graph)

def call_operator(
self,
op, # pyre-ignore
args: tuple[Argument, ...],
kwargs: Optional[dict[str, Argument]] = None,
meta: Optional[NodeMetadata] = None,
) -> ProxyValue:
if meta is None:
meta = NodeMetadata({})
if kwargs is None:
kwargs = {}
return super().call_operator(op, args, kwargs, meta)

def call_submodule(
self, graph_module: torch.fx.GraphModule, inputs: tuple[Argument, ...]
) -> PassResult:
return ExportPass().call(graph_module)

def call_getitem(
self, value: ProxyValue, key: int, meta: Optional[NodeMetadata] = None
) -> ProxyValue:
return super().call_getitem(value, key, meta or NodeMetadata({}))

def _fx(
self,
kind: str,
target: torch.fx.node.Target,
args: tuple[Argument, ...],
kwargs: dict[str, Argument],
meta: NodeMetadata,
) -> ProxyValue:
with self.fake_tensor_mode, enable_python_dispatcher():
return super()._fx(kind, target, args, kwargs, meta)


def single_op_builder(
placeholders: Sequence[Union[torch.Tensor, FakeTensor]],
op: Target,
args: Sequence[Argument],
kwargs: Optional[dict[str, Argument]] = None,
) -> torch.fx.GraphModule:
"""Create a graph module with a single op.

Args:
placeholders: Placeholders to be used as inputs to the GraphModule.
op: The op to be inserted.
args: The args to be passed to the op.
kwargs: The kwargs to be passed to the op.

Returns:
A graph module with a single op
"""
builder = GraphBuilder()
op_to_placeholder_dict = {
p: builder.placeholder(f"p_{i}", p) for i, p in enumerate(placeholders)
}
proxy_args, proxy_kwargs = pytree.tree_map_only(
(torch.Tensor, FakeTensor), lambda x: op_to_placeholder_dict[x], (args, kwargs)
)
node = builder.call_operator(op, proxy_args, proxy_kwargs)
builder.output([node])
return builder.get_graph_module()
__all__ = ["GraphBuilder", "single_op_builder"]
11 changes: 11 additions & 0 deletions backends/cadence/aot/memory_constraints.py
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Original file line number Diff line number Diff line change
Expand Up @@ -324,6 +324,17 @@ def add_absolute_placement_constraint(
)
)

def set_absolute_placement_constraint(
self, spec: TensorSpec, constraint: AbsolutePlacementConstraint
) -> None:
"""Set an absolute placement constraint for `spec` by spec identity.

Overwrites any existing constraint for the same spec. Range validation
of pinned_memory_id is the caller's responsibility (depends on the
planner's MemoryConfig).
"""
self._absolute_placement_constraints[id(spec)] = constraint

def get_absolute_placement_constraint(
self, spec: TensorSpec
) -> Optional[AbsolutePlacementConstraint]:
Expand Down
34 changes: 34 additions & 0 deletions backends/cadence/aot/memory_planning_algo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -283,6 +283,40 @@ def plan_with_constraints(
) -> None:
"""Callable interface for ET memory planning."""

# Promote specs with a pre-set mem_id to AbsolutePlacementConstraint so
# the planner honours the pinned memory tier and only assigns the offset.
# This is used by planned-temporary alloc nodes whose spec.mem_id is set
# by the AOT pass before planning runs.
#
# mem_id semantics:
# None — not yet assigned (default); planner picks freely
# <= 0 — sentinel for "unassigned/unpinned"; planner picks freely
# [1, num_memories) — valid tier; promoted to constraint below
#
# Materialize to list because collect_specs_from_nodes returns a
# generator and we iterate twice (promotion here, constraint
# collection in spec_and_abs_constraints below).
specs = list(specs)
for spec in specs:
if (
spec.mem_id is not None
and isinstance(spec.mem_id, int)
and spec.mem_id > 0
and placement_constraints.get_absolute_placement_constraint(spec)
is None
):
num_memories = self.get_num_memories()
assert 1 <= spec.mem_id < num_memories, (
f"Pre-set spec.mem_id={spec.mem_id} is invalid. "
f"Memory IDs must be in range [1, {num_memories}) for this planner configuration. "
f"Check that the spec.mem_id was set correctly in the AOT pass, "
f"or verify your MemoryConfig defines enough memory tiers."
)
placement_constraints.set_absolute_placement_constraint(
spec,
AbsolutePlacementConstraint(pinned_memory_id=spec.mem_id),
)

spec_and_abs_constraints = {
spec: placement_constraints.get_absolute_placement_constraint(spec)
for spec in specs
Expand Down
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