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Migrate executorch/ tests from exir.capture to torch.export + to_edge #18111

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Merged
meta-codesync merged 1 commit into from
Mar 13, 2026
+120 −1,645
Merged

Migrate executorch/ tests from exir.capture to torch.export + to_edge #18111

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32 changes: 0 additions & 32 deletions exir/backend/test/BUCK
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Original file line number Diff line number Diff line change
Expand Up @@ -158,38 +158,6 @@ fbcode_target(_kind = runtime.python_library,
],
)

fbcode_target(_kind = runtime.python_test,
name = "test_backends",
srcs = [
"test_backends.py",
],
preload_deps = [
"//executorch/configurations:optimized_native_cpu_ops",
"//executorch/kernels/quantized:custom_ops_generated_lib",
"//executorch/runtime/executor/test:test_backend_compiler_lib",
],
deps = [
":backend_with_compiler_demo",
":hta_partitioner_demo",
":op_partitioner_demo",
":demo_backend",
"//caffe2:torch",
"//caffe2/functorch:functorch_src",
"//executorch/exir:delegate",
"//executorch/exir:graph_module",
"//executorch/exir:lib",
"//executorch/exir:lowered_backend_module",
"//executorch/exir:print_program",
"//executorch/exir:schema",
"//executorch/exir/backend:backend_api",
"//executorch/exir/backend:compile_spec_schema",
"//executorch/exir/backend:partitioner",
"//executorch/exir/dialects:lib",
"//executorch/extension/pybindings:portable_lib", # @manual
"//executorch/extension/pytree:pylib",
],
)

fbcode_target(_kind = runtime.python_test,
name = "test_to_backend_multi_method",
srcs = [
Expand Down
85 changes: 22 additions & 63 deletions exir/backend/test/hta_partitioner_demo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@

import torch
from executorch import exir
from executorch.exir import to_edge
from executorch.exir.backend.canonical_partitioners.pattern_op_partitioner import (
generate_pattern_op_partitions,
)
Expand All @@ -20,7 +21,7 @@
)
from executorch.exir.backend.test.demo_backend import DemoBackend
from executorch.exir.backend.utils import tag_constant_data
from torch.export import ExportedProgram
from torch.export import export, ExportedProgram
from torch.fx.passes.infra.partitioner import Partition


Expand Down Expand Up @@ -63,56 +64,30 @@ def forward(self, x_raw, h, c):
input_h = torch.ones([1, 32])
input_c = torch.ones([1, 32])

pattern_lstm_conv_lifted = (
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(enable_aot=True),
)
.to_edge(
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
exir.EdgeCompileConfig(_check_ir_validity=False)
)
.exported_program.graph_module
)
pattern_lstm_conv = (
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(),
)
.to_edge(
to_edge(
export(LSTMConvPattern(), (input_x, input_h, input_c), strict=True),
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
exir.EdgeCompileConfig(_check_ir_validity=False)
compile_config=exir.EdgeCompileConfig(_check_ir_validity=False),
)
.exported_program.graph_module
.exported_program()
.graph_module
)

def sub(x, y):
return torch.sub(x, y)
class SubModule(torch.nn.Module):
def forward(self, x, y):
return torch.sub(x, y)

pattern_sub_lifted = (
exir.capture(
sub,
(input_x, input_h),
exir.CaptureConfig(enable_aot=True, _unlift=False),
)
.to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
.exported_program.graph_module
)
pattern_sub = (
exir.capture(
sub,
(input_x, input_h),
exir.CaptureConfig(),
to_edge(
export(SubModule(), (input_x, input_h), strict=True),
compile_config=exir.EdgeCompileConfig(_use_edge_ops=True),
)
.to_edge()
.exported_program.graph_module
.exported_program()
.graph_module
)
self.patterns = [
pattern_lstm_conv_lifted.graph,
pattern_lstm_conv.graph,
pattern_sub_lifted.graph,
pattern_sub.graph,
]

Expand Down Expand Up @@ -239,33 +214,17 @@ def forward(self, x_raw, h, c):
input_h = torch.ones([1, 32])
input_c = torch.ones([1, 32])

pattern_lstm_conv_lifted = (
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(enable_aot=True),
)
.to_edge(
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
exir.EdgeCompileConfig(_check_ir_validity=False)
)
.exported_program.graph_module
)
pattern_lstm_conv_unlifted = (
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(),
)
.to_edge(
pattern_lstm_conv = (
to_edge(
export(LSTMConvPattern(), (input_x, input_h, input_c), strict=True),
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
exir.EdgeCompileConfig(_check_ir_validity=False)
compile_config=exir.EdgeCompileConfig(_check_ir_validity=False),
)
.exported_program.graph_module
.exported_program()
.graph_module
)
self.patterns = [
pattern_lstm_conv_lifted.graph,
pattern_lstm_conv_unlifted.graph,
pattern_lstm_conv.graph,
]
# Only (lstm + conv) pattern is lowerable

Expand Down
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