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Add small repro test for unsigned -> signed et loss error #8506

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Merged
merged 1 commit into from
Feb 19, 2025
Merged

Add small repro test for unsigned -> signed et loss error #8506

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1 change: 1 addition & 0 deletions backends/cadence/aot/TARGETS
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Original file line number Diff line number Diff line change
Expand Up @@ -180,6 +180,7 @@ python_library(
typing = True,
deps = [
"//caffe2:torch",
":ops_registrations",
":compiler_utils",
"//executorch/backends/cadence/aot:pass_utils",
"//executorch/backends/cadence/aot:utils",
Expand Down
8 changes: 7 additions & 1 deletion backends/cadence/aot/fuse_ops.py
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Expand Up @@ -16,6 +16,9 @@
from numbers import Number
from typing import cast, Sequence

# Import these for the cadence function signatures.
import executorch.backends.cadence.aot.ops_registrations # noqa: F401
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This line broke the linter job: https://github.com/pytorch/executorch/actions/runs/13398623818/job/37423762070#step:15:7593

I think it needs two spaces before the #. Please run lintrunner -a to fix this, and make sure that the job is passing before merging PRs.

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Sent #8575 to fix this


import torch
import torch.fx
from executorch.backends.cadence.aot.compiler_utils import (
Expand Down Expand Up @@ -849,7 +852,10 @@ def attempt_fusion(
if isinstance(arg, torch.fx.Node)
and isinstance(arg.target, EdgeOpOverload)
and get_edge_overload_packet(arg.target)
== exir_ops.edge.quantized_decomposed.dequantize_per_tensor
in (
exir_ops.edge.quantized_decomposed.dequantize_per_tensor,
exir_ops.edge.cadence.dequantize_per_tensor,
)
]
multiplier_nodes = [
arg
Expand Down
2 changes: 2 additions & 0 deletions backends/cadence/aot/remove_ops.py
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Expand Up @@ -569,6 +569,8 @@ class Subgraph:
exir_ops.edge.aten.hardtanh.default,
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
exir_ops.edge.quantized_decomposed.dequantize_per_tensor.default,
exir_ops.edge.cadence.quantize_per_tensor.default,
exir_ops.edge.cadence.dequantize_per_tensor.default,
}

# must be initialized in the constructor
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8 changes: 8 additions & 0 deletions backends/cadence/aot/reorder_ops.py
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Expand Up @@ -118,6 +118,8 @@ def get_descendent_quant_ops(self, node: torch.fx.Node) -> List[torch.fx.Node]:
if user_target in {
torch.ops.quantized_decomposed.quantize_per_tensor,
exir_ops.edge.quantized_decomposed.quantize_per_tensor,
torch.ops.cadence.quantize_per_tensor,
exir_ops.edge.cadence.quantize_per_tensor,
}:
descendent_quant_ops.append(user)
# If the successor is a trivially quantizable op, consider its users
Expand Down Expand Up @@ -300,6 +302,8 @@ def advance_quantize_op(self, graph_module: torch.fx.GraphModule):
if get_overload_packet(node.target) not in (
exir_ops.edge.quantized_decomposed.quantize_per_tensor,
torch.ops.quantized_decomposed.quantize_per_tensor,
exir_ops.edge.cadence.quantize_per_tensor,
torch.ops.cadence.quantize_per_tensor,
):
continue

Expand Down Expand Up @@ -413,6 +417,7 @@ def postponing_feasible(self, dequant_node: torch.fx.Node):
in {
exir_ops.edge.quantized_decomposed.quantize_per_tensor,
exir_ops.edge.quantized_decomposed.quantize_per_channel,
exir_ops.edge.cadence.quantize_per_tensor,
}
for x in users
)
Expand All @@ -422,6 +427,7 @@ def postpone_dequantize_op(self, graph_module: torch.fx.GraphModule) -> bool:
packet_to_overload_map = {
exir_ops.edge.quantized_decomposed.dequantize_per_tensor: "default",
exir_ops.edge.quantized_decomposed.dequantize_per_channel: "default",
exir_ops.edge.cadence.dequantize_per_tensor: "default",
}
graph = graph_module.graph
modified = False
Expand Down Expand Up @@ -500,6 +506,7 @@ class SinkOpsCloserToUsePass(ExportPass):
exir_ops.edge.aten.dequantize,
exir_ops.edge.quantized_decomposed.dequantize_per_tensor,
exir_ops.edge.quantized_decomposed.dequantize_per_channel,
exir_ops.edge.cadence.dequantize_per_tensor,
}

def sink_ops_closer_to_use(self, graph_module: torch.fx.GraphModule):
Expand Down Expand Up @@ -558,6 +565,7 @@ class HoistOpsCloserToDefPass(ExportPass):

hoistable_ops: Set[EdgeOpOverload] = {
exir_ops.edge.quantized_decomposed.quantize_per_tensor,
exir_ops.edge.cadence.quantize_per_tensor,
exir_ops.edge.aten.slice_copy,
exir_ops.edge.aten.select_copy,
}
Expand Down
10 changes: 6 additions & 4 deletions backends/cadence/aot/replace_ops.py
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Expand Up @@ -162,11 +162,12 @@ def call_operator(
kwargs: Dict[str, Argument],
meta: NodeMetadata,
) -> ProxyValue:
if op not in {exir_ops.edge.quantized_decomposed.quantize_per_tensor.default}:
ns = exir_ops.edge if isinstance(op, EdgeOpOverload) else torch.ops
if op != ns.quantized_decomposed.quantize_per_tensor.default:
return super().call_operator(op, args, kwargs, meta)

return super().call_operator(
exir_ops.edge.cadence.quantize_per_tensor.default,
ns.cadence.quantize_per_tensor.default,
args,
kwargs,
meta,
Expand All @@ -188,11 +189,12 @@ def call_operator(
kwargs: Dict[str, Argument],
meta: NodeMetadata,
) -> ProxyValue:
if op not in {exir_ops.edge.quantized_decomposed.dequantize_per_tensor.default}:
ns = exir_ops.edge if isinstance(op, EdgeOpOverload) else torch.ops
if op != ns.quantized_decomposed.dequantize_per_tensor.default:
return super().call_operator(op, args, kwargs, meta)

return super().call_operator(
exir_ops.edge.cadence.dequantize_per_tensor.default,
ns.cadence.dequantize_per_tensor.default,
args,
kwargs,
meta,
Expand Down
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