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Tag constants after quantization #14955

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Oct 15, 2025
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Tag constants after quantization #14955

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45 changes: 24 additions & 21 deletions examples/models/llama/export_llama_lib.py
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Original file line number Diff line number Diff line change
Expand Up @@ -874,6 +874,7 @@ def _to_edge_and_lower_llama_xnnpack(
xnnpack_extended_ops: bool = False,
generate_etrecord: bool = False,
verbose: bool = False,
gen_tag_fn: Optional[Callable[[torch.fx.Node], Optional[str]]] = None,
) -> LLMEdgeManager: # noqa: C901
partitioners = []

Expand All @@ -896,9 +897,27 @@ def _to_edge_and_lower_llama_xnnpack(
if generate_etrecord:
builder_exported.generate_etrecord = True

builder = builder_exported.pt2e_quantize(quantizers).to_edge_transform_and_lower(
partitioners
)
builder = builder_exported.pt2e_quantize(quantizers)
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@digantdesai digantdesai Oct 13, 2025 •
edited
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Just moving here after pt2e_quantize or something else has also changed?

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@lucylq lucylq Oct 14, 2025 •
edited
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Yep, splitting it so we can tag afterpt2e_quantize and before to_edge_transform_and_lower

if gen_tag_fn is not None:
from executorch.exir.passes.external_constants_pass import (
delegate_external_constants_pass_unlifted,
external_constants_pass,
)

assert (
builder_exported.pre_autograd_graph_module is not None
), "pre_autograd_graph_module shouldn't be None here"
delegate_external_constants_pass_unlifted(
module=builder_exported.pre_autograd_graph_module,
gen_tag_fn=gen_tag_fn,
)

# Also add a pass for 'to_executorch' to tag weights that aren't delegated.
additional_passes.append(
partial(external_constants_pass, gen_tag_fn=gen_tag_fn)
)

builder = builder.to_edge_transform_and_lower(partitioners)
if verbose:
print_delegation_info(builder.edge_manager.exported_program().graph_module)

Expand Down Expand Up @@ -1136,6 +1155,7 @@ def _export_llama(llm_config: LlmConfig) -> LLMEdgeManager: # noqa: C901
llm_config.backend.xnnpack.enabled = True

if llm_config.backend.xnnpack.enabled:
gen_tag_fn = None
if (
llm_config.export.foundation_weights_file is not None
or llm_config.export.lora_weights_file is not None
Expand All @@ -1145,24 +1165,6 @@ def _export_llama(llm_config: LlmConfig) -> LLMEdgeManager: # noqa: C901
if "lora" not in x.name
else llm_config.export.lora_weights_file
)
from executorch.exir.passes.external_constants_pass import (
delegate_external_constants_pass_unlifted,
external_constants_pass,
)

assert (
builder_exported.pre_autograd_graph_module is not None
), "pre_autograd_graph_module shouldn't be None here"
delegate_external_constants_pass_unlifted(
module=builder_exported.pre_autograd_graph_module,
gen_tag_fn=gen_tag_fn,
)

# Also add a pass for 'to_executorch' to tag weights that aren't delegated.
additional_passes.append(
partial(external_constants_pass, gen_tag_fn=gen_tag_fn)
)

builder = _to_edge_and_lower_llama_xnnpack(
builder_exported,
modelname,
Expand All @@ -1173,6 +1175,7 @@ def _export_llama(llm_config: LlmConfig) -> LLMEdgeManager: # noqa: C901
xnnpack_extended_ops=llm_config.backend.xnnpack.extended_ops,
generate_etrecord=llm_config.debug.generate_etrecord,
verbose=llm_config.debug.verbose,
gen_tag_fn=gen_tag_fn,
)
elif llm_config.backend.openvino.enabled:
builder = _to_edge_and_lower_llama_openvino(
Expand Down
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