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Fix modelbuilder export #214

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Merged
sdpython merged 7 commits into from
Sep 4, 2025
Merged

Fix modelbuilder export #214

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b768139
Fix modelbuilder export
xadupre Sep 4, 2025
6237a78
lint
xadupre Sep 4, 2025
2e721b9
fix torch patch
xadupre Sep 4, 2025
b442782
Merge branch 'main' of https://github.com/sdpython/onnx-diagnostic in…
xadupre Sep 4, 2025
e1cd7cb
except
xadupre Sep 4, 2025
33fd641
fix unittest
xadupre Sep 4, 2025
7905d8a
lint
xadupre Sep 4, 2025
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3 changes: 3 additions & 0 deletions CHANGELOGS.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,9 @@ Change Logs
0.7.9
+++++

* :pr:`214`: fix modelbuilder export
* :pr:`213`: use DYNAMIC on batch size

0.7.8
+++++

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2 changes: 1 addition & 1 deletion _doc/examples/plot_export_locate_issue.py
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Expand Up @@ -88,7 +88,7 @@ def forward(self, x: torch.Tensor, ys: list[torch.Tensor]):
with torch_export_patches(stop_if_static=1, verbose=1):
try:
torch.export.export(model, inputs, dynamic_shapes=dyn_shapes)
except (AssertionError, torch._dynamo.exc.TorchRuntimeError) as e:
except (AssertionError, ValueError, torch._dynamo.exc.TorchRuntimeError) as e:
print("-- It failed as excepted.")
print(f"-- final error is {e}")
print("-- Stack Trace")
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64 changes: 10 additions & 54 deletions _unittests/ut_tasks/test_tasks.py
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Expand Up @@ -57,38 +57,16 @@ def test_automatic_speech_recognition_float32(self):
model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
model(**data["inputs"])
model(**data["inputs2"])
Dim = torch.export.Dim
self.maxDiff = None
self.assertIn("{0:Dim(batch),1:DYN(seq_length)}", self.string_type(ds))
self.assertIn("{0:DYN(batch),1:DYN(seq_length)}", self.string_type(ds))
self.assertEqualAny(
{
"decoder_input_ids": {
0: Dim("batch", min=1, max=1024),
1: "seq_length",
},
"decoder_input_ids": {0: "batch", 1: "seq_length"},
"cache_position": {0: "seq_length"},
"encoder_outputs": [{0: Dim("batch", min=1, max=1024)}],
"encoder_outputs": [{0: "batch"}],
"past_key_values": [
[
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
],
[
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
],
[[{0: "batch"}, {0: "batch"}], [{0: "batch"}, {0: "batch"}]],
[[{0: "batch"}, {0: "batch"}], [{0: "batch"}, {0: "batch"}]],
],
},
ds,
Expand Down Expand Up @@ -134,38 +112,16 @@ def test_automatic_speech_recognition_float16(self):
model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
model = to_any(model, torch.float16)
model(**data["inputs2"])
Dim = torch.export.Dim
self.maxDiff = None
self.assertIn("{0:Dim(batch),1:DYN(seq_length)}", self.string_type(ds))
self.assertIn("{0:DYN(batch),1:DYN(seq_length)}", self.string_type(ds))
self.assertEqualAny(
{
"decoder_input_ids": {
0: Dim("batch", min=1, max=1024),
1: "seq_length",
},
"decoder_input_ids": {0: "batch", 1: "seq_length"},
"cache_position": {0: "seq_length"},
"encoder_outputs": [{0: Dim("batch", min=1, max=1024)}],
"encoder_outputs": [{0: "batch"}],
"past_key_values": [
[
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
],
[
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
[
{0: Dim("batch", min=1, max=1024)},
{0: Dim("batch", min=1, max=1024)},
],
],
[[{0: "batch"}, {0: "batch"}], [{0: "batch"}, {0: "batch"}]],
[[{0: "batch"}, {0: "batch"}], [{0: "batch"}, {0: "batch"}]],
],
},
ds,
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5 changes: 5 additions & 0 deletions onnx_diagnostic/helpers/model_builder_helper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -201,10 +201,12 @@ def create_model_builder(
arch_map = {
"ChatGLMForConditionalGeneration": builder.ChatGLMModel,
"ChatGLMModel": builder.ChatGLMModel,
"Ernie4_5_ForCausalLM": builder.ErnieModel,
"GemmaForCausalLM": builder.Gemma2Model,
"Gemma3ForCausalLM": builder.Gemma3Model,
"Gemma3ForConditionalGeneration": builder.Gemma3Model,
"GraniteForCausalLM": builder.GraniteModel,
"GptOssForCausalLM": builder.GPTOSSModel,
"LlamaForCausalLM": builder.LlamaModel,
"MistralForCausalLM": builder.MistralModel,
"NemotronForCausalLM": builder.NemotronModel,
Expand Down Expand Up @@ -235,6 +237,7 @@ def create_model_builder(
"Phi4MMForCausalLM": builder.Phi4MMModel,
"Qwen2ForCausalLM": builder.QwenModel,
"Qwen3ForCausalLM": builder.Qwen3Model,
"SmolLM3ForCausalLM": builder.SmolLM3Model,
}

assert config.architectures[0] in arch_map, (
Expand Down Expand Up @@ -276,6 +279,8 @@ def _post(onnx_model):
for key in text_config:
if not hasattr(config, key):
setattr(config, key, getattr(text_config, key))
elif config.architectures[0] == "GptOssForCausalLM":
delattr(config, "quantization_config")
elif (
config.architectures[0] == "PhiMoEForCausalLM"
and config.max_position_embeddings != config.original_max_position_embeddings
Expand Down
5 changes: 4 additions & 1 deletion onnx_diagnostic/torch_export_patches/patches/patch_torch.py
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Expand Up @@ -205,7 +205,10 @@ def _set_replacement(
# Precondition: a == tgt
assert isinstance(a, sympy.Symbol)

if self.allow_complex_guards_as_runtime_asserts and not _is_supported_equivalence(tgt):
if (
getattr(self, "allow_complex_guards_as_runtime_asserts", False)
or getattr(self, "prefer_deferred_runtime_asserts_over_guards", False)
) and not _is_supported_equivalence(tgt):
# continuing leads to placeholder shapes
# having complex expressions that we can't resolve
return
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12 changes: 9 additions & 3 deletions onnx_diagnostic/torch_models/validate.py
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Expand Up @@ -496,9 +496,15 @@ def validate_model(
cpl = CoupleInputsDynamicShapes(
tuple(), data[k], dynamic_shapes=data["dynamic_shapes"]
)
data[k] = cpl.change_dynamic_dimensions(
desired_values=dict(batch=1), only_desired=True
)
if patch_kwargs.get("patch", False):
with torch_export_patches(**patch_kwargs): # type: ignore[arg-type]
data[k] = cpl.change_dynamic_dimensions(
desired_values=dict(batch=1), only_desired=True
)
else:
data[k] = cpl.change_dynamic_dimensions(
desired_values=dict(batch=1), only_desired=True
)
if verbose:
print(f"[validate_model] batch=1 --> {string_type(data[k], with_shape=True)}")

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2 changes: 1 addition & 1 deletion requirements-dev.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@ matplotlib
onnx-array-api>=0.3.1
onnx
git+https://github.com/onnx/ir-py.git
git+https://github.com/microsoft/onnxscript.git
onnxscript
openpyxl
packaging
pandas
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