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Improves translation to GraphBuilder#95

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sdpython merged 6 commits intomainfrombugr
Feb 18, 2025
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4 changes: 2 additions & 2 deletions.github/workflows/check-urls.yml
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Expand Up@@ -42,6 +42,6 @@ jobs:
print_all:false
timeout:2
retry_count# : 2
exclude_urls:https://hal.archives-ouvertes.fr/hal-00990252/document
exclude_patterns:https://www.data.gouv.fr/fr/datasets/r/e3d83ab3-dc52-4c99-abaf-8a38050cc68c,https://dev.azure.com/
exclude_urls:https://hal.archives-ouvertes.fr/hal-00990252/document,https://github.com/onnx/tensorflow-onnx
exclude_patterns:https://www.data.gouv.fr/fr/datasets/r/e3d83ab3-dc52-4c99-abaf-8a38050cc68c,https://dev.azure.com/,https://github.com/onnx/tensorflow-onnx
# force_pass : true
5 changes: 5 additions & 0 deletionsCHANGELOGS.rst
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@@ -1,6 +1,11 @@
Change Logs
===========

0.3.1
+++++

*:pr:`95`: improves translation to GraphBuilder

0.3.0
+++++

Expand Down
67 changes: 62 additions & 5 deletions_unittests/ut_translate_api/test_translate_builder.py
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Expand Up@@ -8,7 +8,8 @@
fromonnx_array_api.ext_test_caseimportExtTestCase
fromonnx_array_api.light_apiimportstart
fromonnx_array_api.graph_apiimportGraphBuilder
fromonnx_array_api.translate_apiimporttranslate
fromonnx_array_api.translate_apiimporttranslate,Translater
fromonnx_array_api.translate_api.builder_emitterimportBuilderEmitter


OPSET_API=min(19,onnx_opset_version()-1)
Expand All@@ -19,7 +20,7 @@ def setUp(self):
self.maxDiff=None

deftest_exp(self):
onx=start(opset=19).vin("X").Exp().rename("Y").vout().to_onnx()
onx=start(opset=19,ir_version=10).vin("X").Exp().rename("Y").vout().to_onnx()
self.assertIsInstance(onx,ModelProto)
self.assertIn("Exp",str(onx))
ref=ReferenceEvaluator(onx)
Expand All@@ -38,7 +39,7 @@ def light_api(
op.Identity(Y, outputs=["Y"])
return Y
g = GraphBuilder({'': 19})
g = GraphBuilder({'': 19}, ir_version=10)
g.make_tensor_input("X", TensorProto.FLOAT, ())
light_api(g.op, "X")
g.make_tensor_output("Y", TensorProto.FLOAT, ())
Expand DownExpand Up@@ -68,7 +69,7 @@ def light_api(

deftest_zdoc(self):
onx= (
start(opset=19)
start(opset=19,ir_version=10)
.vin("X")
.reshape((-1,1))
.Transpose(perm=[1,0])
Expand All@@ -89,7 +90,7 @@ def light_api(
op.Identity(Y, outputs=["Y"])
return Y
g = GraphBuilder({'': 19})
g = GraphBuilder({'': 19}, ir_version=10)
g.make_tensor_input("X", TensorProto.FLOAT, ())
light_api(g.op, "X")
g.make_tensor_output("Y", TensorProto.FLOAT, ())
Expand DownExpand Up@@ -117,6 +118,62 @@ def light_api(
self.assertNotEmpty(model)
check_model(model)

deftest_exp_f(self):
onx=start(opset=19,ir_version=10).vin("X").Exp().rename("Y").vout().to_onnx()
self.assertIsInstance(onx,ModelProto)
self.assertIn("Exp",str(onx))
ref=ReferenceEvaluator(onx)
a=np.arange(10).astype(np.float32)
got=ref.run(None, {"X":a})[0]
self.assertEqualArray(np.exp(a),got)

tr=Translater(onx,emitter=BuilderEmitter("mm"))
code=tr.export(as_str=True)

expected=dedent(
"""
def light_api(
op: "GraphBuilder",
X: "FLOAT[]",
):
Y = op.Exp(X)
op.Identity(Y, outputs=["Y"])
return Y
def mm() -> "ModelProto":
g = GraphBuilder({'': 19}, ir_version=10)
g.make_tensor_input("X", TensorProto.FLOAT, ())
light_api(g.op, "X")
g.make_tensor_output("Y", TensorProto.FLOAT, ())
model = g.to_onnx()
return model
model = mm()
"""
).strip("\n")
self.assertEqual(expected,code.strip("\n"))

deflight_api(
op:"GraphBuilder",
X:"FLOAT[]",# noqa: F722
):
Y=op.Exp(X)
op.Identity(Y,outputs=["Y"])
returnY

g2=GraphBuilder({"":19})
g2.make_tensor_input("X",TensorProto.FLOAT, ("A",))
light_api(g2.op,"X")
g2.make_tensor_output("Y",TensorProto.FLOAT, ("A",))
onx2=g2.to_onnx()

ref=ReferenceEvaluator(onx2)
a=np.arange(10).astype(np.float32)
got=ref.run(None, {"X":a})[0]
self.assertEqualArray(np.exp(a),got)


if__name__=="__main__":
unittest.main(verbosity=2)
2 changes: 1 addition & 1 deletiononnx_array_api/__init__.py
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Expand Up@@ -2,5 +2,5 @@
APIs to create ONNX Graphs.
"""

__version__="0.3.0"
__version__="0.3.1"
__author__="Xavier Dupré"
60 changes: 52 additions & 8 deletionsonnx_array_api/translate_api/builder_emitter.py
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Expand Up@@ -4,10 +4,17 @@
from .base_emitterimportBaseEmitter

_types= {
TensorProto.DOUBLE:"DOUBLE",
TensorProto.FLOAT:"FLOAT",
TensorProto.FLOAT16:"FLOAT16",
TensorProto.INT64:"INT64",
TensorProto.INT32:"INT32",
TensorProto.INT16:"INT16",
TensorProto.UINT64:"UINT64",
TensorProto.UINT32:"UINT32",
TensorProto.UINT16:"UINT16",
TensorProto.STRING:"STRING",
TensorProto.BOOL:"BOOL",
}


Expand All@@ -20,6 +27,10 @@ class BuilderEmitter(BaseEmitter):
Converts event into proper code.
"""

def__init__(self,make_model_function:str=""):
super().__init__()
self.make_model_function=make_model_function

defjoin(self,rows:List[str],single_line:bool=False)->str:
"Join the rows"
assert (
Expand All@@ -29,6 +40,7 @@ def join(self, rows: List[str], single_line: bool = False) -> str:

def_emit_start(self,**kwargs:Dict[str,Any])->List[str]:
self.opsets=kwargs.get("opsets", {})
self.ir_version=kwargs.get("ir_version",None)
return []

def_emit_to_onnx_model(self,**kwargs:Dict[str,Any])->List[str]:
Expand All@@ -43,12 +55,27 @@ def _emit_to_onnx_model(self, **kwargs: Dict[str, Any]) -> List[str]:
)
rows= [
"",
f"g = GraphBuilder({self.opsets})",
(
f"g = GraphBuilder({self.opsets}, ir_version={self.ir_version})"
ifself.ir_version
elsef"GraphBuilder({self.opsets})"
),
*inputs,
f"{self.name}({inps})",
*outputs,
"model = g.to_onnx()",
]
ifself.make_model_function:
rows= [
"",
"",
f'def{self.make_model_function}() -> "ModelProto":',
*[" "+_for_inrows[1:]],
" return model",
"",
"",
f"model ={self.make_model_function}()",
]
returnrows

def_emit_begin_graph(self,**kwargs:Dict[str,Any])->List[str]:
Expand DownExpand Up@@ -78,13 +105,16 @@ def _emit_input(self, **kwargs: Dict[str, Any]) -> List[str]:
name=kwargs["name"]
itype=kwargs.get("elem_type",0)
shape=kwargs.get("shape",None)
name=self._clean_result_name(name)
ifitype==0:
inp="X"
inp=nameor"X"
else:
ifshapeisNone:
inp=f'X: "{_itype_to_string(itype)}"'
inp=f'{name}: "{_itype_to_string(itype)}"'
else:
inp=f'X: "{_itype_to_string(itype)}[{", ".join(map(str,shape))}]"'
inp= (
f'{name}: "{_itype_to_string(itype)}[{", ".join(map(str,shape))}]"'
)
self.inputs_full.append(inp)
self.inputs.append(name)
self.inputs_full_.append((name,_itype_to_string(itype),shape))
Expand DownExpand Up@@ -113,6 +143,7 @@ def _emit_end_return(self, **kwargs: Dict[str, Any]) -> List[str]:

def_emit_output(self,**kwargs:Dict[str,Any])->List[str]:
name=kwargs["name"]
name=self._clean_result_name(name)
itype=kwargs.get("elem_type",0)
shape=kwargs.get("shape",None)
self.outputs.append(name)
Expand All@@ -126,6 +157,8 @@ def _emit_node(self, **kwargs: Dict[str, Any]) -> List[str]:
ifkwargs.get("domain","")!="":
domain=kwargs["domain"]
op_type=f"{domain}.{op_type}"
else:
domain=""
atts=kwargs.get("atts", {})
args= []
fork,vinatts.items():
Expand All@@ -134,11 +167,22 @@ def _emit_node(self, **kwargs: Dict[str, Any]) -> List[str]:
raiseNotImplementedError("Graph attribute not supported yet.")
args.append(f"{k}={vatt}")

outs=", ".join(outputs)
inps=", ".join(inputs)
outs=", ".join(map(self._clean_result_name,outputs))
inps=", ".join(map(self._clean_result_name,inputs))
op_type=self._emit_node_type(op_type,domain)
sdomain=""ifnotdomainelsef", domain={domain!r}"
ifargs:
sargs=", ".join(args)
row=f"{outs} = op.{op_type}({inps},{sargs})"
ifinps:
row=f"{outs} = op.{op_type}({inps},{sargs}{sdomain})"
else:
row=f"{outs} = op.{op_type}({sargs}{sdomain})"
else:
row=f"{outs} = op.{op_type}({inps})"
row=f"{outs} = op.{op_type}({inps}{sdomain})"
return [row]

def_clean_result_name(self,name):
returnname

def_emit_node_type(self,op_type,domain):
returnop_type
6 changes: 5 additions & 1 deletiononnx_array_api/translate_api/translate.py
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Expand Up@@ -35,7 +35,11 @@ def export(self, as_str, single_line: bool = False) -> Union[str, List[str]]:
last_event=None
ifisinstance(self.proto_,ModelProto):
opsets= {d.domain:d.versionfordinself.proto_.opset_import}
rows.extend(self.emitter(EventType.START,opsets=opsets))
rows.extend(
self.emitter(
EventType.START,opsets=opsets,ir_version=self.proto_.ir_version
)
)
inputs=self.proto_.graph.input
outputs=self.proto_.graph.output
nodes=self.proto_.graph.node
Expand Down
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