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Support translation of local functions#60

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sdpython merged 7 commits intomainfromgr2
Jan 8, 2024
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1 change: 1 addition & 0 deletionsCHANGELOGS.rst
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Expand Up@@ -4,6 +4,7 @@ Change Logs
0.2.0
+++++

* :pr:`60`: supports translation of local functions
* :pr:`59`: add methods to update nodes in GraphAPI

0.1.3
Expand Down
23 changes: 15 additions & 8 deletions_doc/api/light_api.rst
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Expand Up@@ -16,6 +16,13 @@ translate

.. autofunction:: onnx_array_api.light_api.translate

make_helper
+++++++++++

.. autofunction:: onnx_array_api.light_api.make_helper.make_node_extended

.. autofunction:: onnx_array_api.light_api.make_helper.make_ref_attribute

Classes for the Light API
=========================

Expand DownExpand Up@@ -68,19 +75,13 @@ Classes for the Translater
BaseEmitter
+++++++++++

.. autoclass:: onnx_array_api.light_api.emitter.BaseEmitter
:members:

Emitter
+++++++

.. autoclass:: onnx_array_api.light_api.emitter.Emitter
.. autoclass:: onnx_array_api.light_api.base_emitter.BaseEmitter
:members:

EventType
+++++++++

.. autoclass:: onnx_array_api.light_api.translate.EventType
.. autoclass:: onnx_array_api.light_api.base_emitter.EventType
:members:

InnerEmitter
Expand All@@ -89,6 +90,12 @@ InnerEmitter
.. autoclass:: onnx_array_api.light_api.inner_emitter.InnerEmitter
:members:

LightEmitter
++++++++++++

.. autoclass:: onnx_array_api.light_api.light_emitter.LightEmitter
:members:

Translater
++++++++++

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11 changes: 9 additions & 2 deletions_unittests/ut_light_api/test_backend_export.py
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@@ -1,3 +1,4 @@
import sys
import unittest
from typing import Any, Dict, List, Optional
from difflib import unified_diff
Expand All@@ -17,12 +18,16 @@
make_opsetid,
make_tensor_value_info,
)
from onnx.reference.op_run import to_array_extended
from onnx.numpy_helper import from_array, to_array
from onnx.backend.base import Device, DeviceType
from onnx_array_api.reference import ExtendedReferenceEvaluator
from onnx_array_api.light_api.make_helper import make_node_extended
from onnx_array_api.light_api import translate
from onnx_array_api.plotting.text_plot import onnx_simple_text_plot

verbosity = 10 if "-v" in sys.argv or "--verbose" in sys.argv else 0


class ReferenceImplementationError(RuntimeError):
"Fails, export cannot be compared."
Expand All@@ -34,7 +39,7 @@ class ExportWrapper:

def __init__(self, model):
self.model = model
self.expected_sess = ExtendedReferenceEvaluator(self.model)
self.expected_sess = ExtendedReferenceEvaluator(self.model, verbose=verbosity)

@property
def input_names(self):
Expand DownExpand Up@@ -85,13 +90,15 @@ def run(
locs = {
"np": numpy,
"to_array": to_array,
"to_array_extended": to_array_extended,
"from_array": from_array,
"TensorProto": TensorProto,
"make_function": make_function,
"make_opsetid": make_opsetid,
"make_model": make_model,
"make_graph": make_graph,
"make_node": make_node,
"make_node_extended": make_node_extended,
"make_tensor_value_info": make_tensor_value_info,
}
globs = locs.copy()
Expand All@@ -105,7 +112,7 @@ def run(
f"Unable to executed code for api {api!r}\n{new_code}"
) from e
export_model = locs["model"]
ref = ExtendedReferenceEvaluator(export_model)
ref = ExtendedReferenceEvaluator(export_model, verbose=verbosity)
try:
got = ref.run(names, feeds)
except (TypeError, AttributeError) as e:
Expand Down
2 changes: 1 addition & 1 deletion_unittests/ut_light_api/test_translate.py
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Expand Up@@ -6,7 +6,7 @@
from onnx.reference import ReferenceEvaluator
from onnx_array_api.ext_test_case import ExtTestCase
from onnx_array_api.light_api import start, translate, g
from onnx_array_api.light_api.emitter import EventType
from onnx_array_api.light_api.base_emitter import EventType

OPSET_API = min(19, onnx_opset_version() - 1)

Expand Down
124 changes: 116 additions & 8 deletions_unittests/ut_light_api/test_translate_classic.py
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Expand Up@@ -5,6 +5,7 @@
from onnx import ModelProto, TensorProto, load
from onnx.defs import onnx_opset_version
from onnx.reference import ReferenceEvaluator
from onnx.reference.op_run import OpRun
from onnx.helper import (
make_tensor_value_info,
make_node,
Expand DownExpand Up@@ -68,7 +69,7 @@ def test_exp(self):
functions = []
inputs.append(make_tensor_value_info('X', TensorProto.FLOAT, shape=[]))
nodes.append(
make_node(
make_node_extended(
'Exp',
['X'],
['Y']
Expand DownExpand Up@@ -144,14 +145,14 @@ def test_transpose(self):
)
inputs.append(make_tensor_value_info('X', TensorProto.FLOAT, shape=[]))
nodes.append(
make_node(
make_node_extended(
'Reshape',
['X', 'r'],
['r0_0']
)
)
nodes.append(
make_node(
make_node_extended(
'Transpose',
['r0_0'],
['Y'],
Expand DownExpand Up@@ -210,7 +211,7 @@ def test_topk_reverse(self):
inputs.append(make_tensor_value_info('X', TensorProto.FLOAT, shape=[]))
inputs.append(make_tensor_value_info('K', TensorProto.INT64, shape=[]))
nodes.append(
make_node(
make_node_extended(
'TopK',
['X', 'K'],
['Values', 'Indices'],
Expand DownExpand Up@@ -264,7 +265,6 @@ def test_aionnxml(self):
.to_onnx()
)
code = translate(onx, api="onnx")
print(code)
expected = dedent(
"""
opset_imports = [
Expand All@@ -285,14 +285,14 @@ def test_aionnxml(self):
)
inputs.append(make_tensor_value_info('X', TensorProto.FLOAT, shape=[]))
nodes.append(
make_node(
make_node_extended(
'Reshape',
['X', 'r'],
['USE']
)
)
nodes.append(
make_node(
make_node_extended(
'Normalizer',
['USE'],
['Y'],
Expand All@@ -318,7 +318,115 @@ def test_aionnxml(self):
self.maxDiff = None
self.assertEqual(expected, code)

@classmethod
def _code_line(cls, code):
lines = code.split("\n")
return "\n".join(f"{i+1:03d} {line}" for i, line in enumerate(lines))

@classmethod
def _run(cls, code):
try:
code_compiled = compile(code, "<string>", mode="exec")
except Exception as e:
raise AssertionError(
f"Compilation failed due to {e}\n---\n{cls._code_line(code)}\n---\n{e}"
) from e

import onnx
import onnx.helper
import onnx.numpy_helper
import onnx_array_api.light_api.make_helper
import onnx.reference.custom_element_types

def from_array_extended(tensor, name=None):
dt = tensor.dtype
if (
dt == onnx.reference.custom_element_types.float8e4m3fn
and dt.descr[0][0] == "e4m3fn"
):
to = TensorProto.FLOAT8E4M3FN
dt_to = np.uint8
elif (
dt == onnx.reference.custom_element_types.bfloat16
and dt.descr[0][0] == "bfloat16"
):
to = TensorProto.BFLOAT16
dt_to = np.uint16
else:
return onnx.numpy_helper.from_array(tensor, name)

t = onnx.numpy_helper.from_array(tensor.astype(dt_to), name)
t.data_type = to
return t

globs = onnx.__dict__.copy()
globs.update(onnx.helper.__dict__)
globs.update(onnx.numpy_helper.__dict__)
globs.update(onnx_array_api.light_api.make_helper.__dict__)
globs.update(onnx.reference.custom_element_types.__dict__)
globs["from_array_extended"] = from_array_extended
locs = {}
try:
exec(code_compiled, globs, locs)
except Exception as e:
raise AssertionError(
f"Execution failed due to {e}\n---\n{cls._code_line(code)}\n---\n{e}"
) from e
return globs, locs

def test_remove_nodes(self):
path = os.path.join(
os.path.dirname(__file__), "_data", "custom_ops_type_inference_fails_0.onnx"
)
onx = load(path)
code = translate(onx, api="onnx")
_, locs = self._run(code)
self.assertIn("model", locs)
model = locs["model"]
x = np.arange(4).reshape((-1, 2)).astype(np.float32)
feeds = {"X": x}

class CustomGemmFloat8E4M3FN(OpRun):
op_domain = "onnx_extented.ortops.tutorial.cpu"

def _run(
self,
x,
y,
bias=None,
scale_x=None,
scale_y=None,
scale_z=None,
transA=False,
transB=False,
dtype=None,
rowMajor=None,
computeType=None,
):
if scale_x is not None:
x = x * scale_x
if transA:
x = x.T
if scale_y is not None:
y = y * scale_y
if transB:
y = y.T
z = x @ y
if bias is not None:
z += bias
if scale_z is not None:
z = z / scale_z
return (z,)

ref = ReferenceEvaluator(onx, new_ops=[CustomGemmFloat8E4M3FN])
expected = ref.run(None, feeds)[0]
ref2 = ReferenceEvaluator(model, new_ops=[CustomGemmFloat8E4M3FN])
got = ref2.run(None, feeds)[0]
self.assertEqualArray(expected, got)

# with open("debug_test_remove_nodes.py", "w") as f:
# f.write(code)


if __name__ == "__main__":
# TestLightApi().test_topk()
unittest.main(verbosity=2)
2 changes: 1 addition & 1 deletiononnx_array_api/light_api/__init__.py
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Expand Up@@ -67,7 +67,7 @@ def translate(proto: ModelProto, single_line: bool = False, api: str = "light")
:param single_line: as a single line or not
:param api: API to export into,
default is `"light"` and this is handle by class
:class:`onnx_array_api.light_api.emitter.Emitter`,
:class:`onnx_array_api.light_api.light_emitter.LightEmitter`,
another value is `"onnx"` which is the inner API implemented
in onnx package.
:return: code
Expand Down
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