Use ir methods to replace onnx helper

[justinchuby]

Ban onnx.helper and onnx.numpy_helper because they can be slow. Selectively enable usages of some with noqa: TID251 and updated usages of the rest.

Fix ir.tensor to generate float32 tensors when a plain python float is provided.

[codecov]

❌ 11 Tests Failed:

Tests completed	Failed	Passed	Skipped
14639	11	14628	1699

View the top 3 failed test(s) by shortest run time

onnxscript.backend.onnx_export_test.TestOnnxBackEnd::test_export2python_produces_correct_onnx_script_model_0032_test_and_bcast3v2d

Stack Traces | 0.003s run time

onnxscript\backend\onnx_export_test.py:137: in extract_functions
    mod = importlib.import_module(import_name)
C:\hostedtoolcache\windows\Python\3.11.9\x64\Lib\importlib\__init__.py:126: in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
E   ModuleNotFoundError: No module named 'tests.onnx_backend_test_code.test_and_bcast3v2d'

The above exception was the direct cause of the following exception:
.nox\test_ort_nightly\Lib\site-packages\parameterized\parameterized.py:620: in standalone_func
    return func(*(a + p.args), **p.kwargs, **kw)
onnxscript\backend\onnx_export_test.py:271: in test_export2python_produces_correct_onnx_script_model
    functions = extract_functions(backend_test.name, code, self.test_folder)
onnxscript\backend\onnx_export_test.py:139: in extract_functions
    raise AssertionError(
E   AssertionError: Unable to import 'tests.onnx_backend_test_code.test_and_bcast3v2d' (e=No module named 'tests.onnx_backend_test_code.test_and_bcast3v2d') (file: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_and_bcast3v2d.py', absolute path: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_and_bcast3v2d.py', current folder: D:\a\onnxscript\onnxscript
E   ---- CONTENT --
E   import numpy
E   from onnx import TensorProto
E   from onnx.helper import make_tensor
E   from onnxscript import script, external_tensor
E   from onnxscript.values import Opset
E   from onnxscript.onnx_types import BOOL
E   from onnxscript.onnx_opset import opset7
E   
E   @script()
E   def bck_test_and_bcast3v2d(x: BOOL[3,4,5], y: BOOL[4,5]) -> (BOOL[3,4,5]):
E       r_and = opset7.And(x, y)
E       return r_and

onnxscript.backend.onnx_export_test.TestOnnxBackEnd::test_export2python_produces_correct_onnx_script_model_0243_test_clip_default_min

Stack Traces | 0.003s run time

onnxscript\backend\onnx_export_test.py:137: in extract_functions
    mod = importlib.import_module(import_name)
C:\hostedtoolcache\windows\Python\3.11.9\x64\Lib\importlib\__init__.py:126: in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
E   ModuleNotFoundError: No module named 'tests.onnx_backend_test_code.test_clip_default_min'

The above exception was the direct cause of the following exception:
.nox\test_ort_nightly\Lib\site-packages\parameterized\parameterized.py:620: in standalone_func
    return func(*(a + p.args), **p.kwargs, **kw)
onnxscript\backend\onnx_export_test.py:271: in test_export2python_produces_correct_onnx_script_model
    functions = extract_functions(backend_test.name, code, self.test_folder)
onnxscript\backend\onnx_export_test.py:139: in extract_functions
    raise AssertionError(
E   AssertionError: Unable to import 'tests.onnx_backend_test_code.test_clip_default_min' (e=No module named 'tests.onnx_backend_test_code.test_clip_default_min') (file: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_clip_default_min.py', absolute path: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_clip_default_min.py', current folder: D:\a\onnxscript\onnxscript
E   ---- CONTENT --
E   import numpy
E   from onnx import TensorProto
E   from onnx.helper import make_tensor
E   from onnxscript import script, external_tensor
E   from onnxscript.values import Opset
E   from onnxscript.onnx_types import FLOAT
E   from onnxscript.onnx_opset import opset13
E   
E   @script()
E   def bck_test_clip_default_min(x: FLOAT[3,4,5], min: FLOAT) -> (FLOAT[3,4,5]):
E       y = opset13.Clip(x, min)
E       return y

onnxscript.backend.onnx_export_test.TestOnnxBackEnd::test_export2python_produces_correct_onnx_script_model_0759_test_or_bcast4v4d

Stack Traces | 0.003s run time

onnxscript\backend\onnx_export_test.py:137: in extract_functions
    mod = importlib.import_module(import_name)
C:\hostedtoolcache\windows\Python\3.11.9\x64\Lib\importlib\__init__.py:126: in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
E   ModuleNotFoundError: No module named 'tests.onnx_backend_test_code.test_or_bcast4v4d'

The above exception was the direct cause of the following exception:
.nox\test_ort_nightly\Lib\site-packages\parameterized\parameterized.py:620: in standalone_func
    return func(*(a + p.args), **p.kwargs, **kw)
onnxscript\backend\onnx_export_test.py:271: in test_export2python_produces_correct_onnx_script_model
    functions = extract_functions(backend_test.name, code, self.test_folder)
onnxscript\backend\onnx_export_test.py:139: in extract_functions
    raise AssertionError(
E   AssertionError: Unable to import 'tests.onnx_backend_test_code.test_or_bcast4v4d' (e=No module named 'tests.onnx_backend_test_code.test_or_bcast4v4d') (file: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_or_bcast4v4d.py', absolute path: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_or_bcast4v4d.py', current folder: D:\a\onnxscript\onnxscript
E   ---- CONTENT --
E   import numpy
E   from onnx import TensorProto
E   from onnx.helper import make_tensor
E   from onnxscript import script, external_tensor
E   from onnxscript.values import Opset
E   from onnxscript.onnx_types import BOOL
E   from onnxscript.onnx_opset import opset7
E   
E   @script()
E   def bck_test_or_bcast4v4d(x: BOOL[1,4,1,6], y: BOOL[3,1,5,6]) -> (BOOL[3,4,5,6]):
E       r_or = opset7.Or(x, y)
E       return r_or

To view more test analytics, go to the Test Analytics Dashboard
_{📋 Got 3 mins? Take this short survey to help us improve Test Analytics.}

[Copilot]

Pull Request Overview

This PR aims to deprecate the use of onnx.helper and onnx.numpy_helper in favor of ir-based methods to improve performance. Key changes include replacing multiple onnx.helper calls with either their ir or ir.serde counterparts (and adding “# noqa: TID251” comments) and updating imports and utility functions accordingly.

Reviewed Changes

Copilot reviewed 21 out of 21 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
onnxscript/tensor.py	Updated import and added noqa comment on onnx.helper usage.
onnxscript/_internal/utils.py	Applied noqa comments to onnx.helper calls in utility functions.
onnxscript/optimizer/_constant_folding.py	Replaced onnx.numpy_helper.from_array with ir.serde.serialize_tensor.
onnxscript/main.py	Updated model export logic to use ir.Model and ir.save.
onnxscript/optimizer/_legacy/constant_folding.py, etc.	Added ruff: noqa: TID251 markers and adjusted helper calls across files.
onnxscript/_internal/autocast.py	Replaced tensor conversion via numpy_helper with ir.serde.serialize_tensor.
onnxscript/rewriter/llama_rule_sets.py	Modified allowed tensor types check to use as_int() instead of value.
onnxscript/rewriter/cast_constant_of_shape.py and others	Changed onnx.helper.make_tensor calls to use ir.tensor.
onnxscript/function_libs/torch_lib/ops/nn.py	Updated empty-tensor creation to use ir.tensor.

Comments suppressed due to low confidence (2)

onnxscript/rewriter/llama_rule_sets.py:65

• Ensure that converting the attribute value with as_int() returns the expected integer representation that matches the entries in _allowed_tensor_types. Verify that edge cases or unexpected types do not cause the check to fail.

to.as_int() in cls._allowed_tensor_types

onnxscript/_internal/autocast.py:39

• Confirm that the new serialization using ir.serde.serialize_tensor produces outputs consistent with the previous behavior of numpy_helper.from_array, ensuring compatibility with downstream tensor utilities.

return ir.serde.serialize_tensor(ir.tensor(pyvalue, name=tensor_name))

[justinchuby]

Check that sequence is not empty and ask for a dtype if it is