Fix include_self for scatter_reduce #2090

xadupre · 2025-03-07T14:14:32Z

No description provided.

codecov · 2025-03-07T14:18:57Z

❌ 19 Tests Failed:

Tests completed	Failed	Passed	Skipped
6663	19	6644	1922

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

onnxscript.backend.onnx_export_test.TestOnnxBackEnd::test_export2python_produces_correct_onnx_script_model_0266_test_compress_0

Stack Traces | 0.004s 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_compress_0'

The above exception was the direct cause of the following exception:
.nox\test_onnx_weekly\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_compress_0' (e=No module named 'tests.onnx_backend_test_code.test_compress_0') (file: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_compress_0.py', absolute path: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_compress_0.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, FLOAT
E   from onnxscript.onnx_opset import opset11
E   
E   @script()
E   def bck_test_compress_0(input: FLOAT[3,2], condition: BOOL[3]) -> (FLOAT[2,2]):
E       output = opset11.Compress(input, condition, axis=0)
E       return output

onnxscript.backend.onnx_export_test.TestOnnxBackEnd::test_export2python_produces_correct_onnx_script_model_0365_test_erf

Stack Traces | 0.004s run time

onnxscript\backend\onnx_export_test.py:137: in extract_functions
    mod = importlib.import_module(import_name)
C:\hostedtoolcache\windows\Python\3.10.11\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_erf'

The above exception was the direct cause of the following exception:
.nox\test\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_erf' (e=No module named 'tests.onnx_backend_test_code.test_erf') (file: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_erf.py', absolute path: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_erf.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_erf(x: FLOAT[1,3,32,32]) -> (FLOAT[1,3,32,32]):
E       y = opset13.Erf(x)
E       return y

onnxscript.backend.onnx_export_test.TestOnnxBackEnd::test_export2python_produces_correct_onnx_script_model_0530_test_layer_normalization_3d_axis_negative_3_epsilon

Stack Traces | 0.004s 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_layer_normalization_3d_axis_negative_3_epsilon'

The above exception was the direct cause of the following exception:
.nox\test_onnx_weekly\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_layer_normalization_3d_axis_negative_3_epsilon' (e=No module named 'tests.onnx_backend_test_code.test_layer_normalization_3d_axis_negative_3_epsilon') (file: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_layer_normalization_3d_axis_negative_3_epsilon.py', absolute path: 'D:\\a\\onnxscript\\onnxscript\\tests\\onnx_backend_test_code\\test_layer_normalization_3d_axis_negative_3_epsilon.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 opset17
E   
E   @script()
E   def bck_test_layer_normalization_3d_axis_negative_3_epsilon(X: FLOAT[2,3,5], W: FLOAT[2,3,5], B: FLOAT[2,3,5]) -> (FLOAT[2,3,5], FLOAT[1,1,1], FLOAT[1,1,1]):
E       Y, Mean, InvStdDev = opset17.LayerNormalization(X, W, B, axis=-3, epsilon=0.10000000149011612)
E       return Y, Mean, InvStdDev

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onnxscript/function_libs/torch_lib/ops/core.py

justinchuby · 2025-03-07T17:52:56Z

onnxscript/function_libs/torch_lib/ops/core.py

+    if not include_self:
+        if onnx_reduce == "max":
+            value = onh.from_array(
+                np.array([np.finfo(src.dtype.numpy()).min], dtype=src.dtype.numpy())


E.g. could you add a comment on why we needed to use np.finfo min/max for this reduction type, for future readers?

justinchuby · 2025-03-07T17:53:52Z

tests/function_libs/torch_lib/ops_test_data.py

-        # ONNX has not include_self parameter and default is include_self=True mode
-        matcher=lambda sample: sample.kwargs.get("include_self") is False,
-        reason="ONNX does't support include_self=False option",
-    )
    .xfail(
        variant_name="amax",


I wonder if we should set dtypes=(torch.float16,), as well

…catter

Co-authored-by: Justin Chu <[email protected]>

…scatter

onnxscript/function_libs/torch_lib/ops/core.py

justinchuby · 2025-03-10T16:46:08Z

onnxscript/function_libs/torch_lib/ops/core.py

-            value = onh.from_array(
-                np.array([np.finfo(src.dtype.numpy()).max], dtype=src.dtype.numpy())
-            )
+            value = ir.tensor([np.finfo(src.dtype.numpy()).max], dtype=src.dtype)


Does this work for bfloat16 or integer types?

If ml-dtypes is used, that should work as well. I can also switch to pytorch to find the minimum value for each type.

I just tested it, it seems it doesn't work:

>>> import ml_dtypes >>> import numpy as np >>> np.finfo(ml_dtypes.bfloat16) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/justinchu/anaconda3/envs/pytorch/lib/python3.12/site-packages/numpy/_core/getlimits.py", line 525, in __new__ raise ValueError("data type %r not inexact" % (dtype)) ValueError: data type <class 'ml_dtypes.bfloat16'> not inexact >>> np.finfo(np.int32) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/justinchu/anaconda3/envs/pytorch/lib/python3.12/site-packages/numpy/_core/getlimits.py", line 525, in __new__ raise ValueError("data type %r not inexact" % (dtype)) ValueError: data type <class 'numpy.int32'> not inexact >>> np.finfo(np.float32) finfo(resolution=1e-06, min=-3.4028235e+38, max=3.4028235e+38, dtype=float32)

Would it be possible to do this ir.tensor(np.inf, dtype=src.dtype)? Seems like it would work:

>>> ir.tensor(np.inf, dtype=ir.DataType.BFLOAT16) Tensor<BFLOAT16,[]>(array(inf, dtype=bfloat16), name=None)

For int types I think we need some special handling. Maybe we should store max and min values to the ir.DataType class?

onnxscript/function_libs/torch_lib/ops/core.py

+        # whether or not it takes part in it.
+        # It is -inf if the reduction is max, inf for min, 0 for add, 1 for mul.
+        # mean is not supported.
+        dtype = src.dtype or cst.dtype


onnxscript/function_libs/torch_lib/ops/core.py

+        # whether or not it takes part in it.
+        # It is -inf if the reduction is max, inf for min, 0 for add, 1 for mul.
+        # mean is not supported.
+        dtype = src.dtype or cst.dtype


Fix include_self for scatter_reduce

c451d4d

xadupre mentioned this pull request Mar 7, 2025

[ONNX] GNN model inaccuracy: scatter_reduce need to be fixed pytorch/pytorch#147617

Open

xadupre added 2 commits March 7, 2025 15:28

fix values

87c4085

lint

0a6c181

justinchuby self-assigned this Mar 7, 2025

justinchuby self-requested a review March 7, 2025 16:54