Extend unit tests #1967
Extend unit tests #1967
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This is pretty cool. If you can isolate changes to onnxscript/ir in a separate PR that’d be great |
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| type_constraint = deduce_type_constraints.TypeConstraint("test_constraint", {"tensor(float)", "tensor(int64)"}) | ||
| type_constraint.bind_value(value1) | ||
| type_constraint.bind_value(value2) | ||
| expected_repr = "TypeConstraint(name=test_constraint, type_strs={'tensor(float)', 'tensor(int64)'}, values=['value1', 'value2'])" |
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Unused local variable Note
| graph.register_initializer(unnamed_initializer) | ||
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| # Attempt to register an initializer that is produced by a node | ||
| node = ir.Node(domain="", op_type="Add", inputs=[], outputs=[initializer]) |
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Unused local variable Note
| type_constraints = {} | ||
| parameter = _schemas._convert_formal_parameter(mock_param, type_constraints) | ||
| self.assertEqual(parameter.name, "param") | ||
| self.assertTrue(ir.TensorType(ir.DataType.FLOAT) in parameter.type_constraint.allowed_types) |
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Imprecise assert Note
| def match_pattern(op, x): | ||
| return op.Add(x, x) | ||
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| def apply_pattern(op, x, **_): |
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Unused local variable Note
| @@ -4,6 +4,11 @@ | |||
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| import onnxscript.tools.benchmark.benchmark_helpers as bh | |||
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| import torch | |||
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Unused import Note test
| @@ -4,6 +4,11 @@ | |||
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| import onnxscript.tools.benchmark.benchmark_helpers as bh | |||
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| import torch | |||
| import onnx | |||
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Unused import Note test
| def test_class_getitem_shape_already_specified(self): | ||
| from onnxscript.onnx_types import FLOAT | ||
| with self.assertRaises(ValueError): | ||
| FLOAT[None][None] |
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Statement has no effect Note test
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #1967 +/- ##
==========================================
+ Coverage 75.13% 77.04% +1.90%
==========================================
Files 265 265
Lines 28907 30164 +1257
Branches 3331 3336 +5
==========================================
+ Hits 21720 23239 +1519
+ Misses 6158 5903 -255
+ Partials 1029 1022 -7 ☔ View full report in Codecov by Sentry. |
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lintrunner found more than 20 potential problems in the proposed changes. Check the Files changed tab for more details.
titaiwangms
requested review from
justinchuby,
xadupre,
gramalingam and
titaiwangms
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@microsoft-github-policy-service agree |
Hi, I used cover-agent to write the tests for this PR. It uses an AI-based workflow to add new test cases that increase code coverage.
All AI-generated tests have met these four essential criteria:
Increased Coverage
Why adding unit tests is important
Writing and maintaining unit tests can be tedious, especially as codebases grow larger
Despite this challenge, unit tests provide key benefits:
Tests serve as executable documentation by: