mirror of
https://github.com/zebrajr/pytorch.git
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b40dbdc49f
Summary:
I noticed after creating https://github.com/pytorch/pytorch/issues/71553 that the test ownership lint was not working properly.
This fixes my egregious mistake and fixes the broken lints.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71554
Reviewed By: malfet
Differential Revision: D33690732
Pulled By: janeyx99
fbshipit-source-id: ba4dfbcd98038e4afd63e326832ae40935d2501e
(cherry picked from commit 1bbc3d343a)
65 lines
2.4 KiB
Python
65 lines
2.4 KiB
Python
# Owner(s): ["oncall: mobile"]
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import torch
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import torch.utils.bundled_inputs
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import io
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from torch.jit.mobile import _load_for_lite_interpreter
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from torch.testing._internal.common_utils import TestCase, run_tests
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from pathlib import Path
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from itertools import product
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pytorch_test_dir = Path(__file__).resolve().parents[1]
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class TestLiteScriptModule(TestCase):
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def _save_load_mobile_module(self, script_module: torch.jit.ScriptModule):
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buffer = io.BytesIO(script_module._save_to_buffer_for_lite_interpreter(_save_mobile_debug_info=True))
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buffer.seek(0)
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mobile_module = _load_for_lite_interpreter(buffer)
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return mobile_module
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def _try_fn(self, fn, *args, **kwargs):
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try:
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return fn(*args, **kwargs)
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except Exception as e:
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return e
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def test_versioned_div_tensor(self):
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def div_tensor_0_3(self, other):
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if self.is_floating_point() or other.is_floating_point():
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return self.true_divide(other)
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return self.divide(other, rounding_mode='trunc')
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model_path = pytorch_test_dir / "cpp" / "jit" / "upgrader_models" / "test_versioned_div_tensor_v2.ptl"
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mobile_module_v2 = _load_for_lite_interpreter(str(model_path))
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jit_module_v2 = torch.jit.load(str(model_path))
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current_mobile_module = self._save_load_mobile_module(jit_module_v2)
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vals = (2., 3., 2, 3)
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for val_a, val_b in product(vals, vals):
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a = torch.tensor((val_a,))
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b = torch.tensor((val_b,))
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def _helper(m, fn):
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m_results = self._try_fn(m, a, b)
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fn_result = self._try_fn(fn, a, b)
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if isinstance(m_results, Exception):
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self.assertTrue(isinstance(fn_result, Exception))
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else:
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for result in m_results:
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print("result: ", result)
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print("fn_result: ", fn_result)
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print(result == fn_result)
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self.assertTrue(result.eq(fn_result))
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# self.assertEqual(result, fn_result)
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# old operator should produce the same result as applying upgrader of torch.div op
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# _helper(mobile_module_v2, div_tensor_0_3)
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# latest operator should produce the same result as applying torch.div op
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# _helper(current_mobile_module, torch.div)
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if __name__ == '__main__':
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run_tests()
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