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Autograd attaches logging hooks only in debug level (#116522)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/116522 Approved by: https://github.com/albanD
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@ -7,7 +7,7 @@ from torch.testing._internal.logging_utils import LoggingTestCase, make_logging_
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class TestAutogradLogging(LoggingTestCase):
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class TestAutogradLogging(LoggingTestCase):
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@make_logging_test(autograd=logging.INFO)
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@make_logging_test(autograd=logging.DEBUG)
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def test_logging(self, records):
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def test_logging(self, records):
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a = torch.rand(10, requires_grad=True)
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a = torch.rand(10, requires_grad=True)
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b = a.mul(2).div(3).sum()
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b = a.mul(2).div(3).sum()
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@ -660,7 +660,7 @@ def _register_logging_hooks_on_whole_graph(t_outputs: List[torch.Tensor]):
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def prehook(grad_output):
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def prehook(grad_output):
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node = torch._C._current_autograd_node()
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node = torch._C._current_autograd_node()
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log_str = f"Executing: {node} with grad_output: {grad_output}"
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log_str = f"Executing: {node} with grad_output: {grad_output}"
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log.info(log_str)
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log.debug(log_str)
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handles = []
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handles = []
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for node in iter_graph(grad_fns):
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for node in iter_graph(grad_fns):
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@ -674,7 +674,7 @@ def _register_logging_hooks_on_whole_graph(t_outputs: List[torch.Tensor]):
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def _engine_run_backward(t_outputs, *args, **kwargs):
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def _engine_run_backward(t_outputs, *args, **kwargs):
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attach_logging_hooks = log.getEffectiveLevel() <= logging.INFO
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attach_logging_hooks = log.getEffectiveLevel() <= logging.DEBUG
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if attach_logging_hooks:
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if attach_logging_hooks:
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unregister_hooks = _register_logging_hooks_on_whole_graph(t_outputs)
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unregister_hooks = _register_logging_hooks_on_whole_graph(t_outputs)
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try:
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try:
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