reduce parity to 0.22
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@ -12,7 +12,7 @@ from tests.base.models import ParityModuleMNIST, ParityModuleRNN
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# TODO: explore where the time leak comes from
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@pytest.mark.parametrize('cls_model,max_diff', [
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(ParityModuleRNN, 0.05),
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(ParityModuleMNIST, 0.99)
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(ParityModuleMNIST, 0.22)
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])
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@pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires GPU machine")
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def test_pytorch_parity(tmpdir, cls_model, max_diff):
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@ -117,8 +117,8 @@ def test__validation_step__step_end__epoch_end__log(tmpdir):
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def validation_step_end(self, acc):
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self.validation_step_end_called = True
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#self.log('e', acc)
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#self.log('f', acc, on_step=True, on_epoch=True)
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# self.log('e', acc)
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# self.log('f', acc, on_step=True, on_epoch=True)
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return ['random_thing']
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def validation_epoch_end(self, outputs):
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@ -151,10 +151,10 @@ def test__validation_step__step_end__epoch_end__log(tmpdir):
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'd_step/epoch_0',
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'd_step/epoch_1',
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'd_epoch',
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#'e',
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#'f_step/epoch_0',
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#'f_step/epoch_1',
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#'f_epoch',
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# 'e',
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# 'f_step/epoch_0',
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# 'f_step/epoch_1',
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# 'f_epoch',
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'g',
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}
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assert expected_logged_metrics == logged_metrics
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@ -167,7 +167,7 @@ def test__validation_step__step_end__epoch_end__log(tmpdir):
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callback_metrics = set(trainer.callback_metrics.keys())
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callback_metrics.remove('debug_epoch')
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expected_cb_metrics = {'a', 'b', 'b_epoch', 'c', 'd', 'd_epoch', 'g', 'b_step'}
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#expected_cb_metrics = {'a', 'b', 'c', 'd', 'e', 'b_epoch', 'd_epoch', 'f_epoch', 'f', 'g', 'b_step'}
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# expected_cb_metrics = {'a', 'b', 'c', 'd', 'e', 'b_epoch', 'd_epoch', 'f_epoch', 'f', 'g', 'b_step'}
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assert expected_cb_metrics == callback_metrics
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