How to use transform_tail method in pandera

Best Python code snippet using pandera_python

test_decorators.py

Source:test_decorators.py

...371    ) -> DataFrame[OnlyZeroesSchema]:372        return pd.DataFrame({"a": [0, 0]})373    transform_head(df)374    @check_types(tail=1)375    def transform_tail(376        df: DataFrame[OnlyZeroesSchema],  # pylint: disable=unused-argument377    ) -> DataFrame[OnlyZeroesSchema]:378        return pd.DataFrame({"a": [1, 0]})379    transform_tail(df)380    @check_types(lazy=True)381    def transform_lazy(382        df: DataFrame[OnlyZeroesSchema],  # pylint: disable=unused-argument383    ) -> DataFrame[OnlyZeroesSchema]:384        return pd.DataFrame({"a": [1, 1]})385    with pytest.raises(errors.SchemaErrors, match="Usage Tip"):386        transform_lazy(df)387def test_check_types_unchanged() -> None:388    """Test the check_types behaviour when the dataframe is unchanged within the389    function being checked."""390    @check_types391    def transform(392        df: DataFrame[OnlyZeroesSchema],393        notused: int,  # pylint: disable=unused-argument...

cifar10.py

Source:cifar10.py

...185            ])186            img_t = self.transform_body(img)187            img_t = self.transform_tail_gray(img_t)188            transformed_imgs.append(img_t)189        img = self.transform_tail(img)190        return img, transformed_imgs, target191    def __len__(self):192        return len(self.data)193    def extra_repr(self):194        return "Split: {}".format("Train" if self.train is True else "Test")195class Rotation90:196    """Rotate 90 degrenn by given times."""197    def __init__(self, count):198        self.count = count199    def __call__(self, x):200        return TF.rotate(x, 90 * self.count)201if __name__=='__main__':202    dataset = CIFAR10(root='/home/wogong/datasets/cifar-10', train=False, download=True,class_id=0)203    dataloader = torch.utils.data.DataLoader(dataset, batch_size=32, shuffle=True, num_workers=1)...

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