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How to use _check_fn method in pandera

Best Python code snippet using pandera_python

data_test.py

Source:data_test.py

...91        **kwargs))92    iterator = self._iterDataset(dataset)93    check_fn(iterator)94  def testBatchTrainDatasetSimple(self):95    def _check_fn(iterator):96      features, labels = next(iterator)97      self.assertEqual(64, features.shape[0])98    self._testBatchTrainDataset(_check_fn, 64)99  def testBatchTrainDatasetMultiplier(self):100    def _check_fn(iterator):101      features, labels = next(iterator)102      self.assertEqual(30, features.shape[0])103    self._testBatchTrainDataset(_check_fn, 10, batch_multiplier=3)104  def testBatchTrainDatasetMultiple(self):105    def _check_fn(iterator):106      features, labels = next(iterator)107      self.assertEqual(features.shape[0] % 3, 0)108    self._testBatchTrainDataset(109        _check_fn,110        1024,111        batch_type="tokens",112        batch_size_multiple=3,113        bucket_width=10)114  def testBatchTrainDatasetBucket(self):115    def _check_fn(iterator):116      for _ in range(20):117        features, labels = next(iterator)118        length = [max(f, l) for f, l in zip(features, labels)]119        self.assertGreater(3, max(length) - min(length))120        self.assertGreaterEqual(64, features.shape[0])121    self._testBatchTrainDataset(_check_fn, 64, bucket_width=3)122  def testBatchTrainDatasetTokens(self):123    def _check_fn(iterator):124      for _ in range(20):125        features, labels = next(iterator)126        batch_size = features.shape[0]127        max_length = max(list(features) + list(labels))128        self.assertGreaterEqual(256, batch_size * max_length)129    self._testBatchTrainDataset(_check_fn, 256, batch_type="tokens", bucket_width=1)130  def testReorderInferDataset(self):131    dataset = tf.data.Dataset.from_tensor_slices([8, 2, 5, 6, 7, 1, 3, 9])132    dataset = dataset.map(lambda x: {"length": x})133    dataset = data.inference_pipeline(134        dataset, 3, bucket_width=3, length_fn=lambda x: x["length"])135    elements = list(self._iterDataset(dataset))136    def _check_element(element, length, index):137      self.assertAllEqual(element["length"], length)...

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