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More detailed error message in _DirectedInterleaveDataset.

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PiperOrigin-RevId: 357287671
Change-Id: Idfe3a07dbbc3bd1aaa7dc7a9590c5d26857eea4b
This commit is contained in:
Jonathan Shen 2021-02-12 16:13:40 -08:00 committed by TensorFlower Gardener
parent 96d508eb5b
commit 454d8c51cb
1 changed files with 8 additions and 2 deletions
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10
tensorflow/python/data/experimental/ops/interleave_ops.py
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@ -111,11 +111,17 @@ class _DirectedInterleaveDataset(dataset_ops.DatasetV2):
first_output_types = dataset_ops.get_legacy_output_types(data_inputs[0])
first_output_classes = dataset_ops.get_legacy_output_classes(data_inputs[0])
for data_input in data_inputs[1:]:
for i, data_input in enumerate(data_inputs[1:]):
if (dataset_ops.get_legacy_output_types(data_input) != first_output_types
or dataset_ops.get_legacy_output_classes(data_input)
!= first_output_classes):
raise TypeError("All datasets must have the same type and class.")
raise TypeError("All datasets must have the same type and class.\n"
"dataset 0 vs dataset %s types: %s ; %s\n"
"classes: %s ; %s" %
(i + 1, first_output_types,
dataset_ops.get_legacy_output_types(data_input),
first_output_classes,
dataset_ops.get_legacy_output_classes(data_input)))
output_shapes = dataset_ops.get_legacy_output_shapes(self._data_inputs[0])
for data_input in self._data_inputs[1:]: