def enumerate_dataset(start=0):
"""A transformation that enumerate the elements of a dataset.
It is Similar to python's `enumerate`.
For example:
```python
# NOTE: The following examples use `{ ... }` to represent the
# contents of a dataset.
a = { 1, 2, 3 }
b = { (7, 8), (9, 10) }
# The nested structure of the `datasets` argument determines the
# structure of elements in the resulting dataset.
a.apply(tf.contrib.data.enumerate(start=5)) == { (5, 1), (6, 2), (7, 3) }
b.apply(tf.contrib.data.enumerate()) == { (0, (7, 8)), (1, (9, 10)) }
```
Args:
start: A `tf.int64` scalar `tf.Tensor`, representing the start
value for enumeration.
Returns:
A `Dataset` transformation function, which can be passed to
`tf.data.Dataset.apply`.
"""
return enumerate_ops.enumerate_dataset(start)
def enumerate_dataset(start=0):
"""A transformation that enumerate the elements of a dataset.
It is Similar to python's `enumerate`.
For example:
```python
# NOTE: The following examples use `{ ... }` to represent the
# contents of a dataset.
a = { 1, 2, 3 }
b = { (7, 8), (9, 10) }
# The nested structure of the `datasets` argument determines the
# structure of elements in the resulting dataset.
a.apply(tf.contrib.data.enumerate(start=5)) == { (5, 1), (6, 2), (7, 3) }
b.apply(tf.contrib.data.enumerate()) == { (0, (7, 8)), (1, (9, 10)) }
```
Args:
start: A `tf.int64` scalar `tf.Tensor`, representing the start
value for enumeration.
Returns:
A `Dataset` transformation function, which can be passed to
`tf.data.Dataset.apply`.
"""
return enumerate_ops.enumerate_dataset(start)
def testEnumerateDataset(self):
components = (["a", "b"], [1, 2], [37.0, 38])
start = constant_op.constant(20, dtype=dtypes.int64)
dataset = dataset_ops.Dataset.from_tensor_slices(components).apply(
enumerate_ops.enumerate_dataset(start))
self.assertEqual(dtypes.int64, dataset.output_types[0])
self.assertEqual((), dataset.output_shapes[0])
self.assertEqual([tensor_shape.TensorShape([])] * 3,
[shape for shape in dataset.output_shapes[1]])
self.assertDatasetProduces(dataset, [(20, (b"a", 1, 37.0)),
(21, (b"b", 2, 38.0))])
def testEnumerateDataset(self):
components = (["a", "b"], [1, 2], [37.0, 38])
start = constant_op.constant(20, dtype=dtypes.int64)
iterator = (dataset_ops.Dataset.from_tensor_slices(components).apply(
enumerate_ops.enumerate_dataset(start)).make_initializable_iterator())
init_op = iterator.initializer
get_next = iterator.get_next()
self.assertEqual(dtypes.int64, get_next[0].dtype)
self.assertEqual((), get_next[0].shape)
self.assertEqual([tensor_shape.TensorShape([])] * 3,
[t.shape for t in get_next[1]])
with self.cached_session() as sess:
self.evaluate(init_op)
self.assertEqual((20, (b"a", 1, 37.0)), self.evaluate(get_next))
self.assertEqual((21, (b"b", 2, 38.0)), self.evaluate(get_next))
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)