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Added example and description about numpy_function() in Dataset.map() #37853

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merged 4 commits into from Apr 2, 2020
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Added example and description about numpy_function() in Dataset.map() #37853

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Added example and description about numpy_function() in Dataset.map()
ashutosh1919 Mar 24, 2020
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changed descriptions
ashutosh1919 Mar 25, 2020
31eda22
Added description
ashutosh1919 Apr 1, 2020
16cc300
Update tensorflow/python/data/ops/dataset_ops.py
mihaimaruseac Apr 2, 2020
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13 changes: 13 additions & 0 deletions tensorflow/python/data/ops/dataset_ops.py
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Expand Up @@ -1619,6 +1619,19 @@ def map(self, map_func, num_parallel_calls=None, deterministic=None):
>>> list(d.as_numpy_iterator())
[b'HELLO', b'WORLD']

3) Use `tf.numpy_function`, which also allows you to write arbitrary
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Python code. Note here that `tf.py_function` accepts `tf.Tensor` whereas
`tf.numpy_function` accepts numpy arrays and returns only numpy arrays.
For example:

>>> d = tf.data.Dataset.from_tensor_slices(['hello', 'world'])
>>> def upper_case_fn(t: np.ndarray):
... return t.decode('utf-8').upper()
>>> d = d.map(lambda x: tf.numpy_function(func=upper_case_fn,
... inp=[x], Tout=tf.string))
>>> list(d.as_numpy_iterator())
[b'HELLO', b'WORLD']

Performance can often be improved by setting `num_parallel_calls` so that
`map` will use multiple threads to process elements. If deterministic order
isn't required, it can also improve performance to set
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