2017-02-17 10:06:59 -08:00
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# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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2020-11-24 14:53:51 +08:00
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r"""
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2017-03-05 12:07:39 +08:00
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At training and testing time, PaddlePaddle programs need to read data. To ease
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the users' work to write data reading code, we define that
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2017-02-17 10:06:59 -08:00
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2017-03-05 12:07:39 +08:00
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- A *reader* is a function that reads data (from file, network, random number
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generator, etc) and yields data items.
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- A *reader creator* is a function that returns a reader function.
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- A *reader decorator* is a function, which accepts one or more readers, and
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returns a reader.
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- A *batch reader* is a function that reads data (from *reader*, file, network,
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random number generator, etc) and yields a batch of data items.
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#####################
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Data Reader Interface
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#####################
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Indeed, *data reader* doesn't have to be a function that reads and yields data
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items. It can be any function with no parameter that creates a iterable
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(anything can be used in :code:`for x in iterable`)\:
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2026-02-01 04:28:50 +08:00
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.. code-block:: pycon
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2017-03-05 12:07:39 +08:00
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2023-08-30 10:37:35 +08:00
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>>> iterable = data_reader()
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2017-03-05 12:07:39 +08:00
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Element produced from the iterable should be a **single** entry of data,
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**not** a mini batch. That entry of data could be a single item, or a tuple of
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items.
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2022-09-14 21:56:19 +08:00
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Item should be of supported type (e.g., numpy array or list/tuple of float
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or int).
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2017-03-05 12:07:39 +08:00
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An example implementation for single item data reader creator:
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2026-02-01 04:28:50 +08:00
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.. code-block:: pycon
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2017-03-05 12:07:39 +08:00
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2023-08-30 10:37:35 +08:00
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>>> def reader_creator_random_image(width, height):
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... def reader():
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... while True:
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2026-02-01 04:28:50 +08:00
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... yield numpy.random.uniform(-1, 1, size=width * height)
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...
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2023-08-30 10:37:35 +08:00
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... return reader
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2017-03-05 12:07:39 +08:00
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An example implementation for multiple item data reader creator:
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2026-02-01 04:28:50 +08:00
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.. code-block:: pycon
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2017-03-05 12:07:39 +08:00
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2023-08-30 10:37:35 +08:00
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>>> def reader_creator_random_image_and_label(width, height, label):
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... def reader():
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... while True:
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2026-02-01 04:28:50 +08:00
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... yield numpy.random.uniform(-1, 1, size=width * height), label
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...
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2023-08-30 10:37:35 +08:00
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... return reader
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2017-03-05 12:07:39 +08:00
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"""
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2023-11-07 11:14:06 +08:00
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from paddle.reader.decorator import ( # noqa: F401
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ComposeNotAligned,
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buffered,
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cache,
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chain,
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compose,
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firstn,
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map_readers,
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multiprocess_reader,
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shuffle,
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xmap_readers,
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)
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2017-02-22 15:34:36 -08:00
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2020-09-22 13:19:18 +08:00
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__all__ = []
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