This section will introduce basic concepts in Fluid:
- `LoD-Tensor User Guide <lod_tensor_en.html>`_ : LoD-Tensor is a unique term of Fluid. It appends sequence information to Tensor,and supports data of variable lengths.
PaddlePaddle Fluid supports two methods to feed data into networks:
1. Synchronous method - Python Reader:Firstly, use :code:`fluid.layers.data` to set up data input layer. Then, feed in the training data through :code:`executor.run(feed=...)` in :code:`fluid.Executor` or :code:`fluid.ParallelExecutor` .
2. Asynchronous method - py_reader:Firstly, use :code:`fluid.layers.py_reader` to set up data input layer. Then configure the data source with functions :code:`decorate_paddle_reader` or :code:`decorate_tensor_provider` of :code:`py_reader` . After that, call :code:`fluid.layers.read_file` to read data.
Python Reader is a pure Python-side interface, and data feeding is synchronized with the model training/prediction process. Users can pass in data through Numpy Array. For specific operations, please refer to:
.. toctree::
:maxdepth: 1
feeding_data_en.rst
Python Reader supports advanced functions like group batch, shuffle. For specific operations, please refer to:
.. toctree::
:maxdepth: 1
reader.md
Asynchronous py_reader
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Fluid provides asynchronous data feeding method PyReader. It is more efficient as data feeding is not synchronized with the model training/prediction process. For specific operations, please refer to:
PaddlePaddle Fluid supports both single-node training and multi-node training. A variety of training methods are supported for each training mode. This section contains the following sections:
If you have got the hang of Beginner's Guide, and wish to model practical problems and build your original networks, this section will provide
you with some detailed operations:
- `Basic Concepts <../user_guides/howto/basic_concept/index_en.html>`_ :It explains basic concepts of Fluid.
- `Prepare Data <../user_guides/howto/prepare_data/index_en.html>`_ :This section introduces data types supported and data transmission methods when you are training your networks with Fluid.
- `Set up Simple Model <../user_guides/howto/configure_simple_model/index_en.html>`_: This section illustrates how to model practical problems and build networks with related operators of Fluid.
- `Train Neural Networks <../user_guides/howto/training/index_en.html>`_:This section will guide you to perform single-node training, multi-node training, and save or load model variables.
- `Model Evaluation and Debugging <../user_guides/howto/evaluation_and_debugging/index_en.html>`_:It introduces the model evaluation and debugging methods in Fluid
Reproduced classic models of multiple directions in Fluid:
- `Fluid Model Library <../user_guides/models/index_en.html>`_