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user guides index of all (#595)

上级 9b58632c
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:maxdepth: 1
beginners_guide/index_en.rst
user_guides/index_en.rst
design/index_en.rst
howto/index_en.rst
dev/index_en.rst
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###############
Basic Concepts
###############
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.
.. toctree::
:hidden:
lod_tensor_en.rst
###############################
Model Evaluation and Debugging
###############################
There are two articles in this section:
- `Model Evaluation <../evaluation_and_debugging/evaluation/metrics_en.html>`_:This section will introduce the construction of common metrics.
- `Visual DL <../evaluation_and_debugging/debug/visualdl_en.html>`_:How to use Visual DL to visualise training process.
.. toctree::
:hidden:
evaluation/metrics_en.rst
debug/visualdl_en.md
.. _user_guide_prepare_data_en:
#############
Prepare Data
#############
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.
Comparisons of the two methods:
========================= ==================================================== ===============================================
Aspects Synchronous Python Reader Asynchronous py_reader
========================= ==================================================== ===============================================
API interface :code:`executor.run(feed=...)` :code:`fluid.layers.py_reader`
data type Numpy Array Numpy Array or LoDTensor
data augmentation carried out by other libraries on Python end carried out by other libraries on Python end
velocity slow rapid
recommended applications model debugging industrial training
========================= ==================================================== ===============================================
Synchronous Python Reader
##########################
Fluid provides Python Reader to feed in 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
########################
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:
.. toctree::
:maxdepth: 1
use_py_reader_en.rst
######################
Train Neural Networks
######################
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:
.. toctree::
:maxdepth: 1
single_node_en.rst
multi_node_en.rst
save_load_variables_en.rst
####################
Multi-node Training
####################
.. toctree::
:maxdepth: 1
cluster_quick_start_en.rst
cluster_howto_en.rst
train_on_baidu_cloud_en.rst
###########
User Guides
###########
.. todo::
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>`_
.. toctree::
:hidden:
howto/basic_concept/index_en.rst
howto/prepare_data/index_en.rst
howto/configure_simple_model/index_en.rst
howto/training/index_en.rst
howto/evaluation_and_debugging/index_en.rst
models/model12_en.rst
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