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fastNLP.component.bert\_tokenizer module
========================================
.. automodule:: fastNLP.component.bert_tokenizer
:members:
:undoc-members:
:show-inheritance:

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fastNLP.component package
=========================
.. automodule:: fastNLP.component
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
fastNLP.component.bert_tokenizer

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fastNLP.core.batch module
=========================
.. automodule:: fastNLP.core.batch
:members:
:undoc-members:
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fastNLP.core.callback module
============================
.. automodule:: fastNLP.core.callback
:members:
:undoc-members:
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fastNLP.core.const module
=========================
.. automodule:: fastNLP.core.const
:members:
:undoc-members:
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fastNLP.core.dataset module
===========================
.. automodule:: fastNLP.core.dataset
:members:
:undoc-members:
:show-inheritance:

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fastNLP.core.field module
=========================
.. automodule:: fastNLP.core.field
:members:
:undoc-members:
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fastNLP.core.instance module
============================
.. automodule:: fastNLP.core.instance
:members:
:undoc-members:
:show-inheritance:

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fastNLP.core.losses module
==========================
.. automodule:: fastNLP.core.losses
:members:
:undoc-members:
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fastNLP.core.metrics module
===========================
.. automodule:: fastNLP.core.metrics
:members:
:undoc-members:
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fastNLP.core.optimizer module
=============================
.. automodule:: fastNLP.core.optimizer
:members:
:undoc-members:
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fastNLP.core package
====================
.. automodule:: fastNLP.core
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
fastNLP.core.batch
fastNLP.core.callback
fastNLP.core.const
fastNLP.core.dataset
fastNLP.core.field
fastNLP.core.instance
fastNLP.core.losses
fastNLP.core.metrics
fastNLP.core.optimizer
fastNLP.core.sampler
fastNLP.core.tester
fastNLP.core.trainer
fastNLP.core.utils
fastNLP.core.vocabulary

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fastNLP.core.sampler module
===========================
.. automodule:: fastNLP.core.sampler
:members:
:undoc-members:
:show-inheritance:

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fastNLP.core.tester module
==========================
.. automodule:: fastNLP.core.tester
:members:
:undoc-members:
:show-inheritance:

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fastNLP.core.trainer module
===========================
.. automodule:: fastNLP.core.trainer
:members:
:undoc-members:
:show-inheritance:

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fastNLP.core.utils module
=========================
.. automodule:: fastNLP.core.utils
:members:
:undoc-members:
:show-inheritance:

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fastNLP.core.vocabulary module
==============================
.. automodule:: fastNLP.core.vocabulary
:members:
:undoc-members:
:show-inheritance:

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fastNLP.io.base\_loader module
==============================
.. automodule:: fastNLP.io.base_loader
:members:
:undoc-members:
:show-inheritance:

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fastNLP.io.config\_io module
============================
.. automodule:: fastNLP.io.config_io
:members:
:undoc-members:
:show-inheritance:

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fastNLP.io.dataset\_loader module
=================================
.. automodule:: fastNLP.io.dataset_loader
:members:
:undoc-members:
:show-inheritance:

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fastNLP.io.embed\_loader module
===============================
.. automodule:: fastNLP.io.embed_loader
:members:
:undoc-members:
:show-inheritance:

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fastNLP.io.file\_reader module
==============================
.. automodule:: fastNLP.io.file_reader
:members:
:undoc-members:
:show-inheritance:

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fastNLP.io.model\_io module
===========================
.. automodule:: fastNLP.io.model_io
:members:
:undoc-members:
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fastNLP.io package
==================
.. automodule:: fastNLP.io
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
fastNLP.io.base_loader
fastNLP.io.config_io
fastNLP.io.dataset_loader
fastNLP.io.embed_loader
fastNLP.io.file_reader
fastNLP.io.model_io

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fastNLP.models.base\_model module
=================================
.. automodule:: fastNLP.models.base_model
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.bert module
==========================
.. automodule:: fastNLP.models.bert
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.biaffine\_parser module
======================================
.. automodule:: fastNLP.models.biaffine_parser
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.char\_language\_model module
===========================================
.. automodule:: fastNLP.models.char_language_model
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.cnn\_text\_classification module
===============================================
.. automodule:: fastNLP.models.cnn_text_classification
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.enas\_controller module
======================================
.. automodule:: fastNLP.models.enas_controller
:members:
:undoc-members:
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fastNLP.models.enas\_model module
=================================
.. automodule:: fastNLP.models.enas_model
:members:
:undoc-members:
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fastNLP.models.enas\_trainer module
===================================
.. automodule:: fastNLP.models.enas_trainer
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.enas\_utils module
=================================
.. automodule:: fastNLP.models.enas_utils
:members:
:undoc-members:
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fastNLP.models package
======================
.. automodule:: fastNLP.models
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
fastNLP.models.base_model
fastNLP.models.bert
fastNLP.models.biaffine_parser
fastNLP.models.char_language_model
fastNLP.models.cnn_text_classification
fastNLP.models.enas_controller
fastNLP.models.enas_model
fastNLP.models.enas_trainer
fastNLP.models.enas_utils
fastNLP.models.sequence_modeling
fastNLP.models.snli
fastNLP.models.star_transformer

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fastNLP.models.sequence\_modeling module
========================================
.. automodule:: fastNLP.models.sequence_modeling
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.snli module
==========================
.. automodule:: fastNLP.models.snli
:members:
:undoc-members:
:show-inheritance:

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fastNLP.models.star\_transformer module
=======================================
.. automodule:: fastNLP.models.star_transformer
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.aggregator.attention module
===========================================
.. automodule:: fastNLP.modules.aggregator.attention
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.aggregator.pooling module
=========================================
.. automodule:: fastNLP.modules.aggregator.pooling
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.aggregator package
==================================
.. automodule:: fastNLP.modules.aggregator
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
fastNLP.modules.aggregator.attention
fastNLP.modules.aggregator.pooling

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fastNLP.modules.decoder.CRF module
==================================
.. automodule:: fastNLP.modules.decoder.CRF
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.decoder.MLP module
==================================
.. automodule:: fastNLP.modules.decoder.MLP
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.decoder package
===============================
.. automodule:: fastNLP.modules.decoder
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
fastNLP.modules.decoder.CRF
fastNLP.modules.decoder.MLP
fastNLP.modules.decoder.utils

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fastNLP.modules.decoder.utils module
====================================
.. automodule:: fastNLP.modules.decoder.utils
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.dropout module
==============================
.. automodule:: fastNLP.modules.dropout
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.encoder.bert module
===================================
.. automodule:: fastNLP.modules.encoder.bert
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.encoder.char\_encoder module
============================================
.. automodule:: fastNLP.modules.encoder.char_encoder
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.encoder.conv\_maxpool module
============================================
.. automodule:: fastNLP.modules.encoder.conv_maxpool
:members:
:undoc-members:
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fastNLP.modules.encoder.embedding module
========================================
.. automodule:: fastNLP.modules.encoder.embedding
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.encoder.linear module
=====================================
.. automodule:: fastNLP.modules.encoder.linear
:members:
:undoc-members:
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fastNLP.modules.encoder.lstm module
===================================
.. automodule:: fastNLP.modules.encoder.lstm
:members:
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fastNLP.modules.encoder package
===============================
.. automodule:: fastNLP.modules.encoder
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
fastNLP.modules.encoder.bert
fastNLP.modules.encoder.char_encoder
fastNLP.modules.encoder.conv_maxpool
fastNLP.modules.encoder.embedding
fastNLP.modules.encoder.linear
fastNLP.modules.encoder.lstm
fastNLP.modules.encoder.star_transformer
fastNLP.modules.encoder.transformer
fastNLP.modules.encoder.variational_rnn

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fastNLP.modules.encoder.star\_transformer module
================================================
.. automodule:: fastNLP.modules.encoder.star_transformer
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.encoder.transformer module
==========================================
.. automodule:: fastNLP.modules.encoder.transformer
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.encoder.variational\_rnn module
===============================================
.. automodule:: fastNLP.modules.encoder.variational_rnn
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules.other\_modules module
=====================================
.. automodule:: fastNLP.modules.other_modules
:members:
:undoc-members:
:show-inheritance:

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fastNLP.modules package
=======================
.. automodule:: fastNLP.modules
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
.. toctree::
fastNLP.modules.aggregator
fastNLP.modules.decoder
fastNLP.modules.encoder

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fastNLP.modules.utils module
============================
.. automodule:: fastNLP.modules.utils
:members:
:undoc-members:
:show-inheritance:

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fastNLP package
===============
.. automodule:: fastNLP
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
.. toctree::
fastNLP.component
fastNLP.core
fastNLP.io
fastNLP.models
fastNLP.modules

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fastNLP documentation
fastNLP 中文文档
=====================
A Modularized and Extensible Toolkit for Natural Language Processing. Currently still in incubation.
fastNLP 是一款轻量级的 NLP 处理套件。你既可以使用它快速地完成一个命名实体识别（NER）、中文分词或文本分类任务；
也可以使用他构建许多复杂的网络模型，进行科研。它具有如下的特性:
Introduction
- 代码简洁易懂，有着详尽的中文文档以供查阅；
- 深度学习的各个阶段划分明确，配合 fitlog 使用让科研更轻松；
- 内置多种常见模型 （TODO）；
- 基于 PyTorch ，方便从原生 PyTorch 代码迁入，并能使用 PyTorch 中的各种组件；
- 便于 seq2seq；
- 便于 fine-tune
内置的模块
------------
FastNLP is a modular Natural Language Processing system based on
PyTorch, built for fast development of NLP models.
（TODO）
A deep learning NLP model is the composition of three types of modules:
@ -33,31 +41,41 @@ For example:
各个任务上的结果
-----------------------
User's Guide
------------
.. toctree::
:maxdepth: 2
（TODO）
user/installation
user/quickstart
API Reference
快速入门
-------------
If you are looking for information on a specific function, class or
method, this part of the documentation is for you.
TODO
用户手册
---------------
.. toctree::
:maxdepth: 1
安装指南 <user/installation>
快速入门 <user/quickstart>
使用 fastNLP 分类 <user/task1>
使用 fastNLP 分词 <user/task2>
API 文档
-------------
除了用户手册之外，你还可以通过查阅 API 文档来找到你所需要的工具。
.. toctree::
:maxdepth: 2
fastNLP API <fastNLP>
fastNLP
Indices and tables
索引与搜索
==================
* :ref:`genindex`

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fastNLP
=======
.. toctree::
:maxdepth: 4
fastNLP

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============
Installation
============
===============
安装指南
===============
.. contents::
:local:
Make sure your environment satisfies https://github.com/fastnlp/fastNLP/blob/master/requirements.txt .
fastNLP 依赖如下包::
Run the following commands to install fastNLP package:
torch>=0.4.0
numpy
tensorboardX
tqdm
nltk
.. code:: shell
pip install fastNLP
其中torch的安装可能与操作系统及 CUDA 的版本相关，请参见 `PyTorch 官网 <https://pytorch.org/get-started/locally/>`_ 。
在依赖包安装完成的情况，您可以在命令行执行如下指令完成安装
.. code:: shell
>>> pip install fitlog

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Quickstart
==========
.. toctree::
:maxdepth: 1
../tutorials/fastnlp_1_minute_tutorial
../tutorials/fastnlp_10tmin_tutorial
../tutorials/fastnlp_advanced_tutorial
../tutorials/fastnlp_developer_guide
===============
快速入门
===============

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=====================
用 fastNLP 分词
=====================

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fastNLP/__init__.py
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"""
fastNLP 由 :mod:`~fastNLP.core` 、 :mod:`~fastNLP.io` 、:mod:`~fastNLP.modules` 等子模块组成，但常用的组件都可以直接 import ，常用组件如下：
fastNLP 由 :mod:`~fastNLP.core` 、 :mod:`~fastNLP.io` 、:mod:`~fastNLP.modules`、:mod:`~fastNLP.models`
和 :mod:`~fastNLP.component` 等子模块组成。
- :mod:`~fastNLP.core` fastNLP 的核心模块，包括 DataSet、 Trainer、 Tester 等组件
- :mod:`~fastNLP.io` fastNLP 的输入输出模块，实现了数据集的读取，模型的存取等功能
- :mod:`~fastNLP.modules` TODO 如何介绍
- :mod:`~fastNLP.models` 使用 fastNLP 实现的一些常见模型，具体参见 :doc:`fastNLP.models`
- :mod:`~fastNLP.component` TODO
fastNLP 中最常用的组件可以直接从 fastNLP 包中 import ，他们的文档如下：
"""
__all__ = ["Instance", "FieldArray", "Batch", "Vocabulary", "DataSet",
"Trainer", "Tester", "Callback",

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"""
使用 fastNLP 实现的一系列常见模型，具体有：
TODO 详细介绍的表格，与主页相对应
"""
from .base_model import BaseModel
from .biaffine_parser import BiaffineParser, GraphParser
from .char_language_model import CharLM

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fastNLP/models/cnn_text_classification.py
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@ -12,6 +12,14 @@ class CNNText(torch.nn.Module):
"""
使用CNN进行文本分类的模型
'Yoon Kim. 2014. Convolution Neural Networks for Sentence Classification.'
:param tuple(int,int),torch.FloatTensor,nn.Embedding,numpy.ndarray init_embed: Embedding的大小(传入tuple(int, int),
第一个int为vocab_zie, 第二个int为embed_dim); 如果为Tensor, Embedding, ndarray等则直接使用该值初始化Embedding
:param int num_classes: 一共有多少类
:param int,tuple(int) out_channels: 输出channel的数量。如果为list，则需要与kernel_sizes的数量保持一致
:param int,tuple(int) kernel_sizes: 输出channel的kernel大小。
:param int padding:
:param float dropout: Dropout的大小
"""
def __init__(self, init_embed,
@ -20,16 +28,6 @@ class CNNText(torch.nn.Module):
kernel_sizes=(3, 4, 5),
padding=0,
dropout=0.5):
"""
:param tuple(int,int),torch.FloatTensor,nn.Embedding,numpy.ndarray init_embed: Embedding的大小(传入tuple(int, int),
第一个int为vocab_zie, 第二个int为embed_dim); 如果为Tensor, Embedding, ndarray等则直接使用该值初始化Embedding
:param int num_classes: 一共有多少类
:param int,tuple(int) out_channels: 输出channel的数量。如果为list，则需要与kernel_sizes的数量保持一致
:param int,tuple(int) kernel_sizes: 输出channel的kernel大小。
:param int padding:
:param float dropout: Dropout的大小
"""
super(CNNText, self).__init__()
# no support for pre-trained embedding currently

14
fastNLP/modules/__init__.py
View File

@ -1,13 +1,19 @@
"""
modules 模块是 fastNLP 的重要组成部分，它实现了神经网络构建中常见的组件，
具体包括 TODO
可以和 PyTorch 结合使用？TODO
TODO __all__ 里面多暴露一些
"""
from . import aggregator
from . import decoder
from . import encoder
from .aggregator import *
from .decoder import *
from .other_modules import *
from .dropout import TimestepDropout
from .encoder import *
__version__ = '0.0.0'
__all__ = ['encoder',
'decoder',
'aggregator']

3
fastNLP/modules/aggregator/__init__.py
View File

@ -1,3 +1,5 @@
__all__ = ["MaxPool", "MaxPoolWithMask", "AvgPool", "MeanPoolWithMask", "KMaxPool", "Attention", "BiAttention",
"SelfAttention"]
from .pooling import MaxPool
from .pooling import MaxPoolWithMask
from .pooling import AvgPool
@ -7,4 +9,3 @@ from .pooling import KMaxPool
from .attention import Attention
from .attention import BiAttention
from .attention import SelfAttention

6
fastNLP/modules/aggregator/attention.py
View File

@ -117,11 +117,11 @@ class BiAttention(nn.Module):
.. math::
\begin{array}{ll} \\
e_ij = {a}^{\mathbf{T}}_{i}{b}_{j} \\
\\begin{array}{ll} \\\\
e_ij = {a}^{\\mathbf{T}}_{i}{b}_{j} \\\\
a_i =
b_j =
\end{array}
\\end{array}
"""

21
fastNLP/modules/decoder/CRF.py
View File

@ -144,18 +144,19 @@ def _is_transition_allowed(encoding_type, from_tag, from_label, to_tag, to_label
class ConditionalRandomField(nn.Module):
"""条件随机场。
提供forward()以及viterbi_decode()两个方法，分别用于训练与inference。
:param int num_tags: 标签的数量
:param bool include_start_end_trans: 是否考虑各个tag作为开始以及结尾的分数。
:param List[Tuple[from_tag_id(int), to_tag_id(int)]] allowed_transitions: 内部的Tuple[from_tag_id(int),
to_tag_id(int)]视为允许发生的跃迁，其他没有包含的跃迁认为是禁止跃迁，可以通过
allowed_transitions()函数得到；如果为None，则所有跃迁均为合法
:param str initial_method: 初始化方法。见initial_parameter
"""
def __init__(self, num_tags, include_start_end_trans=False, allowed_transitions=None,
initial_method=None):
"""条件随机场。
提供forward()以及viterbi_decode()两个方法，分别用于训练与inference。
:param int num_tags: 标签的数量
:param bool include_start_end_trans: 是否考虑各个tag作为开始以及结尾的分数。
:param List[Tuple[from_tag_id(int), to_tag_id(int)]] allowed_transitions: 内部的Tuple[from_tag_id(int),
to_tag_id(int)]视为允许发生的跃迁，其他没有包含的跃迁认为是禁止跃迁，可以通过
allowed_transitions()函数得到；如果为None，则所有跃迁均为合法
:param str initial_method: 初始化方法。见initial_parameter
"""
super(ConditionalRandomField, self).__init__()
self.include_start_end_trans = include_start_end_trans

1
fastNLP/modules/decoder/__init__.py
View File

@ -1,2 +1,3 @@
__all__ = ["MLP", "ConditionalRandomField"]
from .CRF import ConditionalRandomField
from .MLP import MLP