Metadata-Version: 2.1
Name: keras-crf
Version: 0.1.0
Summary: A more elegant and convenient CRF built on tensorflow-addons.
Home-page: https://github.com/luozhouyang/keras-crf
Author: ZhouYang Luo
Author-email: zhouyang.luo@gmail.com
License: Apache Software License
Description: # keras-crf
        
        ![Python package](https://github.com/luozhouyang/keras-crf/workflows/Python%20package/badge.svg)
        [![PyPI version](https://badge.fury.io/py/keras-crf.svg)](https://badge.fury.io/py/keras-crf)
        [![Python](https://img.shields.io/pypi/pyversions/keras-crf.svg?style=plastic)](https://badge.fury.io/py/keras-crf)
        
        A more elegant and convenient CRF built on tensorflow-addons.
        
        
        > Python Compatibility is limited to [tensorflow/addons](https://github.com/tensorflow/addons), you can check the compatibility from it's home page.
        
        ## Installation
        
        ```bash
        pip install keras-crf
        ```
        
        ## Usage
        
        Here is an example to show you how to build a CRF model easily:
        
        ```python
        import tensorflow as tf
        
        from keras_crf import CRF
        
        
        sequence_input = tf.keras.layers.Input(shape=(None,), dtype=tf.int32, name='sequence_input')
        sequence_mask = tf.keras.layers.Lambda(lambda x: tf.greater(x, 0))(sequence_input)
        outputs = tf.keras.layers.Embedding(100, 128)(sequence_input)
        outputs = tf.keras.layers.Dense(256)(outputs)
        crf = CRF(7)
        # mask is important to compute sequence length in CRF
        outputs = crf(outputs, mask=sequence_mask)
        model = tf.keras.Model(inputs=sequence_input, outputs=outputs)
        model.compile(
            loss=crf.neg_log_likelihood,
            metrics=[crf.accuracy],
            optimizer=tf.keras.optimizers.Adam(5e-5)
            )
        model.summary()
        ```
        
        The model summary:
        
        ```bash
        Model: "functional_1"
        __________________________________________________________________________________________________
        Layer (type)                    Output Shape         Param #     Connected to                     
        ==================================================================================================
        sequence_input (InputLayer)     [(None, None)]       0                                            
        __________________________________________________________________________________________________
        embedding (Embedding)           (None, None, 128)    12800       sequence_input[0][0]             
        __________________________________________________________________________________________________
        dense (Dense)                   (None, None, 256)    33024       embedding[0][0]                  
        __________________________________________________________________________________________________
        lambda (Lambda)                 (None, None)         0           sequence_input[0][0]             
        __________________________________________________________________________________________________
        crf (CRF)                       (None, None, 7)      1862        dense[0][0]                      
                                                                         lambda[0][0]                     
        ==================================================================================================
        Total params: 47,686
        Trainable params: 47,686
        Non-trainable params: 0
        __________________________________________________________________________________________________
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
