【Tensorflow+Keras】tf.keras.layers.Bidirectional()的解析与使用

缺乏、安全感 2022-11-19 11:29 315阅读 0赞

# 1 作用 #

实现RNN类型神经网络的双向构造  
RNN类型神经网络比如LSTM、GRU等等

# 2 参数 #

> tf.keras.layers.Bidirectional(  
> layer,  
> merge\_mode=‘concat’,  
> weights=None,  
> backward\_layer=None  
> )

*  layer 神经网络，如RNN、LSTM、GRU
 *  merge\_mode 前向和后向RNN的输出将被组合的模式。\{‘sum’，‘mul’，‘concat’，‘ave’，None\}中的一个。如果为None，则将不合并输出，它们将作为列表返回。默认值为“ concat”。
 *  weights
 *  backward\_layer 处理向后输入处理的神经网络，如果未提供，则作为参数传递的图层实例 将用于自动生成后向图层

***注意***

> *该层的调用参数与包装的RNN层的调用参数相同。请注意，在initial\_state此层的调用期间传递参数时，列表中元素列表的前半部分initial\_state 将传递给正向RNN调用，而元素列表中的后半部分将传递给后向RNN调用。*

# 3 举例使用 #

[三十个tf.keras.layers.Bidirectional的例子][tf.keras.layers.Bidirectional]  
导入模块和定义参数

import numpy as np
    from tensorflow import keras
    from tensorflow.keras import layers
    
    max_features = 20000  # Only consider the top 20k words
    maxlen = 200  # Only consider the first 200 words of each movie review

构建模型

# Input for variable-length sequences of integers
    inputs = keras.Input(shape=(None,), dtype="int32")
    # Embed each integer in a 128-dimensional vector
    x = layers.Embedding(max_features, 128)(inputs)
    # Add 2 bidirectional LSTMs
    x = layers.Bidirectional(layers.LSTM(64, return_sequences=True))(x)
    x = layers.Bidirectional(layers.LSTM(64))(x)
    # Add a classifier
    outputs = layers.Dense(1, activation="sigmoid")(x)
    model = keras.Model(inputs, outputs)
    model.summary()

加载数据集

(x_train, y_train), (x_val, y_val) = keras.datasets.imdb.load_data(
        num_words=max_features
    )
    print(len(x_train), "Training sequences")
    print(len(x_val), "Validation sequences")
    x_train = keras.preprocessing.sequence.pad_sequences(x_train, maxlen=maxlen)
    x_val = keras.preprocessing.sequence.pad_sequences(x_val, maxlen=maxlen)

训练和评估模型

model.compile("adam", "binary_crossentropy", metrics=["accuracy"])
    model.fit(x_train, y_train, batch_size=32, epochs=2, validation_data=(x_val, y_val))

[tf.keras.layers.Bidirectional]: https://vimsky.com/zh-tw/examples/detail/python-method-keras.layers.Bidirectional.html