TCN代码keras版本

以下是一个基于Keras实现的TCN代码示例：

from keras.layers import Input, Dense, Dropout
from keras.layers import Conv1D, GlobalMaxPooling1D
from keras.models import Model

def tcn(input_shape, num_classes):
    # Input layer
    inputs = Input(shape=input_shape)

    # Convolutional layers
    x = inputs
    for i in range(3):
        d = 2 ** i
        x = Conv1D(filters=64, kernel_size=3, strides=1, dilation_rate=d, padding='causal', activation='relu')(x)

    # Global Max Pooling layer
    x = GlobalMaxPooling1D()(x)

    # Fully connected layers
    x = Dense(64, activation='relu')(x)
    x = Dropout(0.5)(x)
    outputs = Dense(num_classes, activation='softmax')(x)

    # Create model
    model = Model(inputs=inputs, outputs=outputs)
    return model

这是一个简单的TCN模型，包含三个卷积层、一个全局最大池化层和两个全连接层。你可以根据需要修改这个模型来适应你的应用场景。