import tensorflow as tf
from transformers import PreTrainedModel, TFPreTrainedModel
from transformers.modeling_tf_utils import TFSequenceClassificationLoss

class TFNewsClassifier(TFPreTrainedModel, TFSequenceClassificationLoss):
    def __init__(self, config):
        super().__init__(config)
        self.num_labels = config.num_labels
        
        # Define your model architecture
        self.lstm = tf.keras.layers.LSTM(128, return_sequences=True)
        self.lstm2 = tf.keras.layers.LSTM(64)
        self.dropout = tf.keras.layers.Dropout(0.5)
        self.classifier = tf.keras.layers.Dense(self.num_labels, activation='softmax')
        
    def call(self, inputs, training=False):
        x = self.lstm(inputs)
        x = self.dropout(x, training=training)
        x = self.lstm2(x)
        x = self.dropout(x, training=training)
        return self.classifier(x)