import tensorflow as tf from tensorflow.keras.applications import ResNet50 from tensorflow.keras.layers import LSTM, Dense, GlobalAveragePooling2D, Dropout from tensorflow.keras.activations import relu class Model(tf.keras.Model): def __init__(self, num_classes, latent_dim=2048, lstm_layers=1, hidden_dim=2048, bidirectional=False): super(Model, self).__init__() self.base_model = tf.keras.Sequential([ ResNet50(include_top=False, weights=None, input_shape=(None, None, 3)), ], name=’resnet50_base’) self.base_model.layers[0].name = ‘resnet50_base’ # Set a unique name for the ResNet50 model self.base_model.layers[0].trainable = False […]