Не знаю как переделать get_session под TF2

def emnist_train(model):
    t_start = time.time()
 
    emnist_path = 'C:\\Users\\nokkoran\\PycharmProjects\\EMNIST2\\'
    X_train = idx2numpy.convert_from_file(emnist_path + 'emnist-byclass-train-images-idx3-ubyte')
    y_train = idx2numpy.convert_from_file(emnist_path + 'emnist-byclass-train-labels-idx1-ubyte')
 
    X_test = idx2numpy.convert_from_file(emnist_path + 'emnist-byclass-test-images-idx3-ubyte')
    y_test = idx2numpy.convert_from_file(emnist_path + 'emnist-byclass-test-labels-idx1-ubyte')
 
    X_train = np.reshape(X_train, (X_train.shape[0], 28, 28, 1))
    X_test = np.reshape(X_test, (X_test.shape[0], 28, 28, 1))
 
    print(X_train.shape, y_train.shape, X_test.shape, y_test.shape, len(emnist_labels))
 
    # Test:
    k = 100
    X_train = X_train[:X_train.shape[0] // k]
    y_train = y_train[:y_train.shape[0] // k]
    X_test = X_test[:X_test.shape[0] // k]
    y_test = y_test[:y_test.shape[0] // k]
 
    # Normalize
    X_train = X_train.astype(np.float32)
    X_train /= 255.0
    X_test = X_test.astype(np.float32)
    X_test /= 255.0
 
    x_train_cat = keras.utils.to_categorical(y_train, len(emnist_labels))
    y_test_cat = keras.utils.to_categorical(y_test, len(emnist_labels))
 
    # Set a learning rate reduction
    learning_rate_reduction = keras.callbacks.ReduceLROnPlateau(monitor='val_acc', patience=3, verbose=1, factor=0.5, min_lr=0.00001)
 
    # Required for learning_rate_reduction:
    keras.backend.get_session().run(tf.global_variables_initializer())
 
    model.fit(X_train, x_train_cat, validation_data=(X_test, y_test_cat), callbacks=[learning_rate_reduction], batch_size=64, epochs=30)
    print("Training done, dT:", time.time() - t_start)
 
 
keras.backend.get_session().run(tf.global_variables_initializer())

tf.compat.v1.keras.backend.get_session()

from tensorflow.compat.v1 import keras