keras custom metric for path planning neural network doesnt work

Firstly some info about the background of the problem. I am building an artificial neural network solving an AGV path planning problem. The input of the network is a 15x15 grid terrain of 0,1 , meaning that 0 is empty space for the robot to go and 1 is an obstacle. There are 5 fixed destinations for all samples. The only thing changing is the terrain. My output is path between the start and destinations. I want to use a custom metric that measures how many obstacles are being hit and evaluate the produced path. Below is the code. I have already made an obs list in which, obs[0][sample_index]->obstacles of the train_sample[index] and obs[1][sample_index]->obstacles of the test_sample[index]. However the after the compile the model doesnt fit. Can someone explain to me what is the problem with the custom metric?

def index(y):
    if y in y_train:
        a=y_train.index(y)
    elif y in y_test:
        a=y_test.index(y)
    return a

def custom_metric(y_true, y_pred):

    ind=index(y_true)

    obs_in_ypred=0


    if y_true in y_train:
        for i in range(0,len(y_pred),2):
            if y_pred[i]*15+y_pred[i+1] in obs[0][ind]:
                obs_in_ypred=obs_in_ypred+1
    elif y_true in y_test:
        for i in range(0,len(y_pred),2):
            if y_pred[i]*15+y_pred[i+1] in obs[1][ind]:
                obs_in_ypred=obs_in_ypred+1
        
    metric1=1-obs_in_ypred/(len(obs[0][ind]))
    metric2=1-obs_in_ypred/(len(obs[1][ind]))

    return tf.keras.backend.in_train_phase(metric1,metric2)