fashion-mnist-compute-cost.py

def compute_cost(Z3, Y):
    '''
    Computes the cost
    
    Arguments:
    Z3 -- output of forward propagation (output of the last LINEAR unit), of shape (10, number_of_examples)
    Y -- "true" labels vector placeholder, same shape as Z3
    
    Returns:
    cost - Tensor of the cost function
    '''
    
    # Get logits (predictions) and labels
    logits = tf.transpose(Z3)
    labels = tf.transpose(Y)
    
    # Compute cost
    cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=labels))
    
    return cost