placeholder_tf.py

def create_placeholders(n_x, n_y):
    """
    Arguments:
    n_x -- scalar, size of an image vector (64 * 64 * 3 = 12288)
    n_y -- scalar, number of classes (from 0 to 5, so n_y = 6)
    
    Returns:
    X -- placeholder for the data input, of shape [n_x, None] and dtype "tf.float32"
    Y -- placeholder for the input labels, of shape [n_y, None] and dtype "tf.float32"
    
    You will use None because it let's us be flexible on the number of examples you will for the placeholders.
    In fact, the number of examples during test/train is different.
    """
    
    X = tf.placeholder(tf.float32, shape = [n_x, None], name = 'X')
    Y = tf.placeholder(tf.float32, shape = [n_y, None], name = 'Y')
    
    return X, Y