src/fingerflow/matcher/VerifyNet/utils.py
def euclidean_distance(vects):
    """Find the Euclidean distance between two vectors.

    Arguments:
        vects: List containing two tensors of same length.

    Returns:
        Tensor containing euclidean distance
        (as floating point value) between vectors.
    """

    x, y = vects
    sum_square = tf.math.reduce_sum(tf.math.square(x - y), axis=1, keepdims=True)

    return tf.math.sqrt(tf.math.maximum(sum_square, tf.keras.backend.epsilon()))
Find the Euclidean distance between two vectors.

    Arguments:
        vects: List containing two tensors of same length.

    Returns:
        Tensor containing euclidean distance
        (as floating point value) between vectors.
    
Find the Euclidean distance between two vectors.
Find the Euclidean distance between two vectors .
def euclidean_distance(vects):
    x, y = vects
    sum_square = tf.math.reduce_sum(tf.math.square(x - y), axis=1, keepdims=True)
    return tf.math.sqrt(tf.math.maximum(sum_square, tf.keras.backend.epsilon()))
def euclidean_distance ( vects ) : x , y = vects sum_square = tf . math . reduce_sum ( tf . math . square ( x - y ) , axis = 1 , keepdims = True ) return tf . math . sqrt ( tf . math . maximum ( sum_square , tf . keras . backend . epsilon ( ) ) )
Find the Euclidean distance between two vectors.
Find the Euclidean distance between two vectors .
"""Find the Euclidean distance between two vectors.

    Arguments:
        vects: List containing two tensors of same length.

    Returns:
        Tensor containing euclidean distance
        (as floating point value) between vectors.
    """
Tensor containing euclidean distance
(as floating point value) between vectors.
Tensor containing euclidean distance ( as floating point value ) between vectors .
vects
List containing two tensors of same length.
List containing two tensors of same length .