1b5dd6e75723da209cc67c89b4446ac79a8070c5,tensorlayer/cost.py,,cosine_similarity,#Any#Any#,250

Before Change

    -----------
    a tensor of [batch_size, ]
    
    return tf.reduce_sum(tf.mul(v1, v2), reduction_indices=1) / (tf.sqrt(tf.reduce_sum(tf.mul(v1, v1), reduction_indices=1)) * tf.sqrt(tf.reduce_sum(tf.mul(v2, v2), reduction_indices=1)))



//// Regularization Functions

After Change

    a tensor of [batch_size, ]
    
    try: //// TF1.0
        cost = tf.reduce_sum(tf.multiply(v1, v2), 1) / (tf.sqrt(tf.reduce_sum(tf.multiply(v1, v1), 1)) * tf.sqrt(tf.reduce_sum(tf.multiply(v2, v2), 1)))
    except: //// TF0.12
        cost = tf.reduce_sum(tf.mul(v1, v2), reduction_indices=1) / (tf.sqrt(tf.reduce_sum(tf.mul(v1, v1), reduction_indices=1)) * tf.sqrt(tf.reduce_sum(tf.mul(v2, v2), reduction_indices=1)))
    return cost


//// Regularization Functions
def li_regularizer(scale, scope=None):

Instances