panchishin/top_k_loss.py

## top_k_loss.py
def top_k_loss(k=25):
    @tf.function
    def loss(y_true, y_pred):
        y_error_of_true = tf.keras.losses.categorical_crossentropy(y_true=y_true,y_pred=y_pred)
        topk, indexs = tf.math.top_k( y_error_of_true, k=tf.minimum(k, y_true.shape[0]) )
        return topk
    return loss
	def top_k_loss(k=25):
	@tf.function
	def loss(y_true, y_pred):
	y_error_of_true = tf.keras.losses.categorical_crossentropy(y_true=y_true,y_pred=y_pred)
	topk, indexs = tf.math.top_k( y_error_of_true, k=tf.minimum(k, y_true.shape[0]) )
	return topk
	return loss