F-score, Precision, and Recall values

[Hani]

from tensorflow.keras import backend as K
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def computeMetrics(true, pred): # considering sigmoid activation, threshold = 0.5
pred = K.cast(K.greater(pred, 0.5), K.floatx())

gP = K.cast( K.sum(true), K.floatx()) + K.epsilon()
cP = K.sum(true * pred) + K.epsilon()
pP = K.sum(pred) + K.epsilon()

precision = cP / pP
recall = cP / gP
f1 = (2 * precision * recall) / (precision + recall)

return f1, precision, recall

metrics =computeMetrics(y_test, y_pred)

print('metrics -----> ',metrics)


output:
metrics -----> (<tf.Tensor 'truediv_2:0' shape=() dtype=float32>, <tf.Tensor 'truediv:0' shape=() dtype=float32>, <tf.Tensor 'truediv_1:0' shape=() dtype=float32>)


Anyone can help to get the values from the metrics ?