How to do "round half up" in tensorflow

Question

I have some question when doing tf.round(x) x=[0.4, 1.5, 2.5, -1.5, -2.5, -0.4]

If I want to get the ans=[0, 2, 3, -2, -3, 0] rounding half way away from zero

How should I do? I've tried tf.keras.backend.round(), tf.math.round, tf.math.rint()

I got similar answer in python but not in TF

>>>decimal.Decimal(101.5).quantize(decimal.Decimal('0'), rounding=decimal.ROUND_HALF_UP)
Decimal('102')
>>>decimal.Decimal(102.5).quantize(decimal.Decimal('0'), rounding=decimal.ROUND_HALF_UP)
Decimal('103')
>>>decimal.Decimal(-101.5).quantize(decimal.Decimal('0'), rounding=decimal.ROUND_HALF_UP)
Decimal('-102')
>>>decimal.Decimal(-102.5).quantize(decimal.Decimal('0'), rounding=decimal.ROUND_HALF_UP)
Decimal('-103')

Thank you

Answer 1

How about this ?

x = np.array([0.4, 1.5, 2.5, -1.5, -2.5, -0.4]) 
for i, val in enumerate(x):
   if val % 1 == 0.5
       x[i] = tf.math.floor(x[i]) if val < 0 else tf.math.floor(x[i]+0.5)
   else
       x[i] = tf.math.round(x[i])
print(x)

[ 0. 2. 3. -2. -3. 0.]

Answer 2

Try

x=tf.constant([0.4, 1.5, 2.5, -1.5, -2.5, -0.4])
x=tf.where(x>0, tf.math.nextafter(x, np.inf), tf.math.nextafter(x, -np.inf))
x=tf.round(x)

this will round away from 0.