How can I drop rows in a tensor if the sum of the elements in each row is lower than the threshold -1? For example:
tensor = tf.random.normal((3, 3))
tf.Tensor(
[[ 0.506158 0.53865975 -0.40939444]
[ 0.4917719 -0.1575156 1.2308844 ]
[ 0.08580616 -1.1503975 -2.252681 ]], shape=(3, 3), dtype=float32)
Since the sum of the last row is smaller than -1, I need to remove it and get the tensor (2, 3):
tf.Tensor(
[[ 0.506158 0.53865975 -0.40939444]
[ 0.4917719 -0.1575156 1.2308844 ]], shape=(2, 3), dtype=float32)
I know how to use tf.reduce_sum, but I do not know how to delete rows from a tensor. Something like df.drop
would be nice.
CodePudding user response:
tf.boolean_mask
is all you need.
tensor = tf.constant([
[ 0.506158, 0.53865975, -0.40939444],
[ 0.4917719, -0.1575156, 1.2308844 ],
[ 0.08580616, -1.1503975, -2.252681 ],
])
mask = tf.reduce_sum(tensor, axis=1) > -1
# <tf.Tensor: shape=(3,), dtype=bool, numpy=array([ True, True, False])>
tf.boolean_mask(
tensor=tensor,
mask=mask,
axis=0
)
# <tf.Tensor: shape=(2, 3), dtype=float32, numpy=
# array([[ 0.506158 , 0.53865975, -0.40939444],
# [ 0.4917719 , -0.1575156 , 1.2308844 ]], dtype=float32)>
CodePudding user response:
You could use tf.where
to extract the indices of the rows for which the sum of the elements is greater than -1, and then use tf.gather
to drop the other rows.
import tensorflow as tf
tf.random.set_seed(0)
x = tf.random.normal((3, 3))
# <tf.Tensor: shape=(3, 3), dtype=float32, numpy=
# array([[ 1.5110626 , 0.42292204, -0.41969493],
# [-1.0360372 , -1.2368279 , 0.47027302],
# [-0.01397489, 1.1888583 , 0.60253334]], dtype=float32)>
x = tf.gather(x, indices=tf.squeeze(tf.where(tf.reduce_sum(x, axis=1) > -1)), axis=0)
# <tf.Tensor: shape=(2, 3), dtype=float32, numpy=
# array([[ 1.5110626 , 0.42292204, -0.41969493],
# [-0.01397489, 1.1888583 , 0.60253334]], dtype=float32)>