Given tensor data
[[[ 0., 0.],
[ 1., 1.],
[-1., -1.]],
[[-1., -1.],
[ 4., 4.],
[ 5., 5.]]]
I want to remove [-1,-1] and get
[[[ 0., 0.],
[ 1., 1.]],
[[ 4., 4.],
[ 5., 5.]]]
How to get the above without using ragged feature in tensorflow?
You can try this:
x = tf.constant(
[[[ 0., 0.],
[ 1., 1.],
[-1., -2.]],
[[-1., -2.],
[ 4., 4.],
[ 5., 5.]]])
mask = tf.math.not_equal(x, np.array([-1, -1]))
result = tf.boolean_mask(x, mask)
shape = tf.shape(x)
result = tf.reshape(result, (shape[0], -1, shape[2]))