Issue
I want to broadcast my tensor of size (32, 128) to (128, 128) but it generates this error. InvalidArgumentError: Incompatible shapes: [32,128] vs. [128,128] [Op:BroadcastTo].
I want to know whether it’s possible to broadcast it or not. what are the possible reasons to perform this.
I use the following code
loss = tf.broadcast_to(kl_loss, [128, 128])
Solution
We can use tf.broadcast_to, But we need to consider that first we need to convert 2D tensor to 3D tensor and then reshape it to 2D like below.
import tensorflow as tf
kl_loss = tf.random.uniform((32, 128))
print(kl_loss.shape)
# (32, 128)
result = tf.reshape(tf.broadcast_to(kl_loss, [4 , 32, 128]), [128, 128])
# ------------------------------------------ ^4 : 128//32
print(result.shape)
# (128, 128)
What will the output look like? (Example for broadcasting from (2, 3) to (4, 3))
tf.random.set_seed(123)
x = tf.random.uniform((2, 3))
print(x)
y = tf.broadcast_to(x, [2, 2, 3])
print(y)
z = tf.reshape(y, [4, 3])
print(z)
# x =>
tf.Tensor(
[[0.12615311 0.5727513 0.2993133 ]
[0.5461836 0.7205157 0.7889533 ]], shape=(2, 3), dtype=float32)
# y =>
tf.Tensor(
[[[0.12615311 0.5727513 0.2993133 ]
[0.5461836 0.7205157 0.7889533 ]]
[[0.12615311 0.5727513 0.2993133 ]
[0.5461836 0.7205157 0.7889533 ]]], shape=(2, 2, 3), dtype=float32)
# z =>
tf.Tensor(
[[0.12615311 0.5727513 0.2993133 ]
[0.5461836 0.7205157 0.7889533 ]
[0.12615311 0.5727513 0.2993133 ]
[0.5461836 0.7205157 0.7889533 ]], shape=(4, 3), dtype=float32)
Answered By – I'mahdi
This Answer collected from stackoverflow, is licensed under cc by-sa 2.5 , cc by-sa 3.0 and cc by-sa 4.0