David S
2020-11-30 14:56:50
The answer I provided does have the answer, but not the immediate one!
Given the example you gave in your comment to @Meow Cat 2012:
import tensorflow as tf
import numpy as np
a = np.array([[1,2,3.0],[4,5,6.0]]
res = tf.einsum('ki,kj->kij',a,a)
print(res.shape) # TensorShape([2, 3, 3])
tf.einsum() function will compute the outer product of two tensors.
Another solution using tf.linalg.matmul is (@DachuanZhao pointed it out):
import tensorflow as tf
import numpy as np
a = np.array([[1,2,3.0],[4,5,6.0]]
res = tf.linalg.matmul(tf.expand_dims(a, axis=-1),tf.expand_dims(a, axis=1))
print(res.shape) # (2, 3, 3)
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Yes , I have found anther solution :
tf.linalg.matmul(tf.expand_dims(a, axis=-1),tf.expand_dims(a, axis=1))@DachuanZhao Cool, happy you managed. I will add this solution to my answer for future users