Dot product of two tensors.
tf.keras.ops.dot(
x1, x2
)
- If both
x1
and x2
are 1-D tensors, it is inner product of vectors
(without complex conjugation).
- If both
x1
and x2
are 2-D tensors, it is matrix multiplication.
- If either
x1
or x2
is 0-D (scalar), it is equivalent to x1 * x2
.
- If
x1
is an N-D tensor and x2
is a 1-D tensor, it is a sum product
over the last axis of x1
and x2
.
- If
x1
is an N-D tensor and x2
is an M-D tensor (where M>=2
),
it is a sum product over the last axis of x1
and the second-to-last
axis of x2
: dot(x1, x2)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m])
.
Args |
x1
|
First argument.
|
x2
|
Second argument.
|
Note |
Torch backend does not accept 0-D tensors as arguments.
|
Returns |
Dot product of x1 and x2 .
|