tf.keras.ops.dot

Dot product of two tensors.

View aliases

Main aliases

tf.keras.ops.numpy.dot

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.