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Returns the diagonal part of the tensor.
tf.linalg.tensor_diag_part(
input, name=None
)
This operation returns a tensor with the diagonal
part
of the input
. The diagonal
part is computed as follows:
Assume input
has dimensions [D1,..., Dk, D1,..., Dk]
, then the output is a
tensor of rank k
with dimensions [D1,..., Dk]
where:
diagonal[i1,..., ik] = input[i1, ..., ik, i1,..., ik]
.
For a rank 2 tensor, linalg.diag_part
and linalg.tensor_diag_part
produce the same result. For rank 3 and higher, linalg.diag_part extracts
the diagonal of each inner-most matrix in the tensor. An example where
they differ is given below.
x = [[[[1111,1112],[1121,1122]],
[[1211,1212],[1221,1222]]],
[[[2111, 2112], [2121, 2122]],
[[2211, 2212], [2221, 2222]]]
]
tf.linalg.tensor_diag_part(x)
<tf.Tensor: shape=(2, 2), dtype=int32, numpy=
array([[1111, 1212],
[2121, 2222]], dtype=int32)>
tf.linalg.diag_part(x).shape
TensorShape([2, 2, 2])
Args | |
---|---|
input
|
A Tensor with rank 2k .
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor containing diagonals of input . Has the same type as input , and
rank k .
|