# tf.matrix_diag_part(input, name=None)

### tf.matrix_diag_part(input, name=None)

See the guide: Math > Matrix Math Functions

Returns the batched diagonal part of a batched tensor.

This operation returns a tensor with the diagonal part of the batched input. The diagonal part is computed as follows:

Assume input has k dimensions [I, J, K, ..., M, N], then the output is a tensor of rank k - 1 with dimensions [I, J, K, ..., min(M, N)] where:

diagonal[i, j, k, ..., n] = input[i, j, k, ..., n, n].

The input must be at least a matrix.

For example:

# 'input' is [[[1, 0, 0, 0]
[0, 2, 0, 0]
[0, 0, 3, 0]
[0, 0, 0, 4]],
[[5, 0, 0, 0]
[0, 6, 0, 0]
[0, 0, 7, 0]
[0, 0, 0, 8]]]

and input.shape = (2, 4, 4)

tf.matrix_diag_part(input) ==> [[1, 2, 3, 4], [5, 6, 7, 8]]

which has shape (2, 4)


#### Args:

• input: A Tensor. Rank k tensor where k >= 2.
• name: A name for the operation (optional).

#### Returns:

A Tensor. Has the same type as input. The extracted diagonal(s) having shape diagonal.shape = input.shape[:-2] + [min(input.shape[-2:])].

Defined in tensorflow/python/ops/gen_array_ops.py.