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### `tf.batch_matrix_band_part(input, num_lower, num_upper, name=None)` {#batch_matrix_band_part}
Copy a tensor setting everything outside a central band in each innermost matrix
to zero.
The `band` part is computed as follows:
Assume `input` has `k` dimensions `[I, J, K, ..., M, N]`, then the output is a
tensor with the same shape where
`band[i, j, k, ..., m, n] = in_band(m, n) * input[i, j, k, ..., m, n]`.
The indicator function 'in_band(m, n)` is one if
`(num_lower < 0 || (m-n) <= num_lower)) &&
(num_upper < 0 || (n-m) <= num_upper)`, and zero otherwise.
For example:
```prettyprint
# if 'input' is [[ 0, 1, 2, 3]
[-1, 0, 1, 2]
[-2, -1, 0, 1]
[-3, -2, -1, 0]],
tf.batch_matrix_band_part(input, 1, -1) ==> [[ 0, 1, 2, 3]
[-1, 0, 1, 2]
[ 0, -1, 0, 1]
[ 0, 0, -1, 0]],
tf.batch_matrix_band_part(input, 2, 1) ==> [[ 0, 1, 0, 0]
[-1, 0, 1, 0]
[-2, -1, 0, 1]
[ 0, -2, -1, 0]]
```
Useful special cases:
```prettyprint
tf.batch_matrix_band_part(input, 0, -1) ==> Upper triangular part.
tf.batch_matrix_band_part(input, -1, 0) ==> Lower triangular part.
tf.batch_matrix_band_part(input, 0, 0) ==> Diagonal.
```
##### Args:
* <b>`input`</b>: A `Tensor`. Rank `k` tensor.
* <b>`num_lower`</b>: A `Tensor` of type `int64`.
0-D tensor. Number of subdiagonals to keep. If negative, keep entire
lower triangle.
* <b>`num_upper`</b>: A `Tensor` of type `int64`.
0-D tensor. Number of superdiagonals to keep. If negative, keep
entire upper triangle.
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
A `Tensor`. Has the same type as `input`.
Rank `k` tensor of the same shape as input. The extracted banded tensor.
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