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TensorFlow 1 version
|
Copy a tensor setting everything outside a central band in each innermost matrix to zero.
tf.linalg.band_part(
input, num_lower, num_upper, name=None
)
Used in the notebooks
| Used in the tutorials |
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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) = (num_lower < 0 || (m-n) <= num_lower)) &&
(num_upper < 0 || (n-m) <= num_upper).
For example:
# if 'input' is [[ 0, 1, 2, 3]
[-1, 0, 1, 2]
[-2, -1, 0, 1]
[-3, -2, -1, 0]],
tf.matrix_band_part(input, 1, -1) ==> [[ 0, 1, 2, 3]
[-1, 0, 1, 2]
[ 0, -1, 0, 1]
[ 0, 0, -1, 0]],
tf.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:
tf.matrix_band_part(input, 0, -1) ==> Upper triangular part.
tf.matrix_band_part(input, -1, 0) ==> Lower triangular part.
tf.matrix_band_part(input, 0, 0) ==> Diagonal.
Args | |
|---|---|
input
|
A Tensor. Rank k tensor.
|
num_lower
|
A Tensor. Must be one of the following types: int32, int64.
0-D tensor. Number of subdiagonals to keep. If negative, keep entire
lower triangle.
|
num_upper
|
A Tensor. Must have the same type as num_lower.
0-D tensor. Number of superdiagonals to keep. If negative, keep
entire upper triangle.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
A Tensor. Has the same type as input.
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