| Given two tensors: X and K, retrieve
| the top
|
| K[…, 1] elements from X on the last
| dimension.
|
| X is an input tensor of shape [a_1, a_2,
| …, a_n, r].
|
| K is an input tensor of shape [a_1, a_2,
| …, a_n, 1], where for each element,
| r >= K[…, 1] > 0
|
| Output two outputs:
|
| -Flatten values tensor of shape [ \sum_i
| K[i, 1] ] which contains the values of
| the top K[…, 1] elements along the
| last dimension
|
| -Flatten indices tensor of shape [ \sum_i
| K[i, 1] ] which contains the indices
| of the top K[…, 1] elements, flatten
| indices from the input tensor).
|
| These two outputs should be used with
| the input K, so that we know which indices
| in X are picked.
|
| Given two equivalent values, this operator
| uses the indices along the last dim-
| ension as a tiebreaker. That is, the
| element with the lower index will appear
| first.
|
| Retrieve the top-K elements of the last
| dimension.
|
| Given an input tensor of shape $(a_1,
| a_2, …, a_n, r)$. k can be passed
| as an integer argument or a 1D tensor
| containing a single integer.
|
| Returns up to three outputs:
|
| 1. Value tensor of shape $(a_1, a_2,
| …, a_n, k)$ which contains the values
| of the top k elements along the last dimension
|
| 2. Index tensor of shape $(a_1, a_2,
| …, a_n, k)$ which contains the indices
| of the top k elements (original indices
| from the input tensor).
|
| 3. [OPTIONAL] Flattened index tensor
| of shape $(a_1 * a_2 * … * a_n * k,)$.
|
| Given two equivalent values, this operator
| uses the indices along the last dimension
| as a tiebreaker.
|
| That is, the element with the lower index
| will appear first.
|
| Github Links:
|
| - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/top_k.cc
|