Finds values and indices of the k
largest elements for the last dimension.
tf.raw_ops.TopK( input, k, sorted=True, name=None )
If the input is a vector (rank-1), finds the k
largest entries in the vector and outputs their values and indices as vectors. Thus values[j]
is the j
-th largest entry in input
, and its index is indices[j]
.
For matrices (resp. higher rank input), computes the top k
entries in each row (resp. vector along the last dimension). Thus,
values.shape = indices.shape = input.shape[:-1] + [k]
If two elements are equal, the lower-index element appears first.
If k
varies dynamically, use TopKV2
below.
Args | |
---|---|
input | A Tensor . Must be one of the following types: float32 , float64 , int32 , uint8 , int16 , int8 , int64 , bfloat16 , uint16 , half , uint32 , uint64 . 1-D or higher with last dimension at least k . |
k | An int that is >= 0 . Number of top elements to look for along the last dimension (along each row for matrices). |
sorted | An optional bool . Defaults to True . If true the resulting k elements will be sorted by the values in descending order. |
name | A name for the operation (optional). |
Returns | |
---|---|
A tuple of Tensor objects (values, indices). | |
values | A Tensor . Has the same type as input . |
indices | A Tensor of type int32 . |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/TopK