tf.nn.top_k( input, k=1, sorted=True, name=None )
See the guide: Neural Network > Evaluation
Finds values and indices of the
k largest entries for the last dimension.
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
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.
input: 1-D or higher
Tensorwith last dimension at least
Tensor. Number of top elements to look for along the last dimension (along each row for matrices).
sorted: If true the resulting
kelements will be sorted by the values in descending order.
name: Optional name for the operation.
klargest elements along each last dimensional slice.
indices: The indices of
valueswithin the last dimension of
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