Counts the number of occurrences of each value in an integer array.
Outputs a vector with length `size` and the same dtype as `weights`. If `weights` are empty, then index `i` stores the number of times the value `i` is counted in `arr`. If `weights` are non-empty, then index `i` stores the sum of the value in `weights` at each index where the corresponding value in `arr` is `i`.
Values in `arr` outside of the range [0, size) are ignored.
Nested Classes
| class | RaggedBincount.Options |
Optional attributes for
RaggedBincount
|
|
Public Methods
| Output <U> |
asOutput
()
Returns the symbolic handle of a tensor.
|
| static RaggedBincount.Options |
binaryOutput
(Boolean binaryOutput)
|
| static <U extends Number, T extends Number> RaggedBincount <U> | |
| Output <U> |
output
()
1D `Tensor` with length equal to `size` or 2D `Tensor` with [batch_size, `size`].
|
Inherited Methods
Public Methods
public Output <U> asOutput ()
Returns the symbolic handle of a tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static RaggedBincount.Options binaryOutput (Boolean binaryOutput)
Parameters
| binaryOutput | bool; Whether the kernel should count the appearance or number of occurrences. |
|---|
public static RaggedBincount <U> create ( Scope scope, Operand <Long> splits, Operand <T> values, Operand <T> size, Operand <U> weights, Options... options)
Factory method to create a class wrapping a new RaggedBincount operation.
Parameters
| scope | current scope |
|---|---|
| splits | 1D int64 `Tensor`. |
| values | 2D int `Tensor`. |
| size | non-negative int scalar `Tensor`. |
| weights | is an int32, int64, float32, or float64 `Tensor` with the same shape as `input`, or a length-0 `Tensor`, in which case it acts as all weights equal to 1. |
| options | carries optional attributes values |
Returns
- a new instance of RaggedBincount
public Output <U> output ()
1D `Tensor` with length equal to `size` or 2D `Tensor` with [batch_size, `size`]. The counts or summed weights for each value in the range [0, size).