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SparseBincount

public final class SparseBincount

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 SparseBincount.Options Optional attributes for SparseBincount  

Public Methods

Output<U>
asOutput()
Returns the symbolic handle of a tensor.
static SparseBincount.Options
binaryOutput(Boolean binaryOutput)
static <U extends Number, T extends Number> SparseBincount<U>
create(Scope scope, Operand<Long> indices, Operand<T> values, Operand<Long> denseShape, Operand<T> size, Operand<U> weights, Options... options)
Factory method to create a class wrapping a new SparseBincount operation.
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 SparseBincount.Options binaryOutput (Boolean binaryOutput)

Parameters
binaryOutput bool; Whether the kernel should count the appearance or number of occurrences.

public static SparseBincount<U> create (Scope scope, Operand<Long> indices, Operand<T> values, Operand<Long> denseShape, Operand<T> size, Operand<U> weights, Options... options)

Factory method to create a class wrapping a new SparseBincount operation.

Parameters
scope current scope
indices 2D int64 `Tensor`.
values 1D int `Tensor`.
denseShape 1D int64 `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 SparseBincount

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).