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# SparseCategoricalCrossentropy

public class SparseCategoricalCrossentropy

A metric that computes the sparse categorical cross-entropy loss between true labels and predicted labels.

### Public Constructors

 (Ops tf, String name, boolean fromLogits, int axis, long seed, Class type) Creates a SparseCategoricalCrossentropy metric

### Public Methods

 Operand ( Operand labels, Operand predictions) Calculates the weighted loss between ``` labels ``` and ``` predictions ```

## Public Constructors

#### public SparseCategoricalCrossentropy (Ops tf, String name, boolean fromLogits, int axis, long seed, Class<T> type)

Creates a SparseCategoricalCrossentropy metric

##### Parameters
 tf the TensorFlow Ops the name of this metric, if null then metric name is ``` getSimpleName() ``` . Whether to interpret predictions as a tensor of logit values as opposed to a probability distribution. The dimension along which the entropy is computed. the seed for random number generation. An initializer created with a given seed will always produce the same random tensor for a given shape and data type. the type for the variables and result

## Public Methods

#### public Operand <T> call ( Operand <? extends TNumber > labels, Operand <? extends TNumber > predictions)

Calculates the weighted loss between ``` labels ``` and ``` predictions ```

##### Parameters
 labels the truth values or labels the predictions
##### Returns
• the loss
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]