SparseSoftmaxCrossEntropyWithLogits
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Calcula el costo de entropía cruzada de softmax y los gradientes para propagar hacia atrás.
A diferencia de `SoftmaxCrossEntropyWithLogits`, esta operación no acepta una matriz de probabilidades de etiquetas, sino una única etiqueta por fila de características. Se considera que esta etiqueta tiene una probabilidad de 1,0 para la fila dada.
Las entradas son logits, no probabilidades.
Constantes
Cadena | OP_NOMBRE | El nombre de esta operación, como lo conoce el motor central de TensorFlow. |
Métodos heredados
De la clase java.lang.Object booleano | es igual (Objeto arg0) |
Clase final<?> | obtenerclase () |
En t | código hash () |
vacío final | notificar () |
vacío final | notificar a todos () |
Cadena | Encadenar () |
vacío final | esperar (arg0 largo, int arg1) |
vacío final | espera (arg0 largo) |
vacío final | esperar () |
Constantes
Cadena final estática pública OP_NAME
El nombre de esta operación, como lo conoce el motor central de TensorFlow.
Valor constante: "SparseSoftmaxCrossEntropyWithLogits"
Métodos públicos
Salida pública <T> backprop ()
gradientes retropropagados (matriz batch_size x num_classes).
Método de fábrica para crear una clase que envuelve una nueva operación SparseSoftmaxCrossEntropyWithLogits.
Parámetros
alcance | alcance actual |
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características | matriz de tamaño de lote x núm_clases |
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etiquetas | vector de tamaño de lote con valores en [0, num_classes). Esta es la etiqueta de la entrada del minibatch determinada. |
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Devoluciones
- una nueva instancia de SparseSoftmaxCrossEntropyWithLogits
Pérdida de salida pública <T> ()
Por ejemplo, pérdida (vector de tamaño de lote).
A menos que se indique lo contrario, el contenido de esta página está sujeto a la licencia Reconocimiento 4.0 de Creative Commons y las muestras de código están sujetas a la licencia Apache 2.0. Para obtener más información, consulta las políticas del sitio web de Google Developers. Java es una marca registrada de Oracle o sus afiliados.
Última actualización: 2025-07-26 (UTC).
[null,null,["Última actualización: 2025-07-26 (UTC)."],[],[],null,["# SparseSoftmaxCrossEntropyWithLogits\n\npublic final class **SparseSoftmaxCrossEntropyWithLogits** \nComputes softmax cross entropy cost and gradients to backpropagate.\n\n\nUnlike \\`SoftmaxCrossEntropyWithLogits\\`, this operation does not accept\na matrix of label probabilities, but rather a single label per row\nof features. This label is considered to have probability 1.0 for the\ngiven row.\n\n\nInputs are the logits, not probabilities.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n### Constants\n\n|--------|----------------------------------------------------------------------------------------------------|---------------------------------------------------------|\n| String | [OP_NAME](/jvm/api_docs/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits#OP_NAME) | The name of this op, as known by TensorFlow core engine |\n\n### Public Methods\n\n|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [backprop](/jvm/api_docs/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits#backprop())() backpropagated gradients (batch_size x num_classes matrix). |\n| static \\\u003cT extends [TNumber](/jvm/api_docs/java/org/tensorflow/types/family/TNumber)\\\u003e [SparseSoftmaxCrossEntropyWithLogits](/jvm/api_docs/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits)\\\u003cT\\\u003e | [create](/jvm/api_docs/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits#create(org.tensorflow.op.Scope, org.tensorflow.Operand\u003cT\u003e, org.tensorflow.Operand\u003c? extends org.tensorflow.types.family.TNumber\u003e))([Scope](/jvm/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e features, [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003c? extends [TNumber](/jvm/api_docs/java/org/tensorflow/types/family/TNumber)\\\u003e labels) Factory method to create a class wrapping a new SparseSoftmaxCrossEntropyWithLogits operation. |\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [loss](/jvm/api_docs/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits#loss())() Per example loss (batch_size vector). |\n\n### Inherited Methods\n\nFrom class [org.tensorflow.op.RawOp](/jvm/api_docs/java/org/tensorflow/op/RawOp) \n\n|----------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| final boolean | [equals](/jvm/api_docs/java/org/tensorflow/op/RawOp#equals(java.lang.Object))(Object obj) |\n| final int | [hashCode](/jvm/api_docs/java/org/tensorflow/op/RawOp#hashCode())() |\n| [Operation](/jvm/api_docs/java/org/tensorflow/Operation) | [op](/jvm/api_docs/java/org/tensorflow/op/RawOp#op())() Return this unit of computation as a single [Operation](/jvm/api_docs/java/org/tensorflow/Operation). |\n| final String | [toString](/jvm/api_docs/java/org/tensorflow/op/RawOp#toString())() |\n\nFrom class java.lang.Object \n\n|------------------|---------------------------|\n| boolean | equals(Object arg0) |\n| final Class\\\u003c?\\\u003e | getClass() |\n| int | hashCode() |\n| final void | notify() |\n| final void | notifyAll() |\n| String | toString() |\n| final void | wait(long arg0, int arg1) |\n| final void | wait(long arg0) |\n| final void | wait() |\n\nFrom interface [org.tensorflow.op.Op](/jvm/api_docs/java/org/tensorflow/op/Op) \n\n|-----------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| abstract [ExecutionEnvironment](/jvm/api_docs/java/org/tensorflow/ExecutionEnvironment) | [env](/jvm/api_docs/java/org/tensorflow/op/Op#env())() Return the execution environment this op was created in. |\n| abstract [Operation](/jvm/api_docs/java/org/tensorflow/Operation) | [op](/jvm/api_docs/java/org/tensorflow/op/Op#op())() Return this unit of computation as a single [Operation](/jvm/api_docs/java/org/tensorflow/Operation). |\n\nConstants\n---------\n\n#### public static final String\n**OP_NAME**\n\nThe name of this op, as known by TensorFlow core engine \nConstant Value: \"SparseSoftmaxCrossEntropyWithLogits\"\n\nPublic Methods\n--------------\n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e\n**backprop**\n()\n\nbackpropagated gradients (batch_size x num_classes matrix). \n\n#### public static [SparseSoftmaxCrossEntropyWithLogits](/jvm/api_docs/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits)\\\u003cT\\\u003e\n**create**\n([Scope](/jvm/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e features, [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003c? extends [TNumber](/jvm/api_docs/java/org/tensorflow/types/family/TNumber)\\\u003e labels)\n\nFactory method to create a class wrapping a new SparseSoftmaxCrossEntropyWithLogits operation. \n\n##### Parameters\n\n| scope | current scope |\n| features | batch_size x num_classes matrix |\n| labels | batch_size vector with values in \\[0, num_classes). This is the label for the given minibatch entry. |\n|----------|------------------------------------------------------------------------------------------------------|\n\n##### Returns\n\n- a new instance of SparseSoftmaxCrossEntropyWithLogits \n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e\n**loss**\n()\n\nPer example loss (batch_size vector)."]]