SparseSoftmaxCrossEntropyWithLogits
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Menghitung biaya entropi silang softmax dan gradien ke propagasi mundur.
Berbeda dengan `SoftmaxCrossEntropyWithLogits`, operasi ini tidak menerima matriks probabilitas label, melainkan satu label per baris fitur. Label ini dianggap memiliki probabilitas 1,0 untuk baris tertentu.
Inputnya adalah logit, bukan probabilitas.
Konstanta
| Rangkaian | OP_NAME | Nama operasi ini dikenal dengan mesin inti TensorFlow |
Metode Warisan
Dari kelas java.lang.Object | boolean | sama dengan (Objek arg0) |
| Kelas terakhir<?> | dapatkan Kelas () |
| ke dalam | Kode hash () |
| kekosongan terakhir | memberitahu () |
| kekosongan terakhir | beri tahuSemua () |
| Rangkaian | keString () |
| kekosongan terakhir | tunggu (arg0 panjang, int arg1) |
| kekosongan terakhir | tunggu (argumen panjang0) |
| kekosongan terakhir | Tunggu () |
Konstanta
String akhir statis publik OP_NAME
Nama operasi ini dikenal dengan mesin inti TensorFlow
Nilai Konstan: "SparseSoftmaxCrossEntropyWithLogits"
Metode Publik
Output publik <T> backprop ()
gradien yang dipropagasi mundur (matriks batch_size x num_classes).
Metode pabrik untuk membuat kelas yang membungkus operasi SparseSoftmaxCrossEntropyWithLogits baru.
Parameter
| cakupan | ruang lingkup saat ini |
|---|
| fitur | matriks ukuran_batch x jumlah_kelas |
|---|
| label | vektor batch_size dengan nilai dalam [0, num_classes). Ini adalah label untuk entri minibatch yang diberikan. |
|---|
Kembali
- contoh baru dari SparseSoftmaxCrossEntropyWithLogits
Output publik <T> kerugian ()
Per contoh kerugian (vektor batch_size).
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 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)."]]
