Svd
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Menghitung dekomposisi eigen dari sekumpulan matriks self-adjoint
(Catatan: Hanya masukan nyata yang didukung).
Menghitung nilai eigen dan vektor eigen matriks M-kali-N terdalam dalam tensor sehingga tensor[...,:,:] = u[..., :, :] * Diag(s[..., :] ) * Mengubah urutan(v[...,:,:]).
Konstanta
Rangkaian | OP_NAME | Nama operasi ini dikenal dengan mesin inti TensorFlow |
Metode Publik
statis <T memperluas TType > Svd <T> | buat ( Lingkup lingkup, Operan <T> a, Long maxIter, Float epsilon, String presisiConfig) Metode pabrik untuk membuat kelas yang membungkus operasi Svd baru. |
Keluaran <T> | |
Keluaran <T> | kamu () Vektor tunggal kiri. |
Keluaran <T> | v () Vektor tunggal kanan. |
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: "XlaSvd"
Metode Publik
Svd statis publik <T> buat ( Lingkup lingkup, Operan <T> a, Long maxIter, Float epsilon, String PrecisionConfig)
Metode pabrik untuk membuat kelas yang membungkus operasi Svd baru.
Parameter
cakupan | ruang lingkup saat ini |
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A | tensor masukan. |
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maxIter | jumlah maksimum pembaruan sapuan, yaitu seluruh bagian segitiga bawah atau bagian segitiga atas berdasarkan parameter yang lebih rendah. Secara heuristik, telah dikemukakan bahwa kira-kira sapuan log(min (M, N)) diperlukan dalam praktiknya (Ref: Golub & van Loan "Perhitungan Matriks"). |
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epsilon | rasio toleransi. |
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konfigurasi presisi | proto xla::PrecisionConfig berseri. |
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Nilai tunggal. Nilai diurutkan dalam urutan terbalik, jadi s[..., 0] adalah nilai terbesar, s[..., 1] adalah nilai terbesar kedua, dan seterusnya.
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Terakhir diperbarui pada 2025-07-27 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-27 UTC."],[],[],null,["# Svd\n\npublic final class **Svd** \nComputes the eigen decomposition of a batch of self-adjoint matrices\n\n\n(Note: Only real inputs are supported).\n\n\nComputes the eigenvalues and eigenvectors of the innermost M-by-N matrices in\ntensor such that tensor\\[...,:,:\\] = u\\[..., :, :\\] \\* Diag(s\\[..., :\\]) \\* Transpose(v\\[...,:,:\\]).\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n### Constants\n\n|--------|-----------------------------------------------------------------|---------------------------------------------------------|\n| String | [OP_NAME](/jvm/api_docs/java/org/tensorflow/op/xla/Svd#OP_NAME) | The name of this op, as known by TensorFlow core engine |\n\n### Public Methods\n\n|---------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| static \\\u003cT extends [TType](/jvm/api_docs/java/org/tensorflow/types/family/TType)\\\u003e [Svd](/jvm/api_docs/java/org/tensorflow/op/xla/Svd)\\\u003cT\\\u003e | [create](/jvm/api_docs/java/org/tensorflow/op/xla/Svd#create(org.tensorflow.op.Scope, org.tensorflow.Operand\u003cT\u003e, java.lang.Long, java.lang.Float, java.lang.String))([Scope](/jvm/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e a, Long maxIter, Float epsilon, String precisionConfig) Factory method to create a class wrapping a new Svd operation. |\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [s](/jvm/api_docs/java/org/tensorflow/op/xla/Svd#s())() Singular values. |\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [u](/jvm/api_docs/java/org/tensorflow/op/xla/Svd#u())() Left singular vectors. |\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [v](/jvm/api_docs/java/org/tensorflow/op/xla/Svd#v())() Right singular vectors. |\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: \"XlaSvd\"\n\nPublic Methods\n--------------\n\n#### public static [Svd](/jvm/api_docs/java/org/tensorflow/op/xla/Svd)\\\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 a, Long maxIter, Float epsilon, String precisionConfig)\n\nFactory method to create a class wrapping a new Svd operation. \n\n##### Parameters\n\n| scope | current scope |\n| a | the input tensor. |\n| maxIter | maximum number of sweep update, i.e., the whole lower triangular part or upper triangular part based on parameter lower. Heuristically, it has been argued that approximately log(min (M, N)) sweeps are needed in practice (Ref: Golub \\& van Loan \"Matrix Computation\"). |\n| epsilon | the tolerance ratio. |\n| precisionConfig | a serialized xla::PrecisionConfig proto. |\n|-----------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n\n##### Returns\n\n- a new instance of Svd \n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e\n**s**\n()\n\nSingular values. The values are sorted in reverse order of magnitude, so\ns\\[..., 0\\] is the largest value, s\\[..., 1\\] is the second largest, etc. \n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e\n**u**\n()\n\nLeft singular vectors. \n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e\n**v**\n()\n\nRight singular vectors."]]