DeserializeManySparse
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Deserialisasi dan gabungkan `SparseTensors` dari minibatch serial.
Input `serialized_sparse` harus berupa matriks string berbentuk `[N x 3]` dengan `N` adalah ukuran minibatch dan baris-barisnya sesuai dengan output yang dikemas dari `SerializeSparse`. Peringkat objek `SparseTensor` asli semuanya harus cocok. Saat `SparseTensor` terakhir dibuat, peringkatnya satu lebih tinggi daripada peringkat objek `SparseTensor` yang masuk (objek tersebut telah digabungkan di sepanjang dimensi baris baru).
Nilai bentuk objek `SparseTensor` keluaran untuk semua dimensi tetapi yang pertama adalah nilai maksimal seluruh nilai bentuk objek `SparseTensor` masukan untuk dimensi yang sesuai. Nilai bentuk pertamanya adalah `N`, ukuran minibatch.
Indeks objek `SparseTensor` masukan diasumsikan diurutkan dalam urutan leksikografis standar. Jika tidak demikian, setelah langkah ini jalankan `SparseReorder` untuk memulihkan pengurutan indeks.
Misalnya, jika input serial adalah matriks `[2 x 3]` yang mewakili dua objek `SparseTensor` asli:
indeks = [ 0] [10] [20] nilai = [1, 2, 3] bentuk = [50]
Dan
indeks = [ 2] [10] nilai = [4, 5] bentuk = [30]
maka `SparseTensor` terakhir yang dideserialisasi akan menjadi:
indeks = [0 0] [0 10] [0 20] [1 2] [1 10] nilai = [1, 2, 3, 4, 5] bentuk = [2 50]
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: "DeserializeManySparse"
Metode Publik
Metode pabrik untuk membuat kelas yang membungkus operasi DeserializeManySparse baru.
Parameter
| cakupan | ruang lingkup saat ini |
|---|
| berseriSparse | 2-D, Objek `SparseTensor` berseri `N`. Harus memiliki 3 kolom. |
|---|
| tipe | `dtype` dari objek `SparseTensor` yang diserialkan. |
|---|
Kembali
- contoh baru dari DeserializeManySparse
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Terakhir diperbarui pada 2025-07-25 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-25 UTC."],[],[],null,["# DeserializeManySparse\n\npublic final class **DeserializeManySparse** \nDeserialize and concatenate \\`SparseTensors\\` from a serialized minibatch.\n\n\nThe input \\`serialized_sparse\\` must be a string matrix of shape \\`\\[N x 3\\]\\` where\n\\`N\\` is the minibatch size and the rows correspond to packed outputs of\n\\`SerializeSparse\\`. The ranks of the original \\`SparseTensor\\` objects\nmust all match. When the final \\`SparseTensor\\` is created, it has rank one\nhigher than the ranks of the incoming \\`SparseTensor\\` objects\n(they have been concatenated along a new row dimension).\n\n\nThe output \\`SparseTensor\\` object's shape values for all dimensions but the\nfirst are the max across the input \\`SparseTensor\\` objects' shape values\nfor the corresponding dimensions. Its first shape value is \\`N\\`, the minibatch\nsize.\n\n\nThe input \\`SparseTensor\\` objects' indices are assumed ordered in\nstandard lexicographic order. If this is not the case, after this\nstep run \\`SparseReorder\\` to restore index ordering.\n\n\nFor example, if the serialized input is a \\`\\[2 x 3\\]\\` matrix representing two\noriginal \\`SparseTensor\\` objects:\n\n\nindex = \\[ 0\\]\n\\[10\\]\n\\[20\\]\nvalues = \\[1, 2, 3\\]\nshape = \\[50\\]\n\n\nand\n\n\nindex = \\[ 2\\]\n\\[10\\]\nvalues = \\[4, 5\\]\nshape = \\[30\\]\n\n\nthen the final deserialized \\`SparseTensor\\` will be:\n\n\nindex = \\[0 0\\]\n\\[0 10\\]\n\\[0 20\\]\n\\[1 2\\]\n\\[1 10\\]\nvalues = \\[1, 2, 3, 4, 5\\]\nshape = \\[2 50\\]\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n### Constants\n\n|--------|----------------------------------------------------------------------------------|---------------------------------------------------------|\n| String | [OP_NAME](/jvm/api_docs/java/org/tensorflow/op/io/DeserializeManySparse#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 [DeserializeManySparse](/jvm/api_docs/java/org/tensorflow/op/io/DeserializeManySparse)\\\u003cT\\\u003e | [create](/jvm/api_docs/java/org/tensorflow/op/io/DeserializeManySparse#create(org.tensorflow.op.Scope, org.tensorflow.Operand\u003corg.tensorflow.types.TString\u003e, java.lang.Class\u003cT\u003e))([Scope](/jvm/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003c[TString](/jvm/api_docs/java/org/tensorflow/types/TString)\\\u003e serializedSparse, Class\\\u003cT\\\u003e dtype) Factory method to create a class wrapping a new DeserializeManySparse operation. |\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003c[TInt64](/jvm/api_docs/java/org/tensorflow/types/TInt64)\\\u003e | [sparseIndices](/jvm/api_docs/java/org/tensorflow/op/io/DeserializeManySparse#sparseIndices())() |\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003c[TInt64](/jvm/api_docs/java/org/tensorflow/types/TInt64)\\\u003e | [sparseShape](/jvm/api_docs/java/org/tensorflow/op/io/DeserializeManySparse#sparseShape())() |\n| [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [sparseValues](/jvm/api_docs/java/org/tensorflow/op/io/DeserializeManySparse#sparseValues())() |\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: \"DeserializeManySparse\"\n\nPublic Methods\n--------------\n\n#### public static [DeserializeManySparse](/jvm/api_docs/java/org/tensorflow/op/io/DeserializeManySparse)\\\u003cT\\\u003e\n**create**\n([Scope](/jvm/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003c[TString](/jvm/api_docs/java/org/tensorflow/types/TString)\\\u003e serializedSparse, Class\\\u003cT\\\u003e dtype)\n\nFactory method to create a class wrapping a new DeserializeManySparse operation. \n\n##### Parameters\n\n| scope | current scope |\n| serializedSparse | 2-D, The \\`N\\` serialized \\`SparseTensor\\` objects. Must have 3 columns. |\n| dtype | The \\`dtype\\` of the serialized \\`SparseTensor\\` objects. |\n|------------------|--------------------------------------------------------------------------|\n\n##### Returns\n\n- a new instance of DeserializeManySparse \n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003c[TInt64](/jvm/api_docs/java/org/tensorflow/types/TInt64)\\\u003e\n**sparseIndices**\n()\n\n\u003cbr /\u003e\n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003c[TInt64](/jvm/api_docs/java/org/tensorflow/types/TInt64)\\\u003e\n**sparseShape**\n()\n\n\u003cbr /\u003e\n\n#### public [Output](/jvm/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e\n**sparseValues**\n()\n\n\u003cbr /\u003e"]]
