FractionalAvgPool.Options
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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 () |
Metode Publik
Parameter
| deterministik | Jika disetel ke True, wilayah pengumpulan tetap akan digunakan saat melakukan iterasi pada node FractionalAvgPool dalam grafik komputasi. Terutama digunakan dalam pengujian unit untuk membuat FractionalAvgPool bersifat deterministik. |
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Parameter
| tumpang tindih | Jika disetel ke True, artinya saat menggabungkan, nilai pada batas sel gabungan yang berdekatan digunakan oleh kedua sel. Misalnya: `indeks 0 1 2 3 4` `nilai 20 5 16 3 7` Jika urutan pengumpulannya adalah [0, 2, 4], maka 16, pada indeks 2 akan digunakan dua kali. Hasilnya adalah [41/3, 26/3] untuk pengumpulan rata-rata pecahan. |
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Parameter
| pseudoAcak | Jika diatur ke True, menghasilkan urutan pengumpulan secara acak semu, jika tidak, secara acak. Periksa kertas [Benjamin Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071) untuk mengetahui perbedaan antara pseudorandom dan acak. |
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Parameter
| benih | Jika salah satu seed atau seed2 disetel bukan nol, pembuat nomor acak akan diunggulkan oleh seed yang diberikan. Jika tidak, ia akan diunggulkan dengan benih acak. |
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Parameter
| benih2 | Benih kedua untuk menghindari benturan benih. |
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Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[],[],null,["# FractionalAvgPool.Options\n\npublic static class **FractionalAvgPool.Options** \nOptional attributes for [FractionalAvgPool](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool) \n\n### Public Methods\n\n|------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options) | [deterministic](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options#deterministic(java.lang.Boolean))(Boolean deterministic) |\n| [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options) | [overlapping](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options#overlapping(java.lang.Boolean))(Boolean overlapping) |\n| [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options) | [pseudoRandom](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options#pseudoRandom(java.lang.Boolean))(Boolean pseudoRandom) |\n| [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options) | [seed](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options#seed(java.lang.Long))(Long seed) |\n| [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options) | [seed2](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options#seed2(java.lang.Long))(Long seed2) |\n\n### Inherited Methods\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\nPublic Methods\n--------------\n\n#### public [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options)\n**deterministic**\n(Boolean deterministic)\n\n\u003cbr /\u003e\n\n##### Parameters\n\n| deterministic | When set to True, a fixed pooling region will be used when iterating over a FractionalAvgPool node in the computation graph. Mainly used in unit test to make FractionalAvgPool deterministic. |\n|---------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n\n#### public [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options)\n**overlapping**\n(Boolean overlapping)\n\n\u003cbr /\u003e\n\n##### Parameters\n\n| overlapping | When set to True, it means when pooling, the values at the boundary of adjacent pooling cells are used by both cells. For example: \\`index 0 1 2 3 4\\` \\`value 20 5 16 3 7\\` If the pooling sequence is \\[0, 2, 4\\], then 16, at index 2 will be used twice. The result would be \\[41/3, 26/3\\] for fractional avg pooling. \u003cbr /\u003e \u003cbr /\u003e |\n|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n\n#### public [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options)\n**pseudoRandom**\n(Boolean pseudoRandom)\n\n\u003cbr /\u003e\n\n##### Parameters\n\n| pseudoRandom | When set to True, generates the pooling sequence in a pseudorandom fashion, otherwise, in a random fashion. Check paper \\[Benjamin Graham, Fractional Max-Pooling\\](http://arxiv.org/abs/1412.6071) for difference between pseudorandom and random. |\n|--------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n\n#### public [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options)\n**seed**\n(Long seed)\n\n\u003cbr /\u003e\n\n##### Parameters\n\n| seed | If either seed or seed2 are set to be non-zero, the random number generator is seeded by the given seed. Otherwise, it is seeded by a random seed. |\n|------|----------------------------------------------------------------------------------------------------------------------------------------------------|\n\n#### public [FractionalAvgPool.Options](/jvm/api_docs/java/org/tensorflow/op/nn/FractionalAvgPool.Options)\n**seed2**\n(Long seed2)\n\n\u003cbr /\u003e\n\n##### Parameters\n\n| seed2 | An second seed to avoid seed collision. |\n|-------|-----------------------------------------|"]]
