Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
tensor akışı:: işlem:: QuantizedConv2D
#include <nn_ops.h>
Nicelenmiş 4B giriş ve filtre tensörleri verildiğinde 2B evrişimi hesaplar.
Özet
Girişler, en düşük değerin ilgili minimumun gerçek sayısını temsil ettiği ve en yüksek değerin maksimumu temsil ettiği nicelenmiş tensörlerdir. Bu, döndürülen minimum ve maksimum değerleri dikkate alarak nicelenmiş çıktıyı yalnızca aynı şekilde yorumlayabileceğiniz anlamına gelir.
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- filtre: filtrenin giriş_derinlik boyutu, girişin derinlik boyutlarıyla eşleşmelidir.
- min_input: En düşük nicelenmiş giriş değerinin temsil ettiği kayan değer.
- max_input: En yüksek nicelenmiş giriş değerinin temsil ettiği kayan değer.
- min_filter: En düşük nicelenmiş filtre değerinin temsil ettiği float değeri.
- max_filter: En yüksek nicelenmiş filtre değerinin temsil ettiği float değeri.
- adımlar: Giriş tensörünün her boyutu için kayan pencerenin adımı.
- padding: Kullanılacak dolgu algoritmasının türü.
İsteğe bağlı özellikler (bkz. Attrs
):
- genişlemeler: 1-D uzunluk tensörü 4.
input
her boyutu için genişleme faktörü. k > 1 olarak ayarlanırsa, o boyuttaki her filtre elemanı arasında k-1 atlanan hücre olacaktır. Boyut sırası data_format
değerine göre belirlenir; ayrıntılar için yukarıya bakın. Parti ve derinlik boyutlarındaki genişlemeler 1 olmalıdır.
İade:
-
Output
çıkışı -
Output
min_output: En düşük nicelenmiş çıkış değerinin temsil ettiği kayan değer. -
Output
max_output: En yüksek nicelenmiş çıkış değerinin temsil ettiği kayan değer.
Yapıcılar ve Yıkıcılar |
---|
QuantizedConv2D (const :: tensorflow::Scope & scope, :: tensorflow::Input input, :: tensorflow::Input filter, :: tensorflow::Input min_input, :: tensorflow::Input max_input, :: tensorflow::Input min_filter, :: tensorflow::Input max_filter, const gtl::ArraySlice< int > & strides, StringPiece padding)
|
QuantizedConv2D (const :: tensorflow::Scope & scope, :: tensorflow::Input input, :: tensorflow::Input filter, :: tensorflow::Input min_input, :: tensorflow::Input max_input, :: tensorflow::Input min_filter, :: tensorflow::Input max_filter, const gtl::ArraySlice< int > & strides, StringPiece padding, const QuantizedConv2D::Attrs & attrs) |
Genel statik işlevler |
---|
Dilations (const gtl::ArraySlice< int > & x) | |
OutType (DataType x) | |
Genel özellikler
Kamu işlevleri
Genel statik işlevler
Dilatasyonlar
Attrs Dilations(
const gtl::ArraySlice< int > & x
)
Çıkış Türü
Attrs OutType(
DataType x
)
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-27 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-27 UTC."],[],[],null,["# tensorflow::ops::QuantizedConv2D Class Reference\n\ntensorflow::ops::QuantizedConv2D\n================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes a 2D convolution given quantized 4D input and filter tensors.\n\nSummary\n-------\n\nThe inputs are quantized tensors where the lowest value represents the real number of the associated minimum, and the highest represents the maximum. This means that you can only interpret the quantized output in the same way, by taking the returned minimum and maximum values into account.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- filter: filter's input_depth dimension must match input's depth dimensions.\n- min_input: The float value that the lowest quantized input value represents.\n- max_input: The float value that the highest quantized input value represents.\n- min_filter: The float value that the lowest quantized filter value represents.\n- max_filter: The float value that the highest quantized filter value represents.\n- strides: The stride of the sliding window for each dimension of the input tensor.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs)):\n\n- dilations: 1-D tensor of length 4. The dilation factor for each dimension of `input`. If set to k \\\u003e 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of `data_format`, see above for details. Dilations in the batch and depth dimensions must be 1.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) min_output: The float value that the lowest quantized output value represents.\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) max_output: The float value that the highest quantized output value represents.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [QuantizedConv2D](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1a8376b9a3557650a011f9c6edb484ec8b)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_input, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_input, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_filter, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_filter, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n| [QuantizedConv2D](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1aa852757615972228954f6d67b3bb8d59)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_input, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_input, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_filter, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_filter, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding, const `[QuantizedConv2D::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [max_output](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1a66d14c5a2888abbc7ae9e711a2fdced8) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [min_output](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1aac559559eda7e4da378605b1b88d3320) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1a36cc12c83f91d1503e6cdeadc7e43272) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1af1401fc53bb8d0556a50807c662bbd61) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public static functions ||\n|-----------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------|\n| [Dilations](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1ae5e27c80b00ace7bafa06479bc01ac5e)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs) |\n| [OutType](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1ad52eb17c8042ea7f90ded915f9f2aa53)`(DataType x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs) |\n\n| ### Structs ||\n|---------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::QuantizedConv2D::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs) | Optional attribute setters for [QuantizedConv2D](/versions/r2.3/api_docs/cc/class/tensorflow/ops/quantized-conv2-d#classtensorflow_1_1ops_1_1_quantized_conv2_d). |\n\nPublic attributes\n-----------------\n\n### max_output\n\n```scdoc\n::tensorflow::Output max_output\n``` \n\n### min_output\n\n```scdoc\n::tensorflow::Output min_output\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### QuantizedConv2D\n\n```gdscript\n QuantizedConv2D(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input filter,\n ::tensorflow::Input min_input,\n ::tensorflow::Input max_input,\n ::tensorflow::Input min_filter,\n ::tensorflow::Input max_filter,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding\n)\n``` \n\n### QuantizedConv2D\n\n```gdscript\n QuantizedConv2D(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input filter,\n ::tensorflow::Input min_input,\n ::tensorflow::Input max_input,\n ::tensorflow::Input min_filter,\n ::tensorflow::Input max_filter,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding,\n const QuantizedConv2D::Attrs & attrs\n)\n``` \n\nPublic static functions\n-----------------------\n\n### Dilations\n\n```gdscript\nAttrs Dilations(\n const gtl::ArraySlice\u003c int \u003e & x\n)\n``` \n\n### OutType\n\n```text\nAttrs OutType(\n DataType x\n)\n```"]]