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aliran tensor:: operasi:: QuantizedBatchNormDenganNormalisasi Global
#include <nn_ops.h> Normalisasi Batch terkuantisasi.
Ringkasan
Operasi ini tidak digunakan lagi dan akan dihapus di masa mendatang. Lebih suka tf.nn.batch_normalization .
Argumen:
- ruang lingkup: Objek Lingkup
- t: Tensor masukan 4D .
- t_min: Nilai yang diwakili oleh input terkuantisasi terendah.
- t_max: Nilai yang diwakili oleh input terkuantisasi tertinggi.
- m: Tensor rata-rata 1D dengan ukuran yang cocok dengan dimensi terakhir t. Ini adalah keluaran pertama dari tf.nn.moments, atau rata-rata pergerakan yang disimpan darinya.
- m_min: Nilai yang diwakili oleh mean terkuantisasi terendah.
- m_max: Nilai yang diwakili oleh mean terkuantisasi tertinggi.
- v: Tensor varians 1D dengan ukuran yang cocok dengan dimensi terakhir t. Ini adalah keluaran kedua dari tf.nn.moments, atau rata-rata pergerakan yang disimpan darinya.
- v_min: Nilai yang diwakili oleh varian terkuantisasi terendah.
- v_max: Nilai yang diwakili oleh varian terkuantisasi tertinggi.
- beta: Tensor beta 1D dengan ukuran yang cocok dengan dimensi terakhir t. Offset yang akan ditambahkan ke tensor yang dinormalisasi.
- beta_min: Nilai yang diwakili oleh offset terkuantisasi terendah.
- beta_max: Nilai yang diwakili oleh offset terkuantisasi tertinggi.
- gamma: Tensor gamma 1D dengan ukuran yang cocok dengan dimensi terakhir t. Jika "scale_after_normalization" benar, tensor ini akan dikalikan dengan tensor yang dinormalisasi.
- gamma_min: Nilai yang diwakili oleh gamma terkuantisasi terendah.
- gamma_max: Nilai yang diwakili oleh gamma terkuantisasi tertinggi.
- variance_epsilon: Angka float kecil untuk menghindari pembagian dengan 0.
- scale_after_normalization: Bool yang menunjukkan apakah tensor yang dihasilkan perlu dikalikan dengan gamma.
Pengembalian:
Konstruktor dan Destruktor |
|---|
QuantizedBatchNormWithGlobalNormalization (const :: tensorflow::Scope & scope, :: tensorflow::Input t, :: tensorflow::Input t_min, :: tensorflow::Input t_max, :: tensorflow::Input m, :: tensorflow::Input m_min, :: tensorflow::Input m_max, :: tensorflow::Input v, :: tensorflow::Input v_min, :: tensorflow::Input v_max, :: tensorflow::Input beta, :: tensorflow::Input beta_min, :: tensorflow::Input beta_max, :: tensorflow::Input gamma, :: tensorflow::Input gamma_min, :: tensorflow::Input gamma_max, DataType out_type, float variance_epsilon, bool scale_after_normalization)
|
Atribut publik
Fungsi publik
QuantizedBatchNormDenganNormalisasi Global
QuantizedBatchNormWithGlobalNormalization(
const ::tensorflow::Scope & scope,
::tensorflow::Input t,
::tensorflow::Input t_min,
::tensorflow::Input t_max,
::tensorflow::Input m,
::tensorflow::Input m_min,
::tensorflow::Input m_max,
::tensorflow::Input v,
::tensorflow::Input v_min,
::tensorflow::Input v_max,
::tensorflow::Input beta,
::tensorflow::Input beta_min,
::tensorflow::Input beta_max,
::tensorflow::Input gamma,
::tensorflow::Input gamma_min,
::tensorflow::Input gamma_max,
DataType out_type,
float variance_epsilon,
bool scale_after_normalization
)
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Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::QuantizedBatchNormWithGlobalNormalization Class Reference\n\ntensorflow::ops::QuantizedBatchNormWithGlobalNormalization\n==========================================================\n\n`#include \u003cnn_ops.h\u003e`\n\nQuantized Batch normalization.\n\nSummary\n-------\n\nThis op is deprecated and will be removed in the future. Prefer `tf.nn.batch_normalization`.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- t: A 4D input [Tensor](/versions/r2.1/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor).\n- t_min: The value represented by the lowest quantized input.\n- t_max: The value represented by the highest quantized input.\n- m: A 1D mean [Tensor](/versions/r2.1/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with size matching the last dimension of t. This is the first output from tf.nn.moments, or a saved moving average thereof.\n- m_min: The value represented by the lowest quantized mean.\n- m_max: The value represented by the highest quantized mean.\n- v: A 1D variance [Tensor](/versions/r2.1/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with size matching the last dimension of t. This is the second output from tf.nn.moments, or a saved moving average thereof.\n- v_min: The value represented by the lowest quantized variance.\n- v_max: The value represented by the highest quantized variance.\n- beta: A 1D beta [Tensor](/versions/r2.1/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with size matching the last dimension of t. An offset to be added to the normalized tensor.\n- beta_min: The value represented by the lowest quantized offset.\n- beta_max: The value represented by the highest quantized offset.\n- gamma: A 1D gamma [Tensor](/versions/r2.1/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with size matching the last dimension of t. If \"scale_after_normalization\" is true, this tensor will be multiplied with the normalized tensor.\n- gamma_min: The value represented by the lowest quantized gamma.\n- gamma_max: The value represented by the highest quantized gamma.\n- variance_epsilon: A small float number to avoid dividing by 0.\n- scale_after_normalization: A bool indicating whether the resulted tensor needs to be multiplied with gamma.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) result\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) result_min\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) result_max\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [QuantizedBatchNormWithGlobalNormalization](#classtensorflow_1_1ops_1_1_quantized_batch_norm_with_global_normalization_1a06c79c043a3a55b798944a5ae0a0f148)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` t, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` t_min, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` t_max, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` m, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` m_min, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` m_max, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` v, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` v_min, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` v_max, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta_min, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta_max, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` gamma, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` gamma_min, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` gamma_max, DataType out_type, float variance_epsilon, bool scale_after_normalization)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_quantized_batch_norm_with_global_normalization_1a84804acca133131cda9e9235b954f9af) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [result](#classtensorflow_1_1ops_1_1_quantized_batch_norm_with_global_normalization_1ab4d42bdea55b03a105681930993cf3d4) | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [result_max](#classtensorflow_1_1ops_1_1_quantized_batch_norm_with_global_normalization_1aacfdd86eadc8f7972ff620b36692ef19) | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [result_min](#classtensorflow_1_1ops_1_1_quantized_batch_norm_with_global_normalization_1a608925a87be94416e98c14506e98fb64) | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### result\n\n```text\n::tensorflow::Output result\n``` \n\n### result_max\n\n```scdoc\n::tensorflow::Output result_max\n``` \n\n### result_min\n\n```scdoc\n::tensorflow::Output result_min\n``` \n\nPublic functions\n----------------\n\n### QuantizedBatchNormWithGlobalNormalization\n\n```gdscript\n QuantizedBatchNormWithGlobalNormalization(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input t,\n ::tensorflow::Input t_min,\n ::tensorflow::Input t_max,\n ::tensorflow::Input m,\n ::tensorflow::Input m_min,\n ::tensorflow::Input m_max,\n ::tensorflow::Input v,\n ::tensorflow::Input v_min,\n ::tensorflow::Input v_max,\n ::tensorflow::Input beta,\n ::tensorflow::Input beta_min,\n ::tensorflow::Input beta_max,\n ::tensorflow::Input gamma,\n ::tensorflow::Input gamma_min,\n ::tensorflow::Input gamma_max,\n DataType out_type,\n float variance_epsilon,\n bool scale_after_normalization\n)\n```"]]
