संग्रह की मदद से व्यवस्थित रहें
अपनी प्राथमिकताओं के आधार पर, कॉन्टेंट को सेव करें और कैटगरी में बांटें.
टेंसरफ़्लो:: ऑप्स:: स्पार्सएप्लाईएडेल्टा
#include <training_ops.h>
var: एक वेरिएबल() से होना चाहिए।
सारांश
तर्क:
- स्कोप: एक स्कोप ऑब्जेक्ट
- संचय: एक वेरिएबल() से होना चाहिए।
- accum_update: : एक वेरिएबल() से होना चाहिए।
- एलआर: सीखने की दर. एक अदिश राशि होनी चाहिए.
- आरएचओ: क्षय कारक। एक अदिश राशि होनी चाहिए.
- एप्सिलॉन: लगातार कारक। एक अदिश राशि होनी चाहिए.
- ग्रेड: ग्रेडिएंट.
- सूचकांक: var और accum के पहले आयाम में सूचकांकों का एक वेक्टर।
वैकल्पिक विशेषताएँ (देखें Attrs
):
- उपयोग_लॉकिंग: यदि सत्य है, तो var और Accum Tensors का अद्यतन एक लॉक द्वारा संरक्षित किया जाएगा; अन्यथा व्यवहार अपरिभाषित है, लेकिन कम विवाद प्रदर्शित कर सकता है।
रिटर्न:
निर्माता और विध्वंसक |
---|
SparseApplyAdadelta (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input accum_update, :: tensorflow::Input lr, :: tensorflow::Input rho, :: tensorflow::Input epsilon, :: tensorflow::Input grad, :: tensorflow::Input indices)
|
SparseApplyAdadelta (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input accum_update, :: tensorflow::Input lr, :: tensorflow::Input rho, :: tensorflow::Input epsilon, :: tensorflow::Input grad, :: tensorflow::Input indices, const SparseApplyAdadelta::Attrs & attrs) |
सार्वजनिक गुण
सार्वजनिक समारोह
नोड
::tensorflow::Node * node() const
operator::tensorflow::Input() const
ऑपरेटर::टेन्सरफ़्लो::आउटपुट
operator::tensorflow::Output() const
सार्वजनिक स्थैतिक कार्य
लॉकिंग का उपयोग करें
Attrs UseLocking(
bool x
)
जब तक कुछ अलग से न बताया जाए, तब तक इस पेज की सामग्री को Creative Commons Attribution 4.0 License के तहत और कोड के नमूनों को Apache 2.0 License के तहत लाइसेंस मिला है. ज़्यादा जानकारी के लिए, Google Developers साइट नीतियां देखें. Oracle और/या इससे जुड़ी हुई कंपनियों का, Java एक रजिस्टर किया हुआ ट्रेडमार्क है.
आखिरी बार 2025-07-25 (UTC) को अपडेट किया गया.
[null,null,["आखिरी बार 2025-07-25 (UTC) को अपडेट किया गया."],[],[],null,["# tensorflow::ops::SparseApplyAdadelta Class Reference\n\ntensorflow::ops::SparseApplyAdadelta\n====================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nvar: Should be from a Variable().\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- accum: Should be from a Variable().\n- accum_update: : Should be from a Variable().\n- lr: Learning rate. Must be a scalar.\n- rho: Decay factor. Must be a scalar.\n- epsilon: Constant factor. Must be a scalar.\n- grad: The gradient.\n- indices: A vector of indices into the first dimension of var and accum.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-apply-adadelta/attrs#structtensorflow_1_1ops_1_1_sparse_apply_adadelta_1_1_attrs)):\n\n- use_locking: If True, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Same as \"var\".\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseApplyAdadelta](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1a10346d215f776d3e4336554f052545cb)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum_update, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices)` ||\n| [SparseApplyAdadelta](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1a9a4a32f0d7bc40f4c2f4960151b6652d)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum_update, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[SparseApplyAdadelta::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-apply-adadelta/attrs#structtensorflow_1_1ops_1_1_sparse_apply_adadelta_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1a24902e3a0d9ef60b0d3b286887554f70) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1a50eabd8a7e93bf722f57c0af4c445d20) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1afb4c76f26417ba0b14db299bca528f40)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1a7bbe6b4f17ecf1a92a119908aba54c77)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1a18310637d40bc623ca8f548c13bb54aa)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|--------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_sparse_apply_adadelta_1acbdbc14d33d39c6d7e41685963b0a775)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-apply-adadelta/attrs#structtensorflow_1_1ops_1_1_sparse_apply_adadelta_1_1_attrs) |\n\n| ### Structs ||\n|------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::SparseApplyAdadelta::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-apply-adadelta/attrs) | Optional attribute setters for [SparseApplyAdadelta](/versions/r1.15/api_docs/cc/class/tensorflow/ops/sparse-apply-adadelta#classtensorflow_1_1ops_1_1_sparse_apply_adadelta). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### out\n\n```text\n::tensorflow::Output out\n``` \n\nPublic functions\n----------------\n\n### SparseApplyAdadelta\n\n```gdscript\n SparseApplyAdadelta(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input accum_update,\n ::tensorflow::Input lr,\n ::tensorflow::Input rho,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices\n)\n``` \n\n### SparseApplyAdadelta\n\n```gdscript\n SparseApplyAdadelta(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input accum_update,\n ::tensorflow::Input lr,\n ::tensorflow::Input rho,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices,\n const SparseApplyAdadelta::Attrs & attrs\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n``` \n\nPublic static functions\n-----------------------\n\n### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n```"]]