संग्रह की मदद से व्यवस्थित रहें
अपनी प्राथमिकताओं के आधार पर, कॉन्टेंट को सेव करें और कैटगरी में बांटें.
टेंसरफ़्लो:: ऑप्स:: AdagradDA लागू करें
#include <training_ops.h>
समीपस्थ एडाग्रैड योजना के अनुसार '*var' को अपडेट करें।
सारांश
तर्क:
- स्कोप: एक स्कोप ऑब्जेक्ट
- var: एक वेरिएबल() से होना चाहिए।
- gradient_accumulator: एक वेरिएबल() से होना चाहिए।
- gradient_squared_accumulator: एक वेरिएबल() से होना चाहिए।
- ग्रेड: ग्रेडिएंट.
- एलआर: स्केलिंग कारक। एक अदिश राशि होनी चाहिए.
- एल1: एल1 नियमितीकरण। एक अदिश राशि होनी चाहिए.
- एल2: एल2 नियमितीकरण। एक अदिश राशि होनी चाहिए.
- ग्लोबल_स्टेप: प्रशिक्षण चरण संख्या। एक अदिश राशि होनी चाहिए.
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 |
---|
ApplyAdagradDA (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input gradient_accumulator, :: tensorflow::Input gradient_squared_accumulator, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input global_step)
|
ApplyAdagradDA (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input gradient_accumulator, :: tensorflow::Input gradient_squared_accumulator, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input global_step, const ApplyAdagradDA::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 2025-07-26 (UTC) को अपडेट किया गया.
[null,null,["आखिरी बार 2025-07-26 (UTC) को अपडेट किया गया."],[],[],null,["# tensorflow::ops::ApplyAdagradDA Class Reference\n\ntensorflow::ops::ApplyAdagradDA\n===============================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate '\\*var' according to the proximal adagrad scheme.\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- var: Should be from a Variable().\n- gradient_accumulator: Should be from a Variable().\n- gradient_squared_accumulator: Should be from a Variable().\n- grad: The gradient.\n- lr: Scaling factor. Must be a scalar.\n- l1: L1 regularization. Must be a scalar.\n- l2: L2 regularization. Must be a scalar.\n- global_step: Training step number. Must be a scalar.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adagrad-d-a/attrs#structtensorflow_1_1ops_1_1_apply_adagrad_d_a_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| [ApplyAdagradDA](#classtensorflow_1_1ops_1_1_apply_adagrad_d_a_1a9717622961f444da4444a7cad85c1147)`(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)` gradient_accumulator, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` gradient_squared_accumulator, ::`[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)` lr, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l1, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` global_step)` ||\n| [ApplyAdagradDA](#classtensorflow_1_1ops_1_1_apply_adagrad_d_a_1a0176953b80b50c379313cad4ace5ee5e)`(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)` gradient_accumulator, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` gradient_squared_accumulator, ::`[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)` lr, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l1, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` global_step, const `[ApplyAdagradDA::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adagrad-d-a/attrs#structtensorflow_1_1ops_1_1_apply_adagrad_d_a_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_apply_adagrad_d_a_1aeb5c4fba5cf1669a64c356f8beb3f37a) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_apply_adagrad_d_a_1aa81832322b402afc32afca0e2663ba26) | `::`[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_apply_adagrad_d_a_1a6018e2f78356d28e62d64284d1da7e04)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_apply_adagrad_d_a_1a6561d70fc94fe24224939f3680880f4b)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_apply_adagrad_d_a_1a50b9e5a00627be0d50ac540b4a762ed1)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_apply_adagrad_d_a_1afef1833b1630afd75a5b5c41a39b2ed1)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adagrad-d-a/attrs#structtensorflow_1_1ops_1_1_apply_adagrad_d_a_1_1_attrs) |\n\n| ### Structs ||\n|---------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ApplyAdagradDA::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adagrad-d-a/attrs) | Optional attribute setters for [ApplyAdagradDA](/versions/r1.15/api_docs/cc/class/tensorflow/ops/apply-adagrad-d-a#classtensorflow_1_1ops_1_1_apply_adagrad_d_a). |\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### ApplyAdagradDA\n\n```gdscript\n ApplyAdagradDA(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input gradient_accumulator,\n ::tensorflow::Input gradient_squared_accumulator,\n ::tensorflow::Input grad,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input global_step\n)\n``` \n\n### ApplyAdagradDA\n\n```gdscript\n ApplyAdagradDA(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input gradient_accumulator,\n ::tensorflow::Input gradient_squared_accumulator,\n ::tensorflow::Input grad,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input global_step,\n const ApplyAdagradDA::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```"]]