संग्रह की मदद से व्यवस्थित रहें
अपनी प्राथमिकताओं के आधार पर, कॉन्टेंट को सेव करें और कैटगरी में बांटें.
टेंसरफ़्लो:: ऑप्स:: ApplyFtrlV2
#include <training_ops.h>
Ftrl-प्रॉक्सिमल योजना के अनुसार '*var' को अपडेट करें।
सारांश
ग्रेड_विथ_श्रिंकेज = ग्रेड + 2 * एल2_श्रिंकेज * वर एक्युम_न्यू = एक्यूम + ग्रेड * ग्रेड लीनियर += ग्रेड_विद_श्रिंकेज - (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var क्वाड्रैटिक = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2 var = (चिह्न(रैखिक) * l1 - रैखिक) / द्विघात यदि |रैखिक| > एल1 अन्यथा 0.0 संचय = संचय_नया
तर्क:
- स्कोप: एक स्कोप ऑब्जेक्ट
- var: एक वेरिएबल() से होना चाहिए।
- संचय: एक वेरिएबल() से होना चाहिए।
- रैखिक: 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 सिकुड़न नियमितीकरण। एक अदिश राशि होनी चाहिए.
- lr_power: स्केलिंग कारक। एक अदिश राशि होनी चाहिए.
वैकल्पिक विशेषताएँ (देखें Attrs
):
- उपयोग_लॉकिंग: यदि
True
, तो var और Accum Tensors का अद्यतनीकरण लॉक द्वारा संरक्षित किया जाएगा; अन्यथा व्यवहार अपरिभाषित है, लेकिन कम विवाद प्रदर्शित कर सकता है।
रिटर्न:
निर्माता और विध्वंसक |
---|
ApplyFtrlV2 (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input l2_shrinkage, :: tensorflow::Input lr_power)
|
ApplyFtrlV2 (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input l2_shrinkage, :: tensorflow::Input lr_power, const ApplyFtrlV2::Attrs & attrs) |
सार्वजनिक गुण
सार्वजनिक समारोह
ApplyFtrlV2
ApplyFtrlV2(
const ::tensorflow::Scope & scope,
::tensorflow::Input var,
::tensorflow::Input accum,
::tensorflow::Input linear,
::tensorflow::Input grad,
::tensorflow::Input lr,
::tensorflow::Input l1,
::tensorflow::Input l2,
::tensorflow::Input l2_shrinkage,
::tensorflow::Input lr_power,
const ApplyFtrlV2::Attrs & attrs
)
नोड
::tensorflow::Node * node() const
operator::tensorflow::Input() const
ऑपरेटर::टेन्सरफ़्लो::आउटपुट
operator::tensorflow::Output() const
सार्वजनिक स्थैतिक कार्य
MultiplyLinearByLr
Attrs MultiplyLinearByLr(
bool x
)
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 2025-07-27 (UTC) को अपडेट किया गया.
[null,null,["आखिरी बार 2025-07-27 (UTC) को अपडेट किया गया."],[],[],null,["# tensorflow::ops::ApplyFtrlV2 Class Reference\n\ntensorflow::ops::ApplyFtrlV2\n============================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate '\\*var' according to the Ftrl-proximal scheme.\n\nSummary\n-------\n\ngrad_with_shrinkage = grad + 2 \\* l2_shrinkage \\* var accum_new = accum + grad \\* grad linear += grad_with_shrinkage - (accum_new\\^(-lr_power) - accum\\^(-lr_power)) / lr \\* var quadratic = 1.0 / (accum_new\\^(lr_power) \\* lr) + 2 \\* l2 var = (sign(linear) \\* l1 - linear) / quadratic if \\|linear\\| \\\u003e l1 else 0.0 accum = accum_new\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- var: Should be from a Variable().\n- accum: Should be from a Variable().\n- linear: 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 shrinkage regularization. Must be a scalar.\n- lr_power: Scaling factor. Must be a scalar.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/apply-ftrl-v2/attrs#structtensorflow_1_1ops_1_1_apply_ftrl_v2_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/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Same as \"var\".\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ApplyFtrlV2](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1add964fb0f6de2aa24265dcd061c72151)`(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)` var, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` linear, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l1, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2_shrinkage, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr_power)` ||\n| [ApplyFtrlV2](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1a0b32d8c13b43426f739ff6590cd07303)`(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)` var, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` linear, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l1, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2_shrinkage, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr_power, const `[ApplyFtrlV2::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/apply-ftrl-v2/attrs#structtensorflow_1_1ops_1_1_apply_ftrl_v2_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1aff11a6d3c5a685a3bce58b6eba270910) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1a37c9c6929132980b64306940e4296ed2) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1ab2dafdb4818ad20aa0e4eed79cfba879)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1a1aede95dcc376ee0ac6c62cfe06d7314)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1a331dd3212dc856b76c62ccc135c74656)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|--------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------|\n| [MultiplyLinearByLr](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1aad4be57c71c744c8f188d58e39c7c910)`(bool x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/apply-ftrl-v2/attrs#structtensorflow_1_1ops_1_1_apply_ftrl_v2_1_1_attrs) |\n| [UseLocking](#classtensorflow_1_1ops_1_1_apply_ftrl_v2_1a5c25a36e1a6eef1e216f631e173e3e42)`(bool x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/apply-ftrl-v2/attrs#structtensorflow_1_1ops_1_1_apply_ftrl_v2_1_1_attrs) |\n\n| ### Structs ||\n|-------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ApplyFtrlV2::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/apply-ftrl-v2/attrs) | Optional attribute setters for [ApplyFtrlV2](/versions/r2.3/api_docs/cc/class/tensorflow/ops/apply-ftrl-v2#classtensorflow_1_1ops_1_1_apply_ftrl_v2). |\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### ApplyFtrlV2\n\n```gdscript\n ApplyFtrlV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input linear,\n ::tensorflow::Input grad,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input l2_shrinkage,\n ::tensorflow::Input lr_power\n)\n``` \n\n### ApplyFtrlV2\n\n```gdscript\n ApplyFtrlV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input linear,\n ::tensorflow::Input grad,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input l2_shrinkage,\n ::tensorflow::Input lr_power,\n const ApplyFtrlV2::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### MultiplyLinearByLr\n\n```text\nAttrs MultiplyLinearByLr(\n bool x\n)\n``` \n\n### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n```"]]