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tensorflow :: operaciones :: RecursoAplicarAdam
#include <training_ops.h>
Actualice '* var' según el algoritmo de Adam.
Resumen
$$lr_t := {learning_rate} * {1 - beta_2^t} / (1 - beta_1^t)$$ $$m_t := beta_1 * m_{t-1} + (1 - beta_1) * g$$ $$v_t := beta_2 * v_{t-1} + (1 - beta_2) * g * g$$ $$variable := variable - lr_t * m_t / ({v_t} + )$$
Argumentos:
- alcance: un objeto de alcance
- var: debe ser de una variable ().
- m: debe ser de una variable ().
- v: debe ser de una variable ().
- beta1_power: debe ser un escalar.
- beta2_power: debe ser un escalar.
- lr: factor de escala. Debe ser un escalar.
- beta1: factor de momento. Debe ser un escalar.
- beta2: factor de momento. Debe ser un escalar.
- épsilon: Término de cresta. Debe ser un escalar.
- grad: El gradiente.
Atributos opcionales (consulte Attrs
):
- use_locking: si es
True
, la actualización de los tensores var, myv estará protegida por un bloqueo; de lo contrario, el comportamiento no está definido, pero puede mostrar menos contención. - use_nesterov: si es
True
, usa la actualización nesterov.
Devoluciones:
Constructores y Destructores |
---|
ResourceApplyAdam (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input m, :: tensorflow::Input v, :: tensorflow::Input beta1_power, :: tensorflow::Input beta2_power, :: tensorflow::Input lr, :: tensorflow::Input beta1, :: tensorflow::Input beta2, :: tensorflow::Input epsilon, :: tensorflow::Input grad)
|
ResourceApplyAdam (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input m, :: tensorflow::Input v, :: tensorflow::Input beta1_power, :: tensorflow::Input beta2_power, :: tensorflow::Input lr, :: tensorflow::Input beta1, :: tensorflow::Input beta2, :: tensorflow::Input epsilon, :: tensorflow::Input grad, const ResourceApplyAdam::Attrs & attrs) |
Atributos públicos
Funciones publicas
RecursoAplicarAdam
ResourceApplyAdam(
const ::tensorflow::Scope & scope,
::tensorflow::Input var,
::tensorflow::Input m,
::tensorflow::Input v,
::tensorflow::Input beta1_power,
::tensorflow::Input beta2_power,
::tensorflow::Input lr,
::tensorflow::Input beta1,
::tensorflow::Input beta2,
::tensorflow::Input epsilon,
::tensorflow::Input grad
)
RecursoAplicarAdam
ResourceApplyAdam(
const ::tensorflow::Scope & scope,
::tensorflow::Input var,
::tensorflow::Input m,
::tensorflow::Input v,
::tensorflow::Input beta1_power,
::tensorflow::Input beta2_power,
::tensorflow::Input lr,
::tensorflow::Input beta1,
::tensorflow::Input beta2,
::tensorflow::Input epsilon,
::tensorflow::Input grad,
const ResourceApplyAdam::Attrs & attrs
)
operador :: tensorflow :: Operación
operator::tensorflow::Operation() const
Funciones estáticas públicas
UseLocking
Attrs UseLocking(
bool x
)
UseNesterov
Attrs UseNesterov(
bool x
)
Salvo que se indique lo contrario, el contenido de esta página está sujeto a la licencia Atribución 4.0 de Creative Commons, y los ejemplos de código están sujetos a la licencia Apache 2.0. Para obtener más información, consulta las políticas del sitio de Google Developers. Java es una marca registrada de Oracle o sus afiliados.
Última actualización: 2020-04-20 (UTC)
[null,null,["Última actualización: 2020-04-20 (UTC)"],[],[],null,["# tensorflow::ops::ResourceApplyAdam Class Reference\n\ntensorflow::ops::ResourceApplyAdam\n==================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate '\\*var' according to the Adam algorithm.\n\nSummary\n-------\n\n$$lr_t := {learning_rate} \\* {1 - beta_2\\^t} / (1 - beta_1\\^t)$$ $$m_t := beta_1 \\* m_{t-1} + (1 - beta_1) \\* g$$ $$v_t := beta_2 \\* v_{t-1} + (1 - beta_2) \\* g \\* g$$ $$variable := variable - lr_t \\* m_t / ({v_t} + )$$\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- m: Should be from a Variable().\n- v: Should be from a Variable().\n- beta1_power: Must be a scalar.\n- beta2_power: Must be a scalar.\n- lr: Scaling factor. Must be a scalar.\n- beta1: Momentum factor. Must be a scalar.\n- beta2: Momentum factor. Must be a scalar.\n- epsilon: Ridge term. Must be a scalar.\n- grad: The gradient.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-adam/attrs#structtensorflow_1_1ops_1_1_resource_apply_adam_1_1_attrs)):\n\n- use_locking: If `True`, updating of the var, m, and v tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.\n- use_nesterov: If `True`, uses the nesterov update.\n\n\u003cbr /\u003e\n\nReturns:\n\n- the created [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ResourceApplyAdam](#classtensorflow_1_1ops_1_1_resource_apply_adam_1ac795afbdb2b0b71ee2d2de82cc60f117)`(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)` m, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` v, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta1_power, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta2_power, ::`[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)` beta1, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta2, ::`[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)` ||\n| [ResourceApplyAdam](#classtensorflow_1_1ops_1_1_resource_apply_adam_1ab1142d9fee53446380bed6cf6ffc3d16)`(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)` m, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` v, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta1_power, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta2_power, ::`[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)` beta1, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` beta2, ::`[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, const `[ResourceApplyAdam::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-adam/attrs#structtensorflow_1_1ops_1_1_resource_apply_adam_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resource_apply_adam_1aabbba4cd6d62166c77e9ac3da3caa0bd) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n\n| ### Public functions ||\n|----------------------------------------------------------------------------------------------------------------------------------|---------|\n| [operator::tensorflow::Operation](#classtensorflow_1_1ops_1_1_resource_apply_adam_1aaf87aff51ef168ae2807151dccb08a18)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_resource_apply_adam_1a608016b3becbe65a6899bb3c0d4c1cf4)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-adam/attrs#structtensorflow_1_1ops_1_1_resource_apply_adam_1_1_attrs) |\n| [UseNesterov](#classtensorflow_1_1ops_1_1_resource_apply_adam_1aa7ac09e230c73e3ee869c80a9eef764d)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-adam/attrs#structtensorflow_1_1ops_1_1_resource_apply_adam_1_1_attrs) |\n\n| ### Structs ||\n|--------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResourceApplyAdam::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-adam/attrs) | Optional attribute setters for [ResourceApplyAdam](/versions/r1.15/api_docs/cc/class/tensorflow/ops/resource-apply-adam#classtensorflow_1_1ops_1_1_resource_apply_adam). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### ResourceApplyAdam\n\n```gdscript\n ResourceApplyAdam(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input m,\n ::tensorflow::Input v,\n ::tensorflow::Input beta1_power,\n ::tensorflow::Input beta2_power,\n ::tensorflow::Input lr,\n ::tensorflow::Input beta1,\n ::tensorflow::Input beta2,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad\n)\n``` \n\n### ResourceApplyAdam\n\n```gdscript\n ResourceApplyAdam(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input m,\n ::tensorflow::Input v,\n ::tensorflow::Input beta1_power,\n ::tensorflow::Input beta2_power,\n ::tensorflow::Input lr,\n ::tensorflow::Input beta1,\n ::tensorflow::Input beta2,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad,\n const ResourceApplyAdam::Attrs & attrs\n)\n``` \n\n### operator::tensorflow::Operation\n\n```gdscript\n operator::tensorflow::Operation() const \n``` \n\nPublic static functions\n-----------------------\n\n### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n``` \n\n### UseNesterov\n\n```text\nAttrs UseNesterov(\n bool x\n)\n```"]]