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tensorflow::ops::ApplyAdam
#include <training_ops.h>
Update '*var' according to the Adam algorithm.
Summary
$$lr_t := {learning_rate} * {1 - beta_2^t} / (1 - beta_1^t)$$ $$m_t := beta_1 * m_{t-1} + (1 - beta_1) * g$$ $$v_t := beta_2 * v_{t-1} + (1 - beta_2) * g * g$$ $$variable := variable - lr_t * m_t / ({v_t} + )$$
Arguments:
- scope: A Scope object
- var: Should be from a Variable().
- m: Should be from a Variable().
- v: Should be from a Variable().
- beta1_power: Must be a scalar.
- beta2_power: Must be a scalar.
- lr: Scaling factor. Must be a scalar.
- beta1: Momentum factor. Must be a scalar.
- beta2: Momentum factor. Must be a scalar.
- epsilon: Ridge term. Must be a scalar.
- grad: The gradient.
Optional attributes (see Attrs
):
- 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.
- use_nesterov: If
True
, uses the nesterov update.
Returns:
Constructors and Destructors
|
ApplyAdam(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)
|
ApplyAdam(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 ApplyAdam::Attrs & attrs)
|
Public attributes
Public functions
ApplyAdam
ApplyAdam(
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
)
ApplyAdam
ApplyAdam(
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 ApplyAdam::Attrs & attrs
)
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
UseLocking
Attrs UseLocking(
bool x
)
UseNesterov
Attrs UseNesterov(
bool x
)
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2020-04-20 UTC.
[null,null,["Last updated 2020-04-20 UTC."],[],[],null,["# tensorflow::ops::ApplyAdam Class Reference\n\ntensorflow::ops::ApplyAdam\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/apply-adam/attrs#structtensorflow_1_1ops_1_1_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- [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| [ApplyAdam](#classtensorflow_1_1ops_1_1_apply_adam_1a63f38ab9210b19bbb905e9d494fd0d7c)`(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| [ApplyAdam](#classtensorflow_1_1ops_1_1_apply_adam_1a23c9c116f231e976487216fbf1d880dd)`(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 `[ApplyAdam::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adam/attrs#structtensorflow_1_1ops_1_1_apply_adam_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_apply_adam_1a56261a4d240b654e6a61c42931d3b847) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_apply_adam_1a51b86c03755b5fa8584c9228a13594d2) | `::`[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_adam_1aca5ba972ba714c19db3728d2dab29a8e)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_apply_adam_1a8e17d2267864bd25f3ab523a287abb8a)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_apply_adam_1a596890f0d578e64a6f55540e249ca5c8)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_apply_adam_1adf5062f34d44b504f428d128fcfecf94)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adam/attrs#structtensorflow_1_1ops_1_1_apply_adam_1_1_attrs) |\n| [UseNesterov](#classtensorflow_1_1ops_1_1_apply_adam_1ae368b25e083d00d0d74551be052064c3)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adam/attrs#structtensorflow_1_1ops_1_1_apply_adam_1_1_attrs) |\n\n| ### Structs ||\n|---------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ApplyAdam::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-adam/attrs) | Optional attribute setters for [ApplyAdam](/versions/r1.15/api_docs/cc/class/tensorflow/ops/apply-adam#classtensorflow_1_1ops_1_1_apply_adam). |\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### ApplyAdam\n\n```gdscript\n ApplyAdam(\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### ApplyAdam\n\n```gdscript\n ApplyAdam(\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 ApplyAdam::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``` \n\n### UseNesterov\n\n```text\nAttrs UseNesterov(\n bool x\n)\n```"]]