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tensorflow::ops::SparseApplyRMSProp
#include <training_ops.h>
Update '*var' according to the RMSProp algorithm.
Summary
Note that in dense implementation of this algorithm, ms and mom will update even if the grad is zero, but in this sparse implementation, ms and mom will not update in iterations during which the grad is zero.
mean_square = decay * mean_square + (1-decay) * gradient ** 2 Delta = learning_rate * gradient / sqrt(mean_square + epsilon)
$$ms <- rho * ms_{t-1} + (1-rho) * grad * grad$$ $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ $$var <- var - mom$$
Args:
- scope: A Scope object
- var: Should be from a Variable().
- ms: Should be from a Variable().
- mom: Should be from a Variable().
- lr: Scaling factor. Must be a scalar.
- rho: Decay rate. Must be a scalar.
- epsilon: Ridge term. Must be a scalar.
- grad: The gradient.
- indices: A vector of indices into the first dimension of var, ms and mom.
Optional attributes (see Attrs):
- use_locking: If
True, updating of the var, ms, and mom tensors is protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
Returns:
Constructors and Destructors
|
SparseApplyRMSProp(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input ms, ::tensorflow::Input mom, ::tensorflow::Input lr, ::tensorflow::Input rho, ::tensorflow::Input momentum, ::tensorflow::Input epsilon, ::tensorflow::Input grad, ::tensorflow::Input indices)
|
SparseApplyRMSProp(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input ms, ::tensorflow::Input mom, ::tensorflow::Input lr, ::tensorflow::Input rho, ::tensorflow::Input momentum, ::tensorflow::Input epsilon, ::tensorflow::Input grad, ::tensorflow::Input indices, const SparseApplyRMSProp::Attrs & attrs)
|
Public attributes
Public functions
SparseApplyRMSProp
SparseApplyRMSProp(
const ::tensorflow::Scope & scope,
::tensorflow::Input var,
::tensorflow::Input ms,
::tensorflow::Input mom,
::tensorflow::Input lr,
::tensorflow::Input rho,
::tensorflow::Input momentum,
::tensorflow::Input epsilon,
::tensorflow::Input grad,
::tensorflow::Input indices,
const SparseApplyRMSProp::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
)
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Last updated 2022-02-08 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-02-08 UTC."],[],[],null,["# tensorflow::ops::SparseApplyRMSProp Class Reference\n\ntensorflow::ops::SparseApplyRMSProp\n===================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate '\\*var' according to the RMSProp algorithm.\n\nSummary\n-------\n\nNote that in dense implementation of this algorithm, ms and mom will update even if the grad is zero, but in this sparse implementation, ms and mom will not update in iterations during which the grad is zero.\n\nmean_square = decay \\* mean_square + (1-decay) \\* gradient \\*\\* 2 Delta = learning_rate \\* gradient / sqrt(mean_square + epsilon)\n\n$$ms \\\u003c- rho \\* ms_{t-1} + (1-rho) \\* grad \\* grad$$ $$mom \\\u003c- momentum \\* mom_{t-1} + lr \\* grad / sqrt(ms + epsilon)$$ $$var \\\u003c- var - mom$$\n\nArgs:\n\n- scope: A [Scope](/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- var: Should be from a Variable().\n- ms: Should be from a Variable().\n- mom: Should be from a Variable().\n- lr: Scaling factor. Must be a scalar.\n- rho: Decay rate. Must be a scalar.\n- epsilon: Ridge term. Must be a scalar.\n- grad: The gradient.\n- indices: A vector of indices into the first dimension of var, ms and mom.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/api_docs/cc/struct/tensorflow/ops/sparse-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1_1_attrs)):\n\n- use_locking: If `True`, updating of the var, ms, and mom tensors is protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Same as \"var\".\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseApplyRMSProp](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1a294b9022369ff505c3a86a061d7e1e89)`(const ::`[tensorflow::Scope](/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ms, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` mom, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` momentum, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices)` ||\n| [SparseApplyRMSProp](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1ae7e1961797bdee0ed9c2e05e0c6f5b9a)`(const ::`[tensorflow::Scope](/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ms, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` mom, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` momentum, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[SparseApplyRMSProp::Attrs](/api_docs/cc/struct/tensorflow/ops/sparse-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1a47820b04ad723a34e536357b737fd52a) | [Operation](/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1a52eae17378a3e495459e1228a85231f1) | `::`[tensorflow::Output](/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1aaaa68f0bf1d1ae0d39baabfb6cf7e914)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1a3332860de74905325de2385e61f1bf1b)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1afa85184aa4b370ef02ba3659b7183a1a)`() const ` | |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1a0cf09326834a568a3c1cad7cf91129e1)`(bool x)` | [Attrs](/api_docs/cc/struct/tensorflow/ops/sparse-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::SparseApplyRMSProp::Attrs](/api_docs/cc/struct/tensorflow/ops/sparse-apply-r-m-s-prop/attrs) | Optional attribute setters for [SparseApplyRMSProp](/api_docs/cc/class/tensorflow/ops/sparse-apply-r-m-s-prop#classtensorflow_1_1ops_1_1_sparse_apply_r_m_s_prop). |\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### SparseApplyRMSProp\n\n```gdscript\n SparseApplyRMSProp(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input ms,\n ::tensorflow::Input mom,\n ::tensorflow::Input lr,\n ::tensorflow::Input rho,\n ::tensorflow::Input momentum,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices\n)\n``` \n\n### SparseApplyRMSProp\n\n```gdscript\n SparseApplyRMSProp(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input ms,\n ::tensorflow::Input mom,\n ::tensorflow::Input lr,\n ::tensorflow::Input rho,\n ::tensorflow::Input momentum,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices,\n const SparseApplyRMSProp::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```"]]
