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tensorflow:: operaciones:: Dispersión mínima
#include <state_ops.h>
Reduce las actualizaciones escasas en una referencia variable mediante la operación min .
Resumen
Esta operación calcula
# Scalar indices
ref[indices, ...] = min(ref[indices, ...], updates[...])
# Vector indices (for each i)
ref[indices[i], ...] = min(ref[indices[i], ...], updates[i, ...])
# High rank indices (for each i, ..., j)
ref[indices[i, ..., j], ...] = min(ref[indices[i, ..., j], ...], updates[i, ..., j, ...])
Esta operación genera una ref después de que se realiza la actualización. Esto hace que sea más fácil encadenar operaciones que necesitan usar el valor de reinicio.
Las entradas duplicadas se manejan correctamente: si varios indices hacen referencia a la misma ubicación, sus contribuciones se combinan.
use_locking: si es True, la actualización estará protegida por un candado; de lo contrario, el comportamiento no está definido, pero puede exhibir menos contención.
Devoluciones:
Output : = Igual que la ref . Devuelto como una conveniencia para las operaciones que desean usar los valores actualizados después de que se realiza la actualización.
[null,null,["Última actualización: 2022-11-04 (UTC)"],[],[],null,["# tensorflow::ops::ScatterMin Class Reference\n\ntensorflow::ops::ScatterMin\n===========================\n\n`#include \u003cstate_ops.h\u003e`\n\nReduces sparse updates into a variable reference using the `min` operation.\n\nSummary\n-------\n\nThis operation computes \n\n```transact-sql\n# Scalar indices\nref[indices, ...] = min(ref[indices, ...], updates[...])\n\n# Vector indices (for each i)\nref[indices[i], ...] = min(ref[indices[i], ...], updates[i, ...])\n\n# High rank indices (for each i, ..., j)\nref[indices[i, ..., j], ...] = min(ref[indices[i, ..., j], ...], updates[i, ..., j, ...])\n```\n\n\u003cbr /\u003e\n\nThis operation outputs `ref` after the update is done. This makes it easier to chain operations that need to use the reset value.\n\nDuplicate entries are handled correctly: if multiple `indices` reference the same location, their contributions combine.\n\nRequires `updates.shape = indices.shape + ref.shape[1:]` or `updates.shape = []`.\n\n\n\u003cbr /\u003e\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- ref: Should be from a [Variable](/versions/r2.3/api_docs/cc/class/tensorflow/ops/variable#classtensorflow_1_1ops_1_1_variable) node.\n- indices: A tensor of indices into the first dimension of `ref`.\n- updates: A tensor of updated values to reduce into `ref`.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/scatter-min/attrs#structtensorflow_1_1ops_1_1_scatter_min_1_1_attrs)):\n\n- use_locking: If True, the update 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 `ref`. Returned as a convenience for operations that want to use the updated values after the update is done.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ScatterMin](#classtensorflow_1_1ops_1_1_scatter_min_1a20672036c077b2295fe3b7f263f1cbbc)`(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)` ref, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` updates)` ||\n| [ScatterMin](#classtensorflow_1_1ops_1_1_scatter_min_1a970f0ae60aca198d4ff561223d356190)`(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)` ref, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` updates, const `[ScatterMin::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/scatter-min/attrs#structtensorflow_1_1ops_1_1_scatter_min_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_scatter_min_1a6b8f4f0a291a0a5110af72304126dfda) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output_ref](#classtensorflow_1_1ops_1_1_scatter_min_1a246255cec7f7a96a7aaec14b4b44b6b7) | `::`[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_scatter_min_1ad2e63dcee002a733c8a1c255be7b2683)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_scatter_min_1a8938d32752649aeaeba42f68891ababc)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_scatter_min_1af6605bb1184a6c918a33ba5d6389874b)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_scatter_min_1a81d4614aac5d7b4ec68e2513034b2970)`(bool x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/scatter-min/attrs#structtensorflow_1_1ops_1_1_scatter_min_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ScatterMin::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/scatter-min/attrs) | Optional attribute setters for [ScatterMin](/versions/r2.3/api_docs/cc/class/tensorflow/ops/scatter-min#classtensorflow_1_1ops_1_1_scatter_min). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output_ref\n\n```scdoc\n::tensorflow::Output output_ref\n``` \n\nPublic functions\n----------------\n\n### ScatterMin\n\n```gdscript\n ScatterMin(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input ref,\n ::tensorflow::Input indices,\n ::tensorflow::Input updates\n)\n``` \n\n### ScatterMin\n\n```gdscript\n ScatterMin(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input ref,\n ::tensorflow::Input indices,\n ::tensorflow::Input updates,\n const ScatterMin::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```"]]