tensorflow:: אופס:: DynamicPartition
#include <data_flow_ops.h>
מחלק data
לטנזורים num_partitions
באמצעות מדדים partitions
.
תַקצִיר
עבור כל אינדקס tuple js
בגודל partitions.ndim
, data[js, ...]
הופכים לחלק outputs[partitions[js]]
. הפרוסות עם partitions[js] = i
ממוקמות outputs[i]
בסדר לקסיקוגרפי של js
, והממד הראשון של outputs[i]
הוא מספר הערכים partitions
השווה ל- i
. בפירוט,
outputs[i].shape = [sum(partitions == i)] + data.shape[partitions.ndim:]
outputs[i] = pack([data[js, ...] for js if partitions[js] == i])
data.shape
חייב להתחיל עם partitions.shape
.
לְדוּגמָה:
# Scalar partitions. partitions = 1 num_partitions = 2 data = [10, 20] outputs[0] = [] # Empty with shape [0, 2] outputs[1] = [[10, 20]]
# Vector partitions. partitions = [0, 0, 1, 1, 0] num_partitions = 2 data = [10, 20, 30, 40, 50] outputs[0] = [10, 20, 50] outputs[1] = [30, 40]
ראה dynamic_stitch
לדוגמא כיצד למזג מחיצות בחזרה.
טיעונים:
- scope: אובייקט Scope
- מחיצות: כל צורה. מדדים בטווח
[0, num_partitions)
. - num_partitions: מספר המחיצות לפלט.
החזרות:
-
OutputList
: טנסור הפלטים.
בנאים והורסים | |
---|---|
DynamicPartition (const :: tensorflow::Scope & scope, :: tensorflow::Input data, :: tensorflow::Input partitions, int64 num_partitions) |
תכונות ציבוריות | |
---|---|
operation | |
outputs |
תפקידים ציבוריים | |
---|---|
operator[] (size_t index) const |
תכונות ציבוריות
מִבצָע
Operation operation
תפוקות
::tensorflow::OutputList outputs
תפקידים ציבוריים
DynamicPartition
DynamicPartition( const ::tensorflow::Scope & scope, ::tensorflow::Input data, ::tensorflow::Input partitions, int64 num_partitions )
מַפעִיל[]
::tensorflow::Output operator[]( size_t index ) const
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עדכון אחרון: 2025-07-25 (שעון UTC).
[null,null,["עדכון אחרון: 2025-07-25 (שעון UTC)."],[],[],null,["# tensorflow::ops::DynamicPartition Class Reference\n\ntensorflow::ops::DynamicPartition\n=================================\n\n`#include \u003cdata_flow_ops.h\u003e`\n\nPartitions `data` into `num_partitions` tensors using indices from `partitions`.\n\nSummary\n-------\n\nFor each index tuple `js` of size `partitions.ndim`, the slice `data[js, ...]` becomes part of `outputs[partitions[js]]`. The slices with `partitions[js] = i` are placed in `outputs[i]` in lexicographic order of `js`, and the first dimension of `outputs[i]` is the number of entries in `partitions` equal to `i`. In detail,\n\n\n```transact-sql\n outputs[i].shape = [sum(partitions == i)] + data.shape[partitions.ndim:]\n```\n\n\u003cbr /\u003e\n\n\n```transact-sql\n outputs[i] = pack([data[js, ...] for js if partitions[js] == i])\n```\n\n\u003cbr /\u003e\n\n`data.shape` must start with `partitions.shape`.\n\nFor example:\n\n\n```scdoc\n # Scalar partitions.\n partitions = 1\n num_partitions = 2\n data = [10, 20]\n outputs[0] = [] # Empty with shape [0, 2]\n outputs[1] = [[10, 20]]\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\n # Vector partitions.\n partitions = [0, 0, 1, 1, 0]\n num_partitions = 2\n data = [10, 20, 30, 40, 50]\n outputs[0] = [10, 20, 50]\n outputs[1] = [30, 40]\n```\n\n\u003cbr /\u003e\n\nSee `dynamic_stitch` for an example on how to merge partitions back.\n\n\n\u003cbr /\u003e\n\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- partitions: [Any](/versions/r2.1/api_docs/cc/class/tensorflow/ops/any#classtensorflow_1_1ops_1_1_any) shape. Indices in the range `[0, num_partitions)`.\n- num_partitions: The number of partitions to output.\n\n\u003cbr /\u003e\n\nReturns:\n\n- `OutputList`: The outputs tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [DynamicPartition](#classtensorflow_1_1ops_1_1_dynamic_partition_1a3054ef5ab4e012816521a61a98ff1cb8)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` data, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` partitions, int64 num_partitions)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_dynamic_partition_1ae34cf25c6a4f479e6eab33dd8d6c7bca) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [outputs](#classtensorflow_1_1ops_1_1_dynamic_partition_1ac93870bad9fb8ccd554d368930d608c0) | `::`[tensorflow::OutputList](/versions/r2.1/api_docs/cc/group/core#group__core_1gab449e6a3abd500c2f4ea93f9e89ba96c) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operator[]](#classtensorflow_1_1ops_1_1_dynamic_partition_1a69567b14d471387c73d2e2240c59d645)`(size_t index) const ` | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### outputs\n\n```text\n::tensorflow::OutputList outputs\n``` \n\nPublic functions\n----------------\n\n### DynamicPartition\n\n```gdscript\n DynamicPartition(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input data,\n ::tensorflow::Input partitions,\n int64 num_partitions\n)\n``` \n\n### operator\\[\\]\n\n```gdscript\n::tensorflow::Output operator[](\n size_t index\n) const \n```"]]