tf.raw_ops.AccumulateNV2
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Returns the element-wise sum of a list of tensors.
tf.raw_ops.AccumulateNV2(
inputs, shape, name=None
)
tf.accumulate_n_v2 performs the same operation as tf.add_n, but does not
wait for all of its inputs to be ready before beginning to sum. This can
save memory if inputs are ready at different times, since minimum temporary
storage is proportional to the output size rather than the inputs size.
Unlike the original accumulate_n, accumulate_n_v2 is differentiable.
Returns a Tensor of same shape and type as the elements of inputs.
Args |
|---|
inputs
|
A list of at least 1 Tensor objects with the same type in: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, qint16, quint16, uint16, complex128, half, uint32, uint64.
A list of Tensor objects, each with same shape and type.
|
shape
|
A tf.TensorShape or list of ints.
Shape of elements of inputs.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor. Has the same type as inputs.
|
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Last updated 2024-04-26 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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.AccumulateNV2\n\n\u003cbr /\u003e\n\nReturns the element-wise sum of a list of tensors.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.AccumulateNV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/AccumulateNV2)\n\n\u003cbr /\u003e\n\n tf.raw_ops.AccumulateNV2(\n inputs, shape, name=None\n )\n\n`tf.accumulate_n_v2` performs the same operation as [`tf.add_n`](../../tf/math/add_n), but does not\nwait for all of its inputs to be ready before beginning to sum. This can\nsave memory if inputs are ready at different times, since minimum temporary\nstorage is proportional to the output size rather than the inputs size.\n\nUnlike the original `accumulate_n`, `accumulate_n_v2` is differentiable.\n\nReturns a `Tensor` of same shape and type as the elements of `inputs`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `inputs` | A list of at least 1 `Tensor` objects with the same type in: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `qint16`, `quint16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. A list of `Tensor` objects, each with same shape and type. |\n| `shape` | A [`tf.TensorShape`](../../tf/TensorShape) or list of `ints`. Shape of elements of `inputs`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `inputs`. ||\n\n\u003cbr /\u003e"]]
