Warning: This API is deprecated and will be removed in a future
version of TensorFlow after
the replacement is stable.
RngReadAndSkip
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Advance the counter of a counter-based RNG.
The state of the RNG after
`rng_read_and_skip(n)` will be the same as that after `uniform([n])`
(or any other distribution). The actual increment added to the
counter is an unspecified implementation choice.
In the case that the input algorithm is RNG_ALG_AUTO_SELECT, the counter in the state needs to be of size int64[2], the current maximal counter size among algorithms. In this case, this op will manage the counter as if it is an 128-bit integer with layout [lower_64bits, higher_64bits]. If an algorithm needs less than 128 bits for the counter, it should use the left portion of the int64[2]. In this way, the int64[2] is compatible with all current RNG algorithms (Philox, ThreeFry and xla::RandomAlgorithm::RNG_DEFAULT). Downstream RNG ops can thus use this counter with any RNG algorithm.
Inherited Methods
From class
java.lang.Object
boolean
|
equals(Object arg0)
|
final
Class<?>
|
getClass()
|
int
|
hashCode()
|
final
void
|
notify()
|
final
void
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notifyAll()
|
String
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toString()
|
final
void
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wait(long arg0, int arg1)
|
final
void
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wait(long arg0)
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final
void
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wait()
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Public Methods
public
Output<Long>
asOutput
()
Returns the symbolic handle of a tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is
used to obtain a symbolic handle that represents the computation of the input.
Factory method to create a class wrapping a new RngReadAndSkip operation.
Parameters
scope |
current scope |
resource |
The handle of the resource variable that stores the state of the RNG. The state consists of the counter followed by the key. |
alg |
The RNG algorithm. |
delta |
The amount of advancement. |
Returns
- a new instance of RngReadAndSkip
public
Output<Long>
value
()
The old value of the resource variable, before incrementing. Since state size is algorithm-dependent, this output will be right-padded with zeros to reach shape int64[3] (the current maximal state size among algorithms).
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Last updated 2022-10-27 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 2022-10-27 UTC."],[],[],null,["# RngReadAndSkip\n\npublic final class **RngReadAndSkip** \nAdvance the counter of a counter-based RNG.\n\n\nThe state of the RNG after\n\\`rng_read_and_skip(n)\\` will be the same as that after \\`uniform(\\[n\\])\\`\n(or any other distribution). The actual increment added to the\ncounter is an unspecified implementation choice.\n\n\nIn the case that the input algorithm is RNG_ALG_AUTO_SELECT, the counter in the state needs to be of size int64\\[2\\], the current maximal counter size among algorithms. In this case, this op will manage the counter as if it is an 128-bit integer with layout \\[lower_64bits, higher_64bits\\]. If an algorithm needs less than 128 bits for the counter, it should use the left portion of the int64\\[2\\]. In this way, the int64\\[2\\] is compatible with all current RNG algorithms (Philox, ThreeFry and xla::RandomAlgorithm::RNG_DEFAULT). Downstream RNG ops can thus use this counter with any RNG algorithm.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n### Public Methods\n\n|-------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [Output](/api_docs/java/org/tensorflow/Output)\\\u003cLong\\\u003e | [asOutput](/api_docs/java/org/tensorflow/op/core/RngReadAndSkip#asOutput())() Returns the symbolic handle of a tensor. |\n| static [RngReadAndSkip](/api_docs/java/org/tensorflow/op/core/RngReadAndSkip) | [create](/api_docs/java/org/tensorflow/op/core/RngReadAndSkip#create(org.tensorflow.op.Scope,%20org.tensorflow.Operand\u003c?\u003e,%20org.tensorflow.Operand\u003cjava.lang.Integer\u003e,%20org.tensorflow.Operand\u003c?\u003e))([Scope](/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003c?\\\u003e resource, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003cInteger\\\u003e alg, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003c?\\\u003e delta) Factory method to create a class wrapping a new RngReadAndSkip operation. |\n| [Output](/api_docs/java/org/tensorflow/Output)\\\u003cLong\\\u003e | [value](/api_docs/java/org/tensorflow/op/core/RngReadAndSkip#value())() The old value of the resource variable, before incrementing. |\n\n### Inherited Methods\n\nFrom class [org.tensorflow.op.PrimitiveOp](/api_docs/java/org/tensorflow/op/PrimitiveOp) \n\n|------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------|\n| final boolean | [equals](/api_docs/java/org/tensorflow/op/PrimitiveOp#equals(java.lang.Object))(Object obj) |\n| final int | [hashCode](/api_docs/java/org/tensorflow/op/PrimitiveOp#hashCode())() |\n| [Operation](/api_docs/java/org/tensorflow/Operation) | [op](/api_docs/java/org/tensorflow/op/PrimitiveOp#op())() Returns the underlying [Operation](/api_docs/java/org/tensorflow/Operation) |\n| final String | [toString](/api_docs/java/org/tensorflow/op/PrimitiveOp#toString())() |\n\nFrom class java.lang.Object \n\n|------------------|---------------------------|\n| boolean | equals(Object arg0) |\n| final Class\\\u003c?\\\u003e | getClass() |\n| int | hashCode() |\n| final void | notify() |\n| final void | notifyAll() |\n| String | toString() |\n| final void | wait(long arg0, int arg1) |\n| final void | wait(long arg0) |\n| final void | wait() |\n\nFrom interface [org.tensorflow.Operand](/api_docs/java/org/tensorflow/Operand) \n\n|-----------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| abstract [Output](/api_docs/java/org/tensorflow/Output)\\\u003cLong\\\u003e | [asOutput](/api_docs/java/org/tensorflow/Operand#asOutput())() Returns the symbolic handle of a tensor. |\n\nPublic Methods\n--------------\n\n#### public [Output](/api_docs/java/org/tensorflow/Output)\\\u003cLong\\\u003e\n**asOutput**\n()\n\nReturns the symbolic handle of a tensor.\n\nInputs to TensorFlow operations are outputs of another TensorFlow operation. This method is\nused to obtain a symbolic handle that represents the computation of the input.\n\n\u003cbr /\u003e\n\n#### public static [RngReadAndSkip](/api_docs/java/org/tensorflow/op/core/RngReadAndSkip)\n**create**\n([Scope](/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003c?\\\u003e resource, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003cInteger\\\u003e alg, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003c?\\\u003e delta)\n\nFactory method to create a class wrapping a new RngReadAndSkip operation. \n\n##### Parameters\n\n| scope | current scope |\n| resource | The handle of the resource variable that stores the state of the RNG. The state consists of the counter followed by the key. |\n| alg | The RNG algorithm. |\n| delta | The amount of advancement. |\n|----------|------------------------------------------------------------------------------------------------------------------------------|\n\n##### Returns\n\n- a new instance of RngReadAndSkip \n\n#### public [Output](/api_docs/java/org/tensorflow/Output)\\\u003cLong\\\u003e\n**value**\n()\n\nThe old value of the resource variable, before incrementing. Since state size is algorithm-dependent, this output will be right-padded with zeros to reach shape int64\\[3\\] (the current maximal state size among algorithms)."]]