Warning: This API is deprecated and will be removed in a future
version of TensorFlow after
the replacement is stable.
MirrorPad
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Pads a tensor with mirrored values.
This operation pads a `input` with mirrored values according to the `paddings`
you specify. `paddings` is an integer tensor with shape `[n, 2]`, where n is
the rank of `input`. For each dimension D of `input`, `paddings[D, 0]` indicates
how many values to add before the contents of `input` in that dimension, and
`paddings[D, 1]` indicates how many values to add after the contents of `input`
in that dimension. Both `paddings[D, 0]` and `paddings[D, 1]` must be no greater
than `input.dim_size(D)` (or `input.dim_size(D) - 1`) if `copy_border` is true
(if false, respectively).
The padded size of each dimension D of the output is:
`paddings(D, 0) + input.dim_size(D) + paddings(D, 1)`
For example:
# 't' is [[1, 2, 3], [4, 5, 6]].
# 'paddings' is [[1, 1]], [2, 2]].
# 'mode' is SYMMETRIC.
# rank of 't' is 2.
pad(t, paddings) ==> [[2, 1, 1, 2, 3, 3, 2]
[2, 1, 1, 2, 3, 3, 2]
[5, 4, 4, 5, 6, 6, 5]
[5, 4, 4, 5, 6, 6, 5]]
Inherited Methods
From class
java.lang.Object
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boolean
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equals(Object arg0)
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final
Class<?>
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getClass()
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int
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hashCode()
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final
void
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notify()
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final
void
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notifyAll()
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String
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toString()
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final
void
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wait(long arg0, int arg1)
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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<T>
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 MirrorPad operation.
Parameters
| scope |
current scope |
| input |
The input tensor to be padded. |
| paddings |
A two-column matrix specifying the padding sizes. The number of
rows must be the same as the rank of `input`. |
| mode |
Either `REFLECT` or `SYMMETRIC`. In reflect mode the padded regions
do not include the borders, while in symmetric mode the padded regions
do include the borders. For example, if `input` is `[1, 2, 3]` and `paddings`
is `[0, 2]`, then the output is `[1, 2, 3, 2, 1]` in reflect mode, and
it is `[1, 2, 3, 3, 2]` in symmetric mode. |
Returns
- a new instance of MirrorPad
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2022-02-12 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 2022-02-12 UTC."],[],[],null,["# MirrorPad\n\npublic final class **MirrorPad** \nPads a tensor with mirrored values.\n\n\nThis operation pads a \\`input\\` with mirrored values according to the \\`paddings\\`\nyou specify. \\`paddings\\` is an integer tensor with shape \\`\\[n, 2\\]\\`, where n is\nthe rank of \\`input\\`. For each dimension D of \\`input\\`, \\`paddings\\[D, 0\\]\\` indicates\nhow many values to add before the contents of \\`input\\` in that dimension, and\n\\`paddings\\[D, 1\\]\\` indicates how many values to add after the contents of \\`input\\`\nin that dimension. Both \\`paddings\\[D, 0\\]\\` and \\`paddings\\[D, 1\\]\\` must be no greater\nthan \\`input.dim_size(D)\\` (or \\`input.dim_size(D) - 1\\`) if \\`copy_border\\` is true\n(if false, respectively).\n\n\nThe padded size of each dimension D of the output is:\n\n\n\\`paddings(D, 0) + input.dim_size(D) + paddings(D, 1)\\`\n\n\nFor example: \n\n # 't' is [[1, 2, 3], [4, 5, 6]].\n # 'paddings' is [[1, 1]], [2, 2]].\n # 'mode' is SYMMETRIC.\n # rank of 't' is 2.\n pad(t, paddings) ==> [[2, 1, 1, 2, 3, 3, 2]\n [2, 1, 1, 2, 3, 3, 2]\n [5, 4, 4, 5, 6, 6, 5]\n [5, 4, 4, 5, 6, 6, 5]]\n \n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n### Public Methods\n\n|--------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [Output](/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [asOutput](/api_docs/java/org/tensorflow/op/core/MirrorPad#asOutput())() Returns the symbolic handle of a tensor. |\n| static \\\u003cT, U extends Number\\\u003e [MirrorPad](/api_docs/java/org/tensorflow/op/core/MirrorPad)\\\u003cT\\\u003e | [create](/api_docs/java/org/tensorflow/op/core/MirrorPad#create(org.tensorflow.op.Scope,%20org.tensorflow.Operand\u003cT\u003e,%20org.tensorflow.Operand\u003cU\u003e,%20java.lang.String))([Scope](/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e input, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003cU\\\u003e paddings, String mode) Factory method to create a class wrapping a new MirrorPad operation. |\n| [Output](/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e | [output](/api_docs/java/org/tensorflow/op/core/MirrorPad#output())() The padded tensor. |\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)\\\u003cT\\\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)\\\u003cT\\\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 [MirrorPad](/api_docs/java/org/tensorflow/op/core/MirrorPad)\\\u003cT\\\u003e\n**create**\n([Scope](/api_docs/java/org/tensorflow/op/Scope) scope, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e input, [Operand](/api_docs/java/org/tensorflow/Operand)\\\u003cU\\\u003e paddings, String mode)\n\nFactory method to create a class wrapping a new MirrorPad operation. \n\n##### Parameters\n\n| scope | current scope |\n| input | The input tensor to be padded. |\n| paddings | A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank of \\`input\\`. |\n| mode | Either \\`REFLECT\\` or \\`SYMMETRIC\\`. In reflect mode the padded regions do not include the borders, while in symmetric mode the padded regions do include the borders. For example, if \\`input\\` is \\`\\[1, 2, 3\\]\\` and \\`paddings\\` is \\`\\[0, 2\\]\\`, then the output is \\`\\[1, 2, 3, 2, 1\\]\\` in reflect mode, and it is \\`\\[1, 2, 3, 3, 2\\]\\` in symmetric mode. |\n|----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n\n##### Returns\n\n- a new instance of MirrorPad \n\n#### public [Output](/api_docs/java/org/tensorflow/Output)\\\u003cT\\\u003e\n**output**\n()\n\nThe padded tensor."]]
