TensorShapeProtoOrBuilder
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Known Indirect Subclasses
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Public Methods
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abstract
TensorShapeProto.Dim
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getDim(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
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abstract
int
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getDimCount()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
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abstract
List<TensorShapeProto.Dim>
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getDimList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
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abstract
TensorShapeProto.DimOrBuilder
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getDimOrBuilder(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
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abstract
List<? extends TensorShapeProto.DimOrBuilder>
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getDimOrBuilderList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
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abstract
boolean
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getUnknownRank()
If true, the number of dimensions in the shape is unknown.
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Public Methods
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. If an entry has size -1, this
corresponds to a dimension of unknown size. The names are
optional.
The order of entries in "dim" matters: It indicates the layout of the
values in the tensor in-memory representation.
The first entry in "dim" is the outermost dimension used to layout the
values, the last entry is the innermost dimension. This matches the
in-memory layout of RowMajor Eigen tensors.
If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public
abstract
int
getDimCount
()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. If an entry has size -1, this
corresponds to a dimension of unknown size. The names are
optional.
The order of entries in "dim" matters: It indicates the layout of the
values in the tensor in-memory representation.
The first entry in "dim" is the outermost dimension used to layout the
values, the last entry is the innermost dimension. This matches the
in-memory layout of RowMajor Eigen tensors.
If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. If an entry has size -1, this
corresponds to a dimension of unknown size. The names are
optional.
The order of entries in "dim" matters: It indicates the layout of the
values in the tensor in-memory representation.
The first entry in "dim" is the outermost dimension used to layout the
values, the last entry is the innermost dimension. This matches the
in-memory layout of RowMajor Eigen tensors.
If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. If an entry has size -1, this
corresponds to a dimension of unknown size. The names are
optional.
The order of entries in "dim" matters: It indicates the layout of the
values in the tensor in-memory representation.
The first entry in "dim" is the outermost dimension used to layout the
values, the last entry is the innermost dimension. This matches the
in-memory layout of RowMajor Eigen tensors.
If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor. If an entry has size -1, this
corresponds to a dimension of unknown size. The names are
optional.
The order of entries in "dim" matters: It indicates the layout of the
values in the tensor in-memory representation.
The first entry in "dim" is the outermost dimension used to layout the
values, the last entry is the innermost dimension. This matches the
in-memory layout of RowMajor Eigen tensors.
If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public
abstract
boolean
getUnknownRank
()
If true, the number of dimensions in the shape is unknown.
If true, "dim.size()" must be 0.
bool unknown_rank = 3;
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Last updated 2021-11-29 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 2021-11-29 UTC."],[],[],null,["# TensorShapeProtoOrBuilder\n\npublic interface **TensorShapeProtoOrBuilder** \n\n|---|---|---|\n| Known Indirect Subclasses [TensorShapeProto](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto), [TensorShapeProto.Builder](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.Builder) |--------------------------------------------------------------------------------------------------------|----------------------------------| | [TensorShapeProto](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto) | ``` Dimensions of a tensor. ``` | | [TensorShapeProto.Builder](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.Builder) | ``` Dimensions of a tensor. ``` | |||\n\n### Public Methods\n\n|---------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| abstract [TensorShapeProto.Dim](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.Dim) | [getDim](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProtoOrBuilder#getDim(int))(int index) ``` Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40} for a 30 x 40 2D tensor. ``` |\n| abstract int | [getDimCount](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProtoOrBuilder#getDimCount())() ``` Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40} for a 30 x 40 2D tensor. ``` |\n| abstract List\\\u003c[TensorShapeProto.Dim](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.Dim)\\\u003e | [getDimList](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProtoOrBuilder#getDimList())() ``` Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40} for a 30 x 40 2D tensor. ``` |\n| abstract [TensorShapeProto.DimOrBuilder](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.DimOrBuilder) | [getDimOrBuilder](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProtoOrBuilder#getDimOrBuilder(int))(int index) ``` Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40} for a 30 x 40 2D tensor. ``` |\n| abstract List\\\u003c? extends [TensorShapeProto.DimOrBuilder](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.DimOrBuilder)\\\u003e | [getDimOrBuilderList](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProtoOrBuilder#getDimOrBuilderList())() ``` Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40} for a 30 x 40 2D tensor. ``` |\n| abstract boolean | [getUnknownRank](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProtoOrBuilder#getUnknownRank())() ``` If true, the number of dimensions in the shape is unknown. ``` |\n\nPublic Methods\n--------------\n\n#### public abstract [TensorShapeProto.Dim](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.Dim)\n**getDim**\n(int index)\n\n\u003cbr /\u003e\n\n```\n Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40}\n for a 30 x 40 2D tensor. If an entry has size -1, this\n corresponds to a dimension of unknown size. The names are\n optional.\n The order of entries in \"dim\" matters: It indicates the layout of the\n values in the tensor in-memory representation.\n The first entry in \"dim\" is the outermost dimension used to layout the\n values, the last entry is the innermost dimension. This matches the\n in-memory layout of RowMajor Eigen tensors.\n If \"dim.size()\" \u003e 0, \"unknown_rank\" must be false.\n \n```\n`repeated .tensorflow.TensorShapeProto.Dim dim = 2;`\n\n\u003cbr /\u003e\n\n#### public abstract int\n**getDimCount**\n()\n\n\u003cbr /\u003e\n\n```\n Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40}\n for a 30 x 40 2D tensor. If an entry has size -1, this\n corresponds to a dimension of unknown size. The names are\n optional.\n The order of entries in \"dim\" matters: It indicates the layout of the\n values in the tensor in-memory representation.\n The first entry in \"dim\" is the outermost dimension used to layout the\n values, the last entry is the innermost dimension. This matches the\n in-memory layout of RowMajor Eigen tensors.\n If \"dim.size()\" \u003e 0, \"unknown_rank\" must be false.\n \n```\n`repeated .tensorflow.TensorShapeProto.Dim dim = 2;`\n\n\u003cbr /\u003e\n\n#### public abstract List\\\u003c[TensorShapeProto.Dim](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.Dim)\\\u003e\n**getDimList**\n()\n\n\u003cbr /\u003e\n\n```\n Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40}\n for a 30 x 40 2D tensor. If an entry has size -1, this\n corresponds to a dimension of unknown size. The names are\n optional.\n The order of entries in \"dim\" matters: It indicates the layout of the\n values in the tensor in-memory representation.\n The first entry in \"dim\" is the outermost dimension used to layout the\n values, the last entry is the innermost dimension. This matches the\n in-memory layout of RowMajor Eigen tensors.\n If \"dim.size()\" \u003e 0, \"unknown_rank\" must be false.\n \n```\n`repeated .tensorflow.TensorShapeProto.Dim dim = 2;`\n\n\u003cbr /\u003e\n\n#### public abstract [TensorShapeProto.DimOrBuilder](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.DimOrBuilder)\n**getDimOrBuilder**\n(int index)\n\n\u003cbr /\u003e\n\n```\n Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40}\n for a 30 x 40 2D tensor. If an entry has size -1, this\n corresponds to a dimension of unknown size. The names are\n optional.\n The order of entries in \"dim\" matters: It indicates the layout of the\n values in the tensor in-memory representation.\n The first entry in \"dim\" is the outermost dimension used to layout the\n values, the last entry is the innermost dimension. This matches the\n in-memory layout of RowMajor Eigen tensors.\n If \"dim.size()\" \u003e 0, \"unknown_rank\" must be false.\n \n```\n`repeated .tensorflow.TensorShapeProto.Dim dim = 2;`\n\n\u003cbr /\u003e\n\n#### public abstract List\\\u003c? extends [TensorShapeProto.DimOrBuilder](/jvm/api_docs/java/org/tensorflow/proto/framework/TensorShapeProto.DimOrBuilder)\\\u003e\n**getDimOrBuilderList**\n()\n\n\u003cbr /\u003e\n\n```\n Dimensions of the tensor, such as {\"input\", 30}, {\"output\", 40}\n for a 30 x 40 2D tensor. If an entry has size -1, this\n corresponds to a dimension of unknown size. The names are\n optional.\n The order of entries in \"dim\" matters: It indicates the layout of the\n values in the tensor in-memory representation.\n The first entry in \"dim\" is the outermost dimension used to layout the\n values, the last entry is the innermost dimension. This matches the\n in-memory layout of RowMajor Eigen tensors.\n If \"dim.size()\" \u003e 0, \"unknown_rank\" must be false.\n \n```\n`repeated .tensorflow.TensorShapeProto.Dim dim = 2;`\n\n\u003cbr /\u003e\n\n#### public abstract boolean\n**getUnknownRank**\n()\n\n\u003cbr /\u003e\n\n```\n If true, the number of dimensions in the shape is unknown.\n If true, \"dim.size()\" must be 0.\n \n```\n`bool unknown_rank = 3;`\n\n\u003cbr /\u003e"]]
