public static final class TensorShapeProto.Builder extends org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder> implements TensorShapeProtoOrBuilder
Dimensions of a tensor.Protobuf type
tensorflow.TensorShapeProto| Modifier and Type | Method and Description |
|---|---|
TensorShapeProto.Builder |
addAllDim(Iterable<? extends TensorShapeProto.Dim> values)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
addDim(int index,
TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
addDim(int index,
TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
addDim(TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
addDim(TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Dim.Builder |
addDimBuilder()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Dim.Builder |
addDimBuilder(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
Object value) |
TensorShapeProto |
build() |
TensorShapeProto |
buildPartial() |
TensorShapeProto.Builder |
clear() |
TensorShapeProto.Builder |
clearDim()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field) |
TensorShapeProto.Builder |
clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof) |
TensorShapeProto.Builder |
clearUnknownRank()
If true, the number of dimensions in the shape is unknown.
|
TensorShapeProto.Builder |
clone() |
TensorShapeProto |
getDefaultInstanceForType() |
static org.nd4j.shade.protobuf.Descriptors.Descriptor |
getDescriptor() |
org.nd4j.shade.protobuf.Descriptors.Descriptor |
getDescriptorForType() |
TensorShapeProto.Dim |
getDim(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Dim.Builder |
getDimBuilder(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
List<TensorShapeProto.Dim.Builder> |
getDimBuilderList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
int |
getDimCount()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
List<TensorShapeProto.Dim> |
getDimList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.DimOrBuilder |
getDimOrBuilder(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
List<? extends TensorShapeProto.DimOrBuilder> |
getDimOrBuilderList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
boolean |
getUnknownRank()
If true, the number of dimensions in the shape is unknown.
|
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable |
internalGetFieldAccessorTable() |
boolean |
isInitialized() |
TensorShapeProto.Builder |
mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
TensorShapeProto.Builder |
mergeFrom(org.nd4j.shade.protobuf.Message other) |
TensorShapeProto.Builder |
mergeFrom(TensorShapeProto other) |
TensorShapeProto.Builder |
mergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) |
TensorShapeProto.Builder |
removeDim(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
setDim(int index,
TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
setDim(int index,
TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40}
for a 30 x 40 2D tensor.
|
TensorShapeProto.Builder |
setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
Object value) |
TensorShapeProto.Builder |
setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
int index,
Object value) |
TensorShapeProto.Builder |
setUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) |
TensorShapeProto.Builder |
setUnknownRank(boolean value)
If true, the number of dimensions in the shape is unknown.
|
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, newBuilderForField, onBuilt, onChanged, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptor()
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder clear()
clear in interface org.nd4j.shade.protobuf.Message.Builderclear in interface org.nd4j.shade.protobuf.MessageLite.Builderclear in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface org.nd4j.shade.protobuf.Message.BuildergetDescriptorForType in interface org.nd4j.shade.protobuf.MessageOrBuildergetDescriptorForType in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto getDefaultInstanceForType()
getDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageOrBuilderpublic TensorShapeProto build()
build in interface org.nd4j.shade.protobuf.Message.Builderbuild in interface org.nd4j.shade.protobuf.MessageLite.Builderpublic TensorShapeProto buildPartial()
buildPartial in interface org.nd4j.shade.protobuf.Message.BuilderbuildPartial in interface org.nd4j.shade.protobuf.MessageLite.Builderpublic TensorShapeProto.Builder clone()
clone in interface org.nd4j.shade.protobuf.Message.Builderclone in interface org.nd4j.shade.protobuf.MessageLite.Builderclone in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
setField in interface org.nd4j.shade.protobuf.Message.BuildersetField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)
clearField in interface org.nd4j.shade.protobuf.Message.BuilderclearField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)
clearOneof in interface org.nd4j.shade.protobuf.Message.BuilderclearOneof in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
setRepeatedField in interface org.nd4j.shade.protobuf.Message.BuildersetRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
addRepeatedField in interface org.nd4j.shade.protobuf.Message.BuilderaddRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder mergeFrom(org.nd4j.shade.protobuf.Message other)
mergeFrom in interface org.nd4j.shade.protobuf.Message.BuildermergeFrom in class org.nd4j.shade.protobuf.AbstractMessage.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder mergeFrom(TensorShapeProto other)
public final boolean isInitialized()
isInitialized in interface org.nd4j.shade.protobuf.MessageLiteOrBuilderisInitialized in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public TensorShapeProto.Builder mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
mergeFrom in interface org.nd4j.shade.protobuf.Message.BuildermergeFrom in interface org.nd4j.shade.protobuf.MessageLite.BuildermergeFrom in class org.nd4j.shade.protobuf.AbstractMessage.Builder<TensorShapeProto.Builder>IOExceptionpublic List<TensorShapeProto.Dim> getDimList()
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;getDimList in interface TensorShapeProtoOrBuilderpublic 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;getDimCount in interface TensorShapeProtoOrBuilderpublic TensorShapeProto.Dim getDim(int index)
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;getDim in interface TensorShapeProtoOrBuilderpublic TensorShapeProto.Builder setDim(int index, TensorShapeProto.Dim value)
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 TensorShapeProto.Builder setDim(int index, TensorShapeProto.Dim.Builder builderForValue)
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 TensorShapeProto.Builder addDim(TensorShapeProto.Dim value)
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 TensorShapeProto.Builder addDim(int index, TensorShapeProto.Dim value)
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 TensorShapeProto.Builder addDim(TensorShapeProto.Dim.Builder builderForValue)
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 TensorShapeProto.Builder addDim(int index, TensorShapeProto.Dim.Builder builderForValue)
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 TensorShapeProto.Builder addAllDim(Iterable<? extends TensorShapeProto.Dim> values)
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 TensorShapeProto.Builder clearDim()
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 TensorShapeProto.Builder removeDim(int index)
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 TensorShapeProto.Dim.Builder getDimBuilder(int index)
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 TensorShapeProto.DimOrBuilder getDimOrBuilder(int index)
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;getDimOrBuilder in interface TensorShapeProtoOrBuilderpublic List<? extends TensorShapeProto.DimOrBuilder> getDimOrBuilderList()
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;getDimOrBuilderList in interface TensorShapeProtoOrBuilderpublic TensorShapeProto.Dim.Builder addDimBuilder()
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 TensorShapeProto.Dim.Builder addDimBuilder(int index)
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 List<TensorShapeProto.Dim.Builder> getDimBuilderList()
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 boolean getUnknownRank()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;getUnknownRank in interface TensorShapeProtoOrBuilderpublic TensorShapeProto.Builder setUnknownRank(boolean value)
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;public TensorShapeProto.Builder clearUnknownRank()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;public final TensorShapeProto.Builder setUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
setUnknownFields in interface org.nd4j.shade.protobuf.Message.BuildersetUnknownFields in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>public final TensorShapeProto.Builder mergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
mergeUnknownFields in interface org.nd4j.shade.protobuf.Message.BuildermergeUnknownFields in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>Copyright © 2020. All rights reserved.