Class TensorShapeProto.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<TensorShapeProto.Builder>
com.google.protobuf.GeneratedMessage.Builder<TensorShapeProto.Builder>
org.tensorflow.proto.TensorShapeProto.Builder
All Implemented Interfaces:
Message.Builder, MessageLite.Builder, MessageLiteOrBuilder, MessageOrBuilder, Cloneable, TensorShapeProtoOrBuilder
Enclosing class:
TensorShapeProto
public static final class TensorShapeProto.Builder extends GeneratedMessage.Builder<TensorShapeProto.Builder> implements TensorShapeProtoOrBuilder
Dimensions of a tensor.
Protobuf type tensorflow.TensorShapeProto

  • Method Details

    • getDescriptor

      public static final Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class GeneratedMessage.Builder<TensorShapeProto.Builder>

    • clear

      public TensorShapeProto.Builder clear()
      Specified by:
      clear in interface Message.Builder
      Specified by:
      clear in interface MessageLite.Builder
      Overrides:
      clear in class GeneratedMessage.Builder<TensorShapeProto.Builder>

    • getDescriptorForType

      public Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface Message.Builder
      Specified by:
      getDescriptorForType in interface MessageOrBuilder
      Overrides:
      getDescriptorForType in class GeneratedMessage.Builder<TensorShapeProto.Builder>

    • getDefaultInstanceForType

      public TensorShapeProto getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface MessageOrBuilder

    • build

      public TensorShapeProto build()
      Specified by:
      build in interface Message.Builder
      Specified by:
      build in interface MessageLite.Builder

    • buildPartial

      public TensorShapeProto buildPartial()
      Specified by:
      buildPartial in interface Message.Builder
      Specified by:
      buildPartial in interface MessageLite.Builder

    • mergeFrom

      public TensorShapeProto.Builder mergeFrom(Message other)
      Specified by:
      mergeFrom in interface Message.Builder
      Overrides:
      mergeFrom in class AbstractMessage.Builder<TensorShapeProto.Builder>

    • mergeFrom

      public TensorShapeProto.Builder mergeFrom(TensorShapeProto other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface MessageLiteOrBuilder
      Overrides:
      isInitialized in class GeneratedMessage.Builder<TensorShapeProto.Builder>

    • mergeFrom

      public TensorShapeProto.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface Message.Builder
      Specified by:
      mergeFrom in interface MessageLite.Builder
      Overrides:
      mergeFrom in class AbstractMessage.Builder<TensorShapeProto.Builder>
      Throws:
      IOException

    • getDimList

      public 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;
      Specified by:
      getDimList in interface TensorShapeProtoOrBuilder

    • getDimCount

      public 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;
      Specified by:
      getDimCount in interface TensorShapeProtoOrBuilder

    • getDim

      public 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;
      Specified by:
      getDim in interface TensorShapeProtoOrBuilder

    • setDim

      public 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;

    • setDim

      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;

    • addDim

      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;

    • addDim

      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;

    • addDim

      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;

    • addDim

      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;

    • addAllDim

      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;

    • clearDim

      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;

    • removeDim

      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;

    • getDimBuilder

      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;

    • getDimOrBuilder

      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;
      Specified by:
      getDimOrBuilder in interface TensorShapeProtoOrBuilder

    • getDimOrBuilderList

      public 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;
      Specified by:
      getDimOrBuilderList in interface TensorShapeProtoOrBuilder

    • addDimBuilder

      public 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;

    • addDimBuilder

      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;

    • getDimBuilderList

      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;

    • getUnknownRank

      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;
      Specified by:
      getUnknownRank in interface TensorShapeProtoOrBuilder
      Returns:
      The unknownRank.

    • setUnknownRank

      public 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;
      Parameters:
      value - The unknownRank to set.
      Returns:
      This builder for chaining.

    • clearUnknownRank

      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;
      Returns:
      This builder for chaining.