Package org.tensorflow.framework

Class TensorShapeProto.Builder

  • All Implemented Interfaces:
    Cloneable, org.nd4j.shade.protobuf.Message.Builder, org.nd4j.shade.protobuf.MessageLite.Builder, org.nd4j.shade.protobuf.MessageLiteOrBuilder, org.nd4j.shade.protobuf.MessageOrBuilder, TensorShapeProtoOrBuilder
    Enclosing class:
    TensorShapeProto
    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

    • Method Detail

      • getDescriptor

        public static final org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • clear

        public TensorShapeProto.Builder clear()
        Specified by:
        clear in interface org.nd4j.shade.protobuf.Message.Builder
        Specified by:
        clear in interface org.nd4j.shade.protobuf.MessageLite.Builder
        Overrides:
        clear in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • getDescriptorForType

        public org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface org.nd4j.shade.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface org.nd4j.shade.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • getDefaultInstanceForType

        public TensorShapeProto getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface org.nd4j.shade.protobuf.MessageOrBuilder

      • build

        public TensorShapeProto build()
        Specified by:
        build in interface org.nd4j.shade.protobuf.Message.Builder
        Specified by:
        build in interface org.nd4j.shade.protobuf.MessageLite.Builder

      • buildPartial

        public TensorShapeProto buildPartial()
        Specified by:
        buildPartial in interface org.nd4j.shade.protobuf.Message.Builder
        Specified by:
        buildPartial in interface org.nd4j.shade.protobuf.MessageLite.Builder

      • clone

        public TensorShapeProto.Builder clone()
        Specified by:
        clone in interface org.nd4j.shade.protobuf.Message.Builder
        Specified by:
        clone in interface org.nd4j.shade.protobuf.MessageLite.Builder
        Overrides:
        clone in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • setField

        public TensorShapeProto.Builder setField​(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
                                         Object value)
        Specified by:
        setField in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        setField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • clearField

        public TensorShapeProto.Builder clearField​(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        clearField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • clearOneof

        public TensorShapeProto.Builder clearOneof​(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        clearOneof in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • setRepeatedField

        public TensorShapeProto.Builder setRepeatedField​(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
                                                 int index,
                                                 Object value)
        Specified by:
        setRepeatedField in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • addRepeatedField

        public TensorShapeProto.Builder addRepeatedField​(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
                                                 Object value)
        Specified by:
        addRepeatedField in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • mergeFrom

        public TensorShapeProto.Builder mergeFrom​(org.nd4j.shade.protobuf.Message other)
        Specified by:
        mergeFrom in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        mergeFrom in class org.nd4j.shade.protobuf.AbstractMessage.Builder<TensorShapeProto.Builder>

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface org.nd4j.shade.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • mergeFrom

        public TensorShapeProto.Builder mergeFrom​(org.nd4j.shade.protobuf.CodedInputStream input,
                                          org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
                                   throws IOException
        Specified by:
        mergeFrom in interface org.nd4j.shade.protobuf.Message.Builder
        Specified by:
        mergeFrom in interface org.nd4j.shade.protobuf.MessageLite.Builder
        Overrides:
        mergeFrom in class org.nd4j.shade.protobuf.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.

      • setUnknownFields

        public final TensorShapeProto.Builder setUnknownFields​(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>

      • mergeUnknownFields

        public final TensorShapeProto.Builder mergeUnknownFields​(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface org.nd4j.shade.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<TensorShapeProto.Builder>