public static final class
TensorShapeProto.Builder
Dimensions of a tensor.Protobuf type
tensorflow.TensorShapeProto
Public Methods
| 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(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.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 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(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
|
| TensorShapeProto |
build()
|
| TensorShapeProto | |
| 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(com.google.protobuf.Descriptors.FieldDescriptor field)
|
| TensorShapeProto.Builder |
clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
|
| TensorShapeProto.Builder |
clearUnknownRank()
If true, the number of dimensions in the shape is unknown. |
| TensorShapeProto.Builder |
clone()
|
| TensorShapeProto | |
| final static com.google.protobuf.Descriptors.Descriptor | |
| com.google.protobuf.Descriptors.Descriptor | |
| 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. |
| final boolean | |
| TensorShapeProto.Builder |
mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
|
| TensorShapeProto.Builder |
mergeFrom(com.google.protobuf.Message other)
|
| final TensorShapeProto.Builder |
mergeUnknownFields(com.google.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 value)
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 |
setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
|
| TensorShapeProto.Builder |
setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
|
| final TensorShapeProto.Builder |
setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
|
| TensorShapeProto.Builder |
setUnknownRank(boolean value)
If true, the number of dimensions in the shape is unknown. |
Inherited Methods
Public Methods
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 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 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 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.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 TensorShapeProto.Builder addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
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 "