public final class
TensorShapeProto
Dimensions of a tensor.
tensorflow.TensorShapeProto
Nested Classes
class | TensorShapeProto.Builder | Dimensions of a tensor. |
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class | TensorShapeProto.Dim | One dimension of the tensor. |
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interface | TensorShapeProto.DimOrBuilder |
Constants
int | DIM_FIELD_NUMBER | |
int | UNKNOWN_RANK_FIELD_NUMBER |
Public Methods
boolean |
equals(Object obj)
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static TensorShapeProto | |
TensorShapeProto | |
final static 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. |
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. |
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|
int | |
final com.google.protobuf.UnknownFieldSet | |
boolean |
getUnknownRank()
If true, the number of dimensions in the shape is unknown. |
int |
hashCode()
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final boolean | |
static TensorShapeProto.Builder |
newBuilder(TensorShapeProto prototype)
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static TensorShapeProto.Builder | |
TensorShapeProto.Builder | |
static TensorShapeProto |
parseDelimitedFrom(InputStream input)
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static TensorShapeProto |
parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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static TensorShapeProto |
parseFrom(ByteBuffer data)
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static TensorShapeProto |
parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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static TensorShapeProto |
parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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static TensorShapeProto |
parseFrom(com.google.protobuf.CodedInputStream input)
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static TensorShapeProto |
parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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static TensorShapeProto |
parseFrom(com.google.protobuf.ByteString data)
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static TensorShapeProto |
parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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static TensorShapeProto |
parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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static
|
parser()
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TensorShapeProto.Builder | |
void |
writeTo(com.google.protobuf.CodedOutputStream output)
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Inherited Methods
Constants
public static final int DIM_FIELD_NUMBER
Constant Value:
2
public static final int UNKNOWN_RANK_FIELD_NUMBER
Constant Value:
3
Public Methods
public boolean equals (Object obj)
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()
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;
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;
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;
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;
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;
public
getParserForType
()
public int getSerializedSize ()
public final com.google.protobuf.UnknownFieldSet getUnknownFields ()
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;
public int hashCode ()
public final boolean isInitialized ()
public static TensorShapeProto parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
IOException |
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public static TensorShapeProto parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
IOException |
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public static TensorShapeProto parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
InvalidProtocolBufferException |
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public static TensorShapeProto parseFrom (com.google.protobuf.CodedInputStream input)
Throws
IOException |
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public static TensorShapeProto parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
InvalidProtocolBufferException |
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public static TensorShapeProto parseFrom (com.google.protobuf.ByteString data)
Throws
InvalidProtocolBufferException |
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public static TensorShapeProto parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
IOException |
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public static TensorShapeProto parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
InvalidProtocolBufferException |
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public
static
parser
()
public void writeTo (com.google.protobuf.CodedOutputStream output)
Throws
IOException |
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