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TensorShapeProto

public final class TensorShapeProto

 Dimensions of a tensor.
 
Protobuf type tensorflow.TensorShapeProto

Nested Classes

class TensorShapeProto.Builder
 Dimensions of a tensor. 
class TensorShapeProto.Dim
 One dimension of the tensor. 
interface TensorShapeProto.DimOrBuilder

Constants

int DIM_FIELD_NUMBER
int UNKNOWN_RANK_FIELD_NUMBER

Public Methods

boolean
equals (Object obj)
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.
int
final com.google.protobuf.UnknownFieldSet
boolean
getUnknownRank ()
 If true, the number of dimensions in the shape is unknown.
int
final boolean
static TensorShapeProto.Builder
static TensorShapeProto.Builder
TensorShapeProto.Builder
static TensorShapeProto
parseDelimitedFrom (InputStream input)
static TensorShapeProto
parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorShapeProto
parseFrom (ByteBuffer data)
static TensorShapeProto
parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorShapeProto
parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorShapeProto
parseFrom (com.google.protobuf.CodedInputStream input)
static TensorShapeProto
parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorShapeProto
parseFrom (com.google.protobuf.ByteString data)
static TensorShapeProto
parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static TensorShapeProto
parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
static
TensorShapeProto.Builder
void
writeTo (com.google.protobuf.CodedOutputStream output)

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 TensorShapeProto getDefaultInstance ()

public TensorShapeProto getDefaultInstanceForType ()

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.Builder newBuilder ( TensorShapeProto prototype)

public static TensorShapeProto.Builder newBuilder ()

public TensorShapeProto.Builder newBuilderForType ()

public static TensorShapeProto parseDelimitedFrom (InputStream input)

Throws
IOException

public static TensorShapeProto parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
IOException

public static TensorShapeProto parseFrom (ByteBuffer data)

Throws
InvalidProtocolBufferException

public static TensorShapeProto parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
IOException

public static TensorShapeProto parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Throws
InvalidProtocolBufferException

public static TensorShapeProto parseFrom (com.google.protobuf.CodedInputStream input)

Throws
IOException
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