Package org.tensorflow.framework
Interface TensorShapeProtoOrBuilder
- All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder
- All Known Implementing Classes:
TensorShapeProto,TensorShapeProto.Builder
public interface TensorShapeProtoOrBuilder
extends com.google.protobuf.MessageOrBuilder
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Method Summary
Modifier and Type Method Description TensorShapeProto.DimgetDim(int index)Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.intgetDimCount()Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.java.util.List<TensorShapeProto.Dim>getDimList()Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.TensorShapeProto.DimOrBuildergetDimOrBuilder(int index)Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.java.util.List<? extends TensorShapeProto.DimOrBuilder>getDimOrBuilderList()Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.booleangetUnknownRank()If true, the number of dimensions in the shape is unknown.Methods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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getDimList
java.util.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; -
getDim
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; -
getDimCount
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; -
getDimOrBuilderList
java.util.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; -
getDimOrBuilder
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
boolean getUnknownRank()If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;- Returns:
- The unknownRank.
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