パブリック インターフェイスTensorInfoOrBuilder
既知の間接サブクラス |
パブリックメソッド
抽象TensorInfo.CompositeTensor | getCompositeTensor () Generic encoding for CompositeTensors. |
抽象TensorInfo.CompositeTensorOrBuilder | getCompositeTensorOrBuilder () Generic encoding for CompositeTensors. |
抽象TensorInfo.CooSparse | getCooSparse () There are many possible encodings of sparse matrices (https://en.wikipedia.org/wiki/Sparse_matrix). |
抽象TensorInfo.CooSparseOrBuilder | getCooSparseOrBuilder () There are many possible encodings of sparse matrices (https://en.wikipedia.org/wiki/Sparse_matrix). |
抽象データ型 | getDtype () .tensorflow.DataType dtype = 2; |
抽象整数 | getDtypeValue () .tensorflow.DataType dtype = 2; |
抽象TensorInfo.EncodingCase | |
抽象文字列 | getName () For dense `Tensor`s, the name of the tensor in the graph. |
抽象的な com.google.protobuf.ByteString | getNameBytes () For dense `Tensor`s, the name of the tensor in the graph. |
抽象TensorShapeProto | getTensorShape () The static shape should be recorded here, to the extent that it can be known in advance. |
抽象TensorShapeProtoOrBuilder | getTensorShapeOrBuilder () The static shape should be recorded here, to the extent that it can be known in advance. |
抽象ブール値 | hasCompositeTensor () Generic encoding for CompositeTensors. |
抽象ブール値 | hasCooSparse () There are many possible encodings of sparse matrices (https://en.wikipedia.org/wiki/Sparse_matrix). |
抽象ブール値 | hasTensorShape () The static shape should be recorded here, to the extent that it can be known in advance. |
パブリックメソッド
パブリック抽象TensorInfo.CompositeTensor getCompositeTensor ()
Generic encoding for CompositeTensors.
.tensorflow.TensorInfo.CompositeTensor composite_tensor = 5;
パブリック抽象TensorInfo.CompositeTensorOrBuilder getCompositeTensorOrBuilder ()
Generic encoding for CompositeTensors.
.tensorflow.TensorInfo.CompositeTensor composite_tensor = 5;
パブリック抽象TensorInfo.CooSparse getCooSparse ()
There are many possible encodings of sparse matrices (https://en.wikipedia.org/wiki/Sparse_matrix). Currently, TensorFlow uses only the COO encoding. This is supported and documented in the SparseTensor Python class.
.tensorflow.TensorInfo.CooSparse coo_sparse = 4;
パブリック抽象TensorInfo.CooSparseOrBuilder getCooSparseOrBuilder ()
There are many possible encodings of sparse matrices (https://en.wikipedia.org/wiki/Sparse_matrix). Currently, TensorFlow uses only the COO encoding. This is supported and documented in the SparseTensor Python class.
.tensorflow.TensorInfo.CooSparse coo_sparse = 4;
パブリック抽象 int getDtypeValue ()
.tensorflow.DataType dtype = 2;
パブリック抽象 String getName ()
For dense `Tensor`s, the name of the tensor in the graph.
string name = 1;
パブリック抽象 com.google.protobuf.ByteString getNameBytes ()
For dense `Tensor`s, the name of the tensor in the graph.
string name = 1;
パブリック抽象TensorShapeProto getTensorShape ()
The static shape should be recorded here, to the extent that it can be known in advance. In the case of a SparseTensor, this field describes the logical shape of the represented tensor (aka dense_shape).
.tensorflow.TensorShapeProto tensor_shape = 3;
パブリック抽象TensorShapeProtoOrBuilder getTensorShapeOrBuilder ()
The static shape should be recorded here, to the extent that it can be known in advance. In the case of a SparseTensor, this field describes the logical shape of the represented tensor (aka dense_shape).
.tensorflow.TensorShapeProto tensor_shape = 3;
public abstract boolean hasCompositeTensor ()
Generic encoding for CompositeTensors.
.tensorflow.TensorInfo.CompositeTensor composite_tensor = 5;
パブリック抽象ブール値hasCooSparse ()
There are many possible encodings of sparse matrices (https://en.wikipedia.org/wiki/Sparse_matrix). Currently, TensorFlow uses only the COO encoding. This is supported and documented in the SparseTensor Python class.
.tensorflow.TensorInfo.CooSparse coo_sparse = 4;
public abstract boolean hasTensorShape ()
The static shape should be recorded here, to the extent that it can be known in advance. In the case of a SparseTensor, this field describes the logical shape of the represented tensor (aka dense_shape).
.tensorflow.TensorShapeProto tensor_shape = 3;