| // Licensed to the Apache Software Foundation (ASF) under one |
| // or more contributor license agreements. See the NOTICE file |
| // distributed with this work for additional information |
| // regarding copyright ownership. The ASF licenses this file |
| // to you under the Apache License, Version 2.0 (the |
| // "License"); you may not use this file except in compliance |
| // with the License. You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, |
| // software distributed under the License is distributed on an |
| // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| // KIND, either express or implied. See the License for the |
| // specific language governing permissions and limitations |
| // under the License. |
| |
| /// EXPERIMENTAL: Metadata for n-dimensional sparse arrays, aka "sparse tensors". |
| /// Arrow implementations in general are not required to implement this type |
| |
| include "Tensor.fbs"; |
| |
| namespace org.apache.arrow.flatbuf; |
| |
| /// ---------------------------------------------------------------------- |
| /// EXPERIMENTAL: Data structures for sparse tensors |
| |
| /// Coodinate (COO) format of sparse tensor index. |
| /// |
| /// COO's index list are represented as a NxM matrix, |
| /// where N is the number of non-zero values, |
| /// and M is the number of dimensions of a sparse tensor. |
| /// |
| /// indicesBuffer stores the location and size of the data of this indices |
| /// matrix. The value type and the stride of the indices matrix is |
| /// specified in indicesType and indicesStrides fields. |
| /// |
| /// For example, let X be a 2x3x4x5 tensor, and it has the following |
| /// 6 non-zero values: |
| /// |
| /// X[0, 1, 2, 0] := 1 |
| /// X[1, 1, 2, 3] := 2 |
| /// X[0, 2, 1, 0] := 3 |
| /// X[0, 1, 3, 0] := 4 |
| /// X[0, 1, 2, 1] := 5 |
| /// X[1, 2, 0, 4] := 6 |
| /// |
| /// In COO format, the index matrix of X is the following 4x6 matrix: |
| /// |
| /// [[0, 0, 0, 0, 1, 1], |
| /// [1, 1, 1, 2, 1, 2], |
| /// [2, 2, 3, 1, 2, 0], |
| /// [0, 1, 0, 0, 3, 4]] |
| /// |
| /// Note that the indices are sorted in lexicographical order. |
| table SparseTensorIndexCOO { |
| /// The type of values in indicesBuffer |
| indicesType: Int; |
| |
| /// Non-negative byte offsets to advance one value cell along each dimension |
| indicesStrides: [long]; |
| |
| /// The location and size of the indices matrix's data |
| indicesBuffer: Buffer; |
| } |
| |
| /// Compressed Sparse Row format, that is matrix-specific. |
| table SparseMatrixIndexCSR { |
| /// The type of values in indptrBuffer |
| indptrType: Int; |
| |
| /// indptrBuffer stores the location and size of indptr array that |
| /// represents the range of the rows. |
| /// The i-th row spans from indptr[i] to indptr[i+1] in the data. |
| /// The length of this array is 1 + (the number of rows), and the type |
| /// of index value is long. |
| /// |
| /// For example, let X be the following 6x4 matrix: |
| /// |
| /// X := [[0, 1, 2, 0], |
| /// [0, 0, 3, 0], |
| /// [0, 4, 0, 5], |
| /// [0, 0, 0, 0], |
| /// [6, 0, 7, 8], |
| /// [0, 9, 0, 0]]. |
| /// |
| /// The array of non-zero values in X is: |
| /// |
| /// values(X) = [1, 2, 3, 4, 5, 6, 7, 8, 9]. |
| /// |
| /// And the indptr of X is: |
| /// |
| /// indptr(X) = [0, 2, 3, 5, 5, 8, 10]. |
| indptrBuffer: Buffer; |
| |
| /// The type of values in indicesBuffer |
| indicesType: Int; |
| |
| /// indicesBuffer stores the location and size of the array that |
| /// contains the column indices of the corresponding non-zero values. |
| /// The type of index value is long. |
| /// |
| /// For example, the indices of the above X is: |
| /// |
| /// indices(X) = [1, 2, 2, 1, 3, 0, 2, 3, 1]. |
| /// |
| /// Note that the indices are sorted in lexicographical order for each row. |
| indicesBuffer: Buffer; |
| } |
| |
| union SparseTensorIndex { |
| SparseTensorIndexCOO, |
| SparseMatrixIndexCSR |
| } |
| |
| table SparseTensor { |
| /// The type of data contained in a value cell. |
| /// Currently only fixed-width value types are supported, |
| /// no strings or nested types. |
| type: Type; |
| |
| /// The dimensions of the tensor, optionally named. |
| shape: [TensorDim]; |
| |
| /// The number of non-zero values in a sparse tensor. |
| non_zero_length: long; |
| |
| /// Sparse tensor index |
| sparseIndex: SparseTensorIndex; |
| |
| /// The location and size of the tensor's data |
| data: Buffer; |
| } |
| |
| root_type SparseTensor; |