Tensors#
Dense Tensors#
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classTensor#
Subclassed by arrow::NumericTensor< TYPE >
Public Functions
Constructor with no dimension names or strides, data assumed to be row-major.
Constructor with non-negative strides.
Constructor with non-negative strides and dimension names.
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int64_tsize()const#
Total number of value cells in the tensor.
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inlineboolis_mutable()const#
Return true if the underlying data buffer is mutable.
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boolis_contiguous()const#
Either row major or column major.
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boolis_row_major()const#
AKA "C order".
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boolis_column_major()const#
AKA "Fortran order".
Public Static Functions
Create a Tensor with full parameters.
This factory function will return Status::Invalid when the parameters are inconsistent
- Parameters:
type – [in] The data type of the tensor values
data – [in] The buffer of the tensor content
shape – [in] The shape of the tensor
strides – [in] The strides of the tensor (if this is empty, the data assumed to be row-major)
dim_names – [in] The names of the tensor dimensions
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staticinlineint64_tCalculateValueOffset(conststd::vector<int64_t>&strides, conststd::vector<int64_t>&index)#
Return the offset of the given index on the given strides.
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template<typenameTYPE>
classNumericTensor:publicarrow::Tensor # Public Functions
Constructor with non-negative strides and dimension names.
Constructor with no dimension names or strides, data assumed to be row-major.
Constructor with non-negative strides.
Public Static Functions
Create a NumericTensor with full parameters.
This factory function will return Status::Invalid when the parameters are inconsistent
- Parameters:
data – [in] The buffer of the tensor content
shape – [in] The shape of the tensor
strides – [in] The strides of the tensor (if this is empty, the data assumed to be row-major)
dim_names – [in] The names of the tensor dimensions
Sparse Tensors#
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enumarrow::SparseTensorFormat::type#
EXPERIMENTAL: The index format type of SparseTensor.
Values:
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enumeratorCOO#
Coordinate list (COO) format.
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enumeratorCSR#
Compressed sparse row (CSR) format.
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enumeratorCSC#
Compressed sparse column (CSC) format.
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enumeratorCSF#
Compressed sparse fiber (CSF) format.
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enumeratorCOO#
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classSparseIndex#
EXPERIMENTAL: The base class for the index of a sparse tensor.
SparseIndex describes where the non-zero elements are within a SparseTensor.
There are several ways to represent this. The format_id is used to distinguish what kind of representation is used. Each possible value of format_id must have only one corresponding concrete subclass of SparseIndex.
Subclassed by arrow::internal::SparseIndexBase< SparseCOOIndex >, arrow::internal::SparseIndexBase< SparseCSCIndex >, arrow::internal::SparseIndexBase< SparseCSFIndex >, arrow::internal::SparseIndexBase< SparseCSRIndex >, arrow::internal::SparseIndexBase< SparseIndexType >
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classSparseCOOIndex:publicarrow::internal::SparseIndexBase<SparseCOOIndex >#
EXPERIMENTAL: The index data for a COO sparse tensor.
A COO sparse index manages the location of its non-zero values by their coordinates.
Public Functions
Construct SparseCOOIndex from column-major NumericTensor.
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inlineconststd::shared_ptr<Tensor >&indices()const#
Return a tensor that has the coordinates of the non-zero values.
The returned tensor is a N x D tensor where N is the number of non-zero values and D is the number of dimensions in the logical data. The column at index
iis a D-tuple of coordinates indicating that the logical value at those coordinates should be found at physical indexi.
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inlinevirtualint64_tnon_zero_length()constoverride#
Return the number of non zero values in the sparse tensor related to this sparse index.
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inlineboolis_canonical()const#
Return whether a sparse tensor index is canonical, or not.
If a sparse tensor index is canonical, it is sorted in the lexicographical order, and the corresponding sparse tensor doesn’t have duplicated entries.
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virtualstd::stringToString()constoverride#
Return a string representation of the sparse index.
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inlineboolEquals(constSparseCOOIndex &other)const#
Return whether the COO indices are equal.
Public Static Functions
Make SparseCOOIndex from a coords tensor and canonicality.
Make SparseCOOIndex from a coords tensor with canonicality auto-detection.
Make SparseCOOIndex from raw properties with canonicality auto-detection.
Make SparseCOOIndex from raw properties.
Make SparseCOOIndex from sparse tensor’s shape properties and data with canonicality auto-detection.
The indices_data should be in row-major (C-like) order. If not, use the raw properties constructor.
Make SparseCOOIndex from sparse tensor’s shape properties and data.
The indices_data should be in row-major (C-like) order. If not, use the raw properties constructor.
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classSparseCSRIndex:publicarrow::internal::SparseCSXIndex<SparseCSRIndex ,internal::SparseMatrixCompressedAxis::ROW>#
EXPERIMENTAL: The index data for a CSR sparse matrix.
A CSR sparse index manages the location of its non-zero values by two vectors.
The first vector, called indptr, represents the range of the rows; the i-th row spans from indptr[i] to indptr[i+1] in the corresponding value vector. So the length of an indptr vector is the number of rows + 1.
The other vector, called indices, represents the column indices of the corresponding non-zero values. So the length of an indices vector is same as the number of non-zero-values.
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classSparseTensor#
EXPERIMENTAL: The base class of sparse tensor container.
Subclassed by arrow::SparseTensorImpl< SparseIndexType >
Public Functions
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inlinestd::shared_ptr<Buffer >data()const#
Return a buffer that contains the value vector of the sparse tensor.
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inlineconstuint8_t*raw_data()const#
Return an immutable raw data pointer.
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inlineuint8_t*raw_mutable_data()const#
Return a mutable raw data pointer.
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inlineconststd::vector<int64_t>&shape()const#
Return a shape vector of the sparse tensor.
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inlineconststd::shared_ptr<SparseIndex >&sparse_index()const#
Return a sparse index of the sparse tensor.
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inlineintndim()const#
Return a number of dimensions of the sparse tensor.
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inlineconststd::vector<std::string>&dim_names()const#
Return a vector of dimension names.
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conststd::string&dim_name(inti)const#
Return the name of the i-th dimension.
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int64_tsize()const#
Total number of value cells in the sparse tensor.
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inlineboolis_mutable()const#
Return true if the underlying data buffer is mutable.
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inlineint64_tnon_zero_length()const#
Total number of non-zero cells in the sparse tensor.
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boolEquals(constSparseTensor &other, constEqualOptions&=EqualOptions::Defaults())const#
Return whether sparse tensors are equal.
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Result <std::shared_ptr<Tensor >>ToTensor(MemoryPool *pool)const#
Return dense representation of sparse tensor as tensor.
The returned Tensor has row-major order (C-like).
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inlinestd::shared_ptr<Buffer >data()const#
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template<typenameSparseIndexType>
classSparseTensorImpl:publicarrow::SparseTensor # EXPERIMENTAL: Concrete sparse tensor implementation classes with sparse index type.
Public Functions
Construct a sparse tensor from physical data buffer and logical index.
Construct an empty sparse tensor.
Public Static Functions
Create a SparseTensor with full parameters.
Create a sparse tensor from a dense tensor.
The dense tensor is re-encoded as a sparse index and a physical data buffer for the non-zero value.
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usingarrow::SparseCOOTensor=SparseTensorImpl <SparseCOOIndex >#
EXPERIMENTAL: Type alias for COO sparse tensor.
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usingarrow::SparseCSCMatrix=SparseTensorImpl <SparseCSCIndex>#
EXPERIMENTAL: Type alias for CSC sparse matrix.
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usingarrow::SparseCSFTensor=SparseTensorImpl <SparseCSFIndex>#
EXPERIMENTAL: Type alias for CSF sparse matrix.
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usingarrow::SparseCSRMatrix=SparseTensorImpl <SparseCSRIndex >#
EXPERIMENTAL: Type alias for CSR sparse matrix.