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usr
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local
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lib64
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python3.6
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site-packages
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torch
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include
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ATen
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/usr/local/lib64/python3.6/site-packages/torch/include/ATen
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AccumulateType.h
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SmallVector.h
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SparseCsrTensorImpl.h
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Edit:
/usr/local/lib64/python3.6/site-packages/torch/include/ATen/SparseCsrTensorImpl.h
(2045B)
#pragma once #include <ATen/Tensor.h> #include <c10/core/TensorImpl.h> #include <c10/util/Exception.h> namespace at { // Struct implementing a sparse CSR tensor. It uses three 1-D tensors for // denoting the data: `crow_indices_`, `col_indices_` and `values_`. // The `crow_indices_` tensor is a integer tensor of shape `(size(0) + 1)` // that represents the compressed row indices of the CSR tensor. The // `col_indices_` tensor is an integer tensor of shape `(nnz())` // that explicitly stores the column indices of each value of the sparse // tensor. The `values_` tensor can be of any pytorch-supported data type // and has shape `(nnz())`. // // Since the main advantage of the CSR format over the COO format is speed of // computation, care must be taken to facilitate smooth interfacing of // these data structures with optimized libraries such as MKL and MAGMA. // Since the MKL interface for pytorch currently uses indexing with int32 // type, it is important to make sure that the `crow_indices` and `col_indices` // are of type int32 when calling MKL routines such as SPMM or SPMV. // // If not calling MKL, it should be alright to use 64 bit integer tensors // for indexing. struct TORCH_API SparseCsrTensorImpl : public TensorImpl { Tensor crow_indices_; Tensor col_indices_; Tensor values_; public: explicit SparseCsrTensorImpl(at::DispatchKeySet, const caffe2::TypeMeta); void resize_as_sparse_csr_tensor_(const Tensor& src); void set_member_tensors( const Tensor& crow_indices, const Tensor& col_indices, const Tensor& values, IntArrayRef size); const Tensor& crow_indices() const { return crow_indices_; } const Tensor& col_indices() const { return col_indices_; } const Tensor& values() const { return values_; } int nnz() { return values_.size(0); } private: explicit SparseCsrTensorImpl( at::DispatchKeySet key_set, const caffe2::TypeMeta data_type, at::Tensor crow_indices, at::Tensor col_indices, at::Tensor values); }; } // namespace at
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