FM / ATen

/usr/local/lib64/python3.6/site-packages/torch/include/ATen/

/usr/local/lib64/python3.6/site-packages/torch/include/ATen

Name	Size	Mode	Actions
core/	-	0755	rm
cpu/	-	0755	rm
cuda/	-	0755	rm
cudnn/	-	0755	rm
detail/	-	0755	rm
hip/	-	0755	rm
native/	-	0755	rm
quantized/	-	0755	rm
AccumulateType.h	4438	0644	edit dl rm
ArrayRef.h	44	0644	edit dl rm
ATen.h	998	0644	edit dl rm
autocast_mode.h	6716	0644	edit dl rm
Backend.h	43	0644	edit dl rm
Backtrace.h	46	0644	edit dl rm
BatchedFallback.h	965	0644	edit dl rm
BatchedTensorImpl.h	5383	0644	edit dl rm
CompositeExplicitAutogradFunctions.h	1622	0644	edit dl rm
CompositeExplicitAutogradFunctions_inl.h	54075	0644	edit dl rm
CompositeImplicitAutogradFunctions.h	1622	0644	edit dl rm
CompositeImplicitAutogradFunctions_inl.h	142082	0644	edit dl rm
Config.h	734	0644	edit dl rm
Context.h	12767	0644	edit dl rm
cpp_custom_type_hack.h	5326	0644	edit dl rm
CPUApplyUtils.h	12582	0644	edit dl rm
CPUFixedAllocator.h	830	0644	edit dl rm
CPUFunctions.h	1600	0644	edit dl rm
CPUFunctions_inl.h	171924	0644	edit dl rm
CPUGeneratorImpl.h	1431	0644	edit dl rm
CUDAFunctions.h	1601	0644	edit dl rm
CUDAFunctions_inl.h	185696	0644	edit dl rm
CUDAGeneratorImpl.h	4695	0644	edit dl rm
Device.h	42	0644	edit dl rm
DeviceGuard.h	1134	0644	edit dl rm
Dimname.h	31	0644	edit dl rm
DimVector.h	46	0644	edit dl rm
Dispatch.h	52137	0644	edit dl rm
div_rtn.h	204	0644	edit dl rm
DLConvertor.h	576	0644	edit dl rm
dlpack.h	5244	0644	edit dl rm
DynamicLibrary.h	369	0644	edit dl rm
ExpandUtils.h	14506	0644	edit dl rm
Formatting.h	34	0644	edit dl rm
Functions.h	846326	0644	edit dl rm
Generator.h	46	0644	edit dl rm
InferSize.h	2143	0644	edit dl rm
InitialTensorOptions.h	445	0644	edit dl rm
Layout.h	42	0644	edit dl rm
MapAllocator.h	2999	0644	edit dl rm
MatrixRef.h	3016	0644	edit dl rm
MemoryOverlap.h	1117	0644	edit dl rm
MetaFunctions.h	1601	0644	edit dl rm
MetaFunctions_inl.h	84006	0644	edit dl rm
NamedTensor.h	35	0644	edit dl rm
NamedTensorUtils.h	5747	0644	edit dl rm
NativeFunctions.h	354651	0644	edit dl rm
NativeMetaFunctions.h	35445	0644	edit dl rm
NumericUtils.h	2787	0644	edit dl rm
OpaqueTensorImpl.h	6080	0644	edit dl rm
Operators.h	1707199	0644	edit dl rm
OpMathType.h	460	0644	edit dl rm
Parallel.h	4875	0644	edit dl rm
ParallelNative.h	2443	0644	edit dl rm
ParallelNativeTBB.h	2934	0644	edit dl rm
ParallelOpenMP.h	3049	0644	edit dl rm
PTThreadPool.h	394	0644	edit dl rm
record_function.h	24044	0644	edit dl rm
RedispatchFunctions.h	1112886	0644	edit dl rm
RegistrationDeclarations.h	545777	0644	edit dl rm
SavedTensorHooks.h	328	0644	edit dl rm
Scalar.h	44	0644	edit dl rm
ScalarOps.h	2272	0644	edit dl rm
ScalarType.h	129	0644	edit dl rm
SequenceNumber.h	373	0644	edit dl rm
SmallVector.h	47	0644	edit dl rm
SparseCsrTensorImpl.h	2045	0644	edit dl rm
SparseCsrTensorUtils.h	523	0644	edit dl rm
SparseTensorImpl.h	12417	0644	edit dl rm
SparseTensorUtils.h	4219	0644	edit dl rm
Storage.h	43	0644	edit dl rm
Tensor.h	48	0644	edit dl rm
TensorAccessor.h	51	0644	edit dl rm
TensorGeometry.h	1855	0644	edit dl rm
TensorIndexing.h	21923	0644	edit dl rm
TensorIterator.h	29962	0644	edit dl rm
TensorIteratorInternal.h	1862	0644	edit dl rm
TensorMeta.h	2917	0644	edit dl rm
TensorNames.h	2519	0644	edit dl rm
TensorOperators.h	3275	0644	edit dl rm
TensorOptions.h	49	0644	edit dl rm
TensorUtils.h	5687	0644	edit dl rm
ThreadLocalState.h	3289	0644	edit dl rm
TracerMode.h	5576	0644	edit dl rm
TypeDefault.h	680	0644	edit dl rm
Utils.h	5993	0644	edit dl rm
Version.h	340	0644	edit dl rm
VmapMode.h	952	0644	edit dl rm
VmapTransforms.h	7654	0644	edit dl rm
WrapDimUtils.h	3438	0644	edit dl rm
WrapDimUtilsMulti.h	768	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/include/ATen/SparseTensorUtils.h (4219B)

#pragma once

#include <ATen/ATen.h>
#include <ATen/SparseTensorImpl.h>
#include <ATen/Parallel.h>

namespace at { namespace sparse {

// Just for documentary purposes
using SparseTensor = Tensor;
using SparseType = Type;

// This is an internal utility function for getting at the SparseTensorImpl,
// so that we can write sparse tensor specific accessors for special fields
// in SparseTensor.  You should only use this for writing low level
// setters/getters for SparseTensorImpl fields; otherwise, you should use
// the low level setters/getters that were implemented using this.
//
// This may be called repeatedly, so make sure it's pretty cheap.
inline  SparseTensorImpl* get_sparse_impl(const SparseTensor& self) {
  TORCH_INTERNAL_ASSERT(self.is_sparse(), "_internal_get_SparseTensorImpl: not a sparse tensor");
  return static_cast<SparseTensorImpl*>(self.unsafeGetTensorImpl());
}

// Takes indices and values and directly puts them into the sparse tensor, no
// copy.  This used to be called THSTensor_(_move)
inline void alias_into_sparse(const SparseTensor& self, const Tensor& indices, const Tensor& values) {
  get_sparse_impl(self)->set_indices_and_values_unsafe(indices, values);
}

// Take indices and values and makes a (data) copy of them to put into the sparse
// indices/values.  This used to be called THSTensor_(_set)
inline void copy_into_sparse(const SparseTensor& self, const Tensor& indices, const Tensor& values, bool non_blocking) {
  alias_into_sparse(
      self,
      indices.to(self._indices().options(), non_blocking, /*copy=*/true),
      values.to(self._values().options(), non_blocking, /*copy=*/true));
}

// TODO: put this into the public API
inline bool is_same_tensor(const Tensor& lhs, const Tensor& rhs) {
  return lhs.unsafeGetTensorImpl() == rhs.unsafeGetTensorImpl();
}

inline bool is_same_density(const SparseTensor& self, const SparseTensor& src) {
  return self.sparse_dim() == src.sparse_dim() && self.dense_dim() == src.dense_dim();
}

// Give us a new values tensor, with the same dimensionality
// as 'values' but with a new number of non-zero elements.
// TODO: Expose this for real in ATen, some day?
// NB: Doesn't preserve data.
inline Tensor new_values_with_size_of(const Tensor& values, int64_t nnz) {
  std::vector<int64_t> size = values.sizes().vec();
  size[0] = nnz;
  return at::empty(size, values.options());
}

// NOTE [ Flatten Sparse Indices ]
// This helper function flattens a sparse indices tensor (a Tensor) into a 1D
// indices tensor. E.g.,
//   input = [[2, 4, 0],
//            [3, 1, 10]]
//   full_size = [2, 12]
//   output = [ 2 * 12 + 3, 4 * 12 + 1, 0 * 12 + 10 ] = [27, 49, 10]
//
// In other words, assuming that each `indices[i, :]` is a valid index to a
// tensor `t` of shape `full_size`. This returns the corresponding indices to
// the flattened tensor `t.reshape( prod(full_size[:indices.size(0)]), -1 )`.
// if forceClone is true, the result will forced to be a clone of self.
// if force_clone is true, the result will forced to be a clone of self.
TORCH_API Tensor flatten_indices(const Tensor& indices, IntArrayRef full_size, bool force_clone = false);

// Flatten sparse tensor's indices from nD to 1D, similar to NOTE [ Flatten Sparse Indices ],
// except this one allows partial flatten: only flatten on specified dims. Note that
// the flatten indices might be uncoalesced if dims_to_flatten.size() < sparse_dim.
// Also if input indices is already coalesced, the flattened indices will also be sorted.
//
// args:
//    indices: sparse tensor indices
//    sizes: sparse tensor sizes
//    dims_to_flatten: a list of dim index to flatten
//
// Ex1:
//   indices = [[2, 4, 0],
//             [3, 1, 3]]
//   sizes = [2, 12]
//   dims_to_flatten = [0, 1]
//   new_indices = [ 2 * 12 + 3, 4 * 12 + 1, 0 * 12 + 3 ] = [27, 49, 3]
//
// Ex2:
//   dims_to_flatten = [1]
//   new_indices = [ 3, 1, 3 ]  # uncoalesced
TORCH_API Tensor flatten_indices_by_dims(const Tensor& indices, const IntArrayRef& sizes, const IntArrayRef& dims_to_flatten);

// Find the CSR representation for a row `indices` from the COO format
TORCH_API Tensor coo_to_csr(const int64_t* indices, int64_t dim, int64_t nnz);

}} // namespace at::sparse

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