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/external/tensorflow/tensorflow/contrib/factorization/python/kernel_tests/
Dmasked_matmul_benchmark.py40 def _make_sparse_mask(self, mask_shape, nnz, sort=False): argument
54 [nnz], minval=0, maxval=num_rows, dtype=dtypes.int64)
56 [nnz], minval=0, maxval=num_cols, dtype=dtypes.int64)
58 values = array_ops.ones([nnz])
62 def _run_graph(self, a_shape, b_shape, nnz, num_iters, sort=False, argument
87 mask_indices_ph = array_ops.placeholder(dtypes.int64, shape=[nnz, 2])
90 mask = self._make_sparse_mask(mask_shape, nnz, sort)
113 nnz=nnz,
132 nnz = 100000
139 self._run_graph(a_shape, b_shape, nnz, num_iters, sort, transpose_a,
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_SparseAddGrad.pbtxt6 1-D with shape `[nnz(sum)]`. The gradient with respect to
13 2-D. The `indices` of the `SparseTensor` A, size `[nnz(A), ndims]`.
19 2-D. The `indices` of the `SparseTensor` B, size `[nnz(B), ndims]`.
26 `[nnz(sum), ndims]`.
32 1-D with shape `[nnz(A)]`. The gradient with respect to the
39 1-D with shape `[nnz(B)]`. The gradient with respect to the
Dapi_def_SparseAdd.pbtxt6 2-D. The `indices` of the first `SparseTensor`, size `[nnz, ndims]` Matrix.
12 1-D. The `values` of the first `SparseTensor`, size `[nnz]` Vector.
24 2-D. The `indices` of the second `SparseTensor`, size `[nnz, ndims]` Matrix.
30 1-D. The `values` of the second `SparseTensor`, size `[nnz]` Vector.
60 In the following shapes, `nnz` is the count after taking `thresh` into account.
Dapi_def_SparseTensorDenseAdd.pbtxt6 2-D. The `indices` of the `SparseTensor`, with shape `[nnz, ndims]`.
12 1-D. The `values` of the `SparseTensor`, with shape `[nnz]`.
Dapi_def_SparseTensorDenseMatMul.pbtxt6 2-D. The `indices` of the `SparseTensor`, size `[nnz, 2]` Matrix.
12 1-D. The `values` of the `SparseTensor`, size `[nnz]` Vector.
/external/eigen/Eigen/src/SparseCore/
DSparseMap.h124 …inline SparseMapBase(Index rows, Index cols, Index nnz, IndexPointer outerIndexPtr, IndexPointer i…
126 …(IsRowMajor?cols:rows), m_zero_nnz(0,internal::convert_index<StorageIndex>(nnz)), m_outerIndex(out…
131 inline SparseMapBase(Index size, Index nnz, IndexPointer innerIndexPtr, ScalarPointer valuePtr)
132 …: m_outerSize(1), m_innerSize(size), m_zero_nnz(0,internal::convert_index<StorageIndex>(nnz)), m_o…
195 …inline SparseMapBase(Index rows, Index cols, Index nnz, StorageIndex* outerIndexPtr, StorageIndex*…
197 : Base(rows, cols, nnz, outerIndexPtr, innerIndexPtr, valuePtr, innerNonZerosPtr)
201 inline SparseMapBase(Index size, Index nnz, StorageIndex* innerIndexPtr, Scalar* valuePtr)
202 : Base(size, nnz, innerIndexPtr, valuePtr)
245 inline Map(Index rows, Index cols, Index nnz, StorageIndex* outerIndexPtr,
247 : Base(rows, cols, nnz, outerIndexPtr, innerIndexPtr, valuePtr, innerNonZerosPtr)
[all …]
DSparseBlock.h46 Index nnz = 0; in nonZeros() local
50 ++nnz; in nonZeros()
51 return nnz; in nonZeros()
132 Index nnz = tmp.nonZeros();
145 if(nnz>free_size)
148 … typename SparseMatrixType::Storage newdata(m_matrix.data().allocatedSize() - block_size + nnz);
153 …internal::smart_copy(tmp.valuePtr() + tmp_start, tmp.valuePtr() + tmp_start + nnz, newd…
154 …internal::smart_copy(tmp.innerIndexPtr() + tmp_start, tmp.innerIndexPtr() + tmp_start + nnz, newd…
156 …matrix.valuePtr()+end, matrix.valuePtr()+end + tail_size, newdata.valuePtr()+start+nnz);
157 …matrix.innerIndexPtr()+end, matrix.innerIndexPtr()+end + tail_size, newdata.indexPtr()+start+nnz);
[all …]
DConservativeSparseSparseProduct.h51 Index nnz = 0; variable
64 indices[nnz] = i;
65 ++nnz;
74 for(Index k=0; k<nnz; ++k)
93 if((nnz<200 && nnz<t200) || nnz * numext::log2(int(nnz)) < t)
95 if(nnz>1) std::sort(indices,indices+nnz);
96 for(Index k=0; k<nnz; ++k)
DMappedSparseMatrix.h42 …inline MappedSparseMatrix(Index rows, Index cols, Index nnz, StorageIndex* outerIndexPtr, StorageI…
43 : Base(rows, cols, nnz, outerIndexPtr, innerIndexPtr, valuePtr, innerNonZeroPtr)
/external/tensorflow/tensorflow/core/kernels/
Dsparse_conditional_accumulator.h164 const int64 nnz = grad_idx->dim_size(0); in AllocateAndAssignToAccumGradFunction() local
169 accum_idx_vec_->reserve(nnz); in AllocateAndAssignToAccumGradFunction()
170 for (int i = 0; i < nnz; i++) { in AllocateAndAssignToAccumGradFunction()
186 count_element_ = new std::vector<int>(nnz, 1); in AllocateAndAssignToAccumGradFunction()
323 const int64 nnz = count_element_->size(); in DivideAccumGradByCounter() local
340 for (int64 i = 0; i < nnz; i++) { in DivideAccumGradByCounter()
387 const int64 nnz = grad_idx_tensor->dim_size(0); in GetAndValidateTensorInputForApplyGrad() local
391 OP_REQUIRES_BOOLEAN(ctx, grad_val_tensor->dim_size(0) == nnz, in GetAndValidateTensorInputForApplyGrad()
392 errors::InvalidArgument("Expected ", nnz, in GetAndValidateTensorInputForApplyGrad()
424 const int64 nnz = accum_idx_vec_->size(); in ReturnIdxTensor() local
[all …]
Dsparse_tensor_dense_matmul_op_gpu.cu.cc31 __global__ void SparseTensorDenseMatMulKernel(int nnz, int m, int b_rows, in SparseTensorDenseMatMulKernel() argument
39 CUDA_1D_KERNEL_LOOP(index, nnz * p) { in SparseTensorDenseMatMulKernel()
73 int nnz = a_values.size(); in Compute() local
82 CudaLaunchConfig config = GetCudaLaunchConfig(p * nnz, d); in Compute()
86 config.block_count, config.thread_per_block, 0, d.stream(), nnz, m, in Compute()
Dsparse_tensor_dense_matmul_op_test.cc42 static Graph* SparseTensorDenseMatmul(int nnz, int m, int k, int n, in SparseTensorDenseMatmul() argument
45 Tensor a_values(DT_FLOAT, TensorShape({nnz})); in SparseTensorDenseMatmul()
46 Tensor a_indices(DT_INT64, TensorShape({nnz, 2})); in SparseTensorDenseMatmul()
57 for (int32 i = 0; i < nnz; ++i) { in SparseTensorDenseMatmul()
Dsparse_dense_binary_op_shared.cc106 const int64 nnz = indices_t->dim_size(0); in Compute() local
108 ctx->allocate_output(0, TensorShape({nnz}), &output_values)); in Compute()
110 ctx, ctx->allocate_temp(DataTypeToEnum<T>::value, TensorShape({nnz}), in Compute()
129 for (int i = 0; i < nnz; ++i) { \ in Compute()
Dsparse_tensor_dense_matmul_op.cc68 const int64 nnz = a_indices->shape().dim_size(0); in Compute() local
69 OP_REQUIRES(ctx, nnz == a_values->NumElements(), in Compute()
111 OP_REQUIRES(ctx, FastBoundsCheck(nnz * outer_right, int32max), in Compute()
251 const std::size_t nnz = a_values.size(); in Compute() local
267 for (std::size_t i = 0; i < nnz; ++i) { in Compute()
287 for (std::size_t i = 0; i < nnz; ++i) { \ in Compute()
Dreshape_util.cc54 const int64 nnz = input_indices_in.shape().dim_size(0); in Reshape() local
128 TensorShape({nnz, output_rank}), in Reshape()
132 for (int i = 0; i < nnz; ++i) { in Reshape()
Dsparse_reduce_op.cc274 int64 nnz = 0; in Compute() local
277 nnz++; in Compute()
283 0, TensorShape({nnz, reduction.reduced_shape.dims()}), in Compute()
292 ctx->allocate_output(1, TensorShape({nnz}), &out_values_t)); in Compute()
/external/libavc/common/arm/
Dih264_resi_trans_quant_a9.s61 @ pointer to store nnz
92 @ :nnz
108 @R9 :nnz
227 vpadd.u8 d18, d16, d17 @I pair add nnz 1
228 vpadd.u8 d20, d18, d19 @I Pair add nnz 2
229 vpadd.u8 d22, d20, d21 @I Pair add nnz 3
233 vmov.u8 d25, #16 @I Get max nnz
234 vsub.u8 d26, d25, d24 @I invert current nnz
236 vst1.u8 d26[0], [r9] @I Write nnz
259 @ pointer to store nnz
[all …]
/external/eigen/bench/
Dsparse_setter.cpp302 const int nnz, in coo_tocsr() argument
312 for (int n = 0; n < nnz; n++){ in coo_tocsr()
322 Bp[n_row] = nnz; in coo_tocsr()
325 for(int n = 0; n < nnz; n++){ in coo_tocsr()
384 I nnz = 0; in csr_sum_duplicates() local
397 Aj[nnz] = j; in csr_sum_duplicates()
398 Ax[nnz] = x; in csr_sum_duplicates()
399 nnz++; in csr_sum_duplicates()
401 Ap[i+1] = nnz; in csr_sum_duplicates()
/external/eigen/Eigen/src/OrderingMethods/
DOrdering.h134 StorageIndex nnz = StorageIndex(mat.nonZeros()); in operator() local
136 StorageIndex Alen = internal::colamd_recommended(nnz, m, n); in operator()
144 for(StorageIndex i=0; i < nnz; i++) A(i) = mat.innerIndexPtr()[i]; in operator()
DEigen_Colamd.h257 inline IndexType colamd_recommended ( IndexType nnz, IndexType n_row, IndexType n_col) in colamd_recommended() argument
259 if ((nnz) < 0 || (n_row) < 0 || (n_col) < 0) in colamd_recommended()
262 return (2 * (nnz) + colamd_c (n_col) + colamd_r (n_row) + (n_col) + ((nnz) / 5)); in colamd_recommended()
327 IndexType nnz ; /* nonzeros in A */ in colamd() local
385 nnz = p [n_col] ; in colamd()
386 if (nnz < 0) /* nnz must be >= 0 */ in colamd()
389 stats [COLAMD_INFO1] = nnz ; in colamd()
390 COLAMD_DEBUG0 (("colamd: number of entries negative %d\n", nnz)) ; in colamd()
414 need = 2*nnz + n_col + Col_size + Row_size ; in colamd()
447 n_col2, max_deg, 2*nnz) ; in colamd()
/external/eigen/Eigen/src/IterativeLinearSolvers/
DIncompleteCholesky.h217 Index nnz = m_L.nonZeros(); in factorize() local
218 Map<VectorSx> vals(m_L.valuePtr(), nnz); //values in factorize()
219 Map<VectorIx> rowIdx(m_L.innerIndexPtr(), nnz); //Row indices in factorize()
329 vals = Map<const VectorSx>(L_save.valuePtr(), nnz); in factorize()
330 rowIdx = Map<const VectorIx>(L_save.innerIndexPtr(), nnz); in factorize()
/external/libavc/encoder/
Dih264e_cavlc.c1233 UWORD32 *nnz; in ih264e_write_pslice_mb_cavlc() local
1246 nnz = (UWORD32 *)ps_ent_ctxt->pu1_top_nnz_luma[ps_ent_ctxt->i4_mb_x]; in ih264e_write_pslice_mb_cavlc()
1247 *nnz = 0; in ih264e_write_pslice_mb_cavlc()
1249 nnz = (UWORD32 *)ps_ent_ctxt->pu1_top_nnz_cbcr[ps_ent_ctxt->i4_mb_x]; in ih264e_write_pslice_mb_cavlc()
1250 *nnz = 0; in ih264e_write_pslice_mb_cavlc()
1544 UWORD32 *nnz; in ih264e_write_bslice_mb_cavlc() local
1557 nnz = (UWORD32 *)ps_ent_ctxt->pu1_top_nnz_luma[ps_ent_ctxt->i4_mb_x]; in ih264e_write_bslice_mb_cavlc()
1558 *nnz = 0; in ih264e_write_bslice_mb_cavlc()
1560 nnz = (UWORD32 *)ps_ent_ctxt->pu1_top_nnz_cbcr[ps_ent_ctxt->i4_mb_x]; in ih264e_write_bslice_mb_cavlc()
1561 *nnz = 0; in ih264e_write_bslice_mb_cavlc()
/external/tensorflow/tensorflow/core/util/sparse/
DREADME.md180 Expected input shapes, orders, and `nnz()`:
213 EXPECT_EQ(conc.nnz(), st1.nnz() + st2.nnz() + st3.nnz());
/external/eigen/doc/
DSparseQuickReference.dox25 sm1.reserve(nnz); // Allocate room for nnz nonzeros elements.
28 <td> Note that when calling reserve(), it is not required that nnz is the exact number of nonzero e…
261 int innerIndices[nnz];
262 double values[nnz];
263 Map<SparseMatrix<double> > sm1(rows,cols,nnz,outerIndexPtr, // read-write
/external/tensorflow/tensorflow/python/kernel_tests/
Dsparse_tensor_dense_matmul_grad_test.py65 sp_t, nnz = self._randomTensor(
78 sp_t_val_shape = [nnz]

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