| /external/tensorflow/tensorflow/core/kernels/sparse/ |
| D | kernels.cc | 45 const int64 total_nnz = indices.dimension(0); in operator ()() local
52 if (csr_col_ind.size() != total_nnz) { in operator ()()
55 " vs. ", total_nnz); in operator ()()
64 for (int64 i = 0; i < total_nnz; ++i) { in operator ()()
70 for (int64 i = 0; i < total_nnz; ++i) { in operator ()()
86 batch_ptr(prev_batch + 1) = total_nnz; in operator ()()
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| D | csr_sparse_matrix_to_sparse_tensor_op.cc | 84 const int64 total_nnz = csr_sparse_matrix->total_nnz(); in Compute() local
91 c, c->allocate_output(0, TensorShape({total_nnz, rank}), &indices)); in Compute()
130 csr_sparse_matrix->total_nnz() / batch_size /* cost per unit */, in Compute()
151 const int64 total_nnz = csr_sparse_matrix->total_nnz(); in Compute() local
158 c, c->allocate_output(0, TensorShape({total_nnz, rank}), &indices_t)); in Compute()
162 c->allocate_output(1, TensorShape({total_nnz}), &values_t)); in Compute()
172 OP_REQUIRES_OK(c, c->allocate_temp(DT_INT32, TensorShape({total_nnz}), in Compute()
191 if (total_nnz > 0) { in Compute()
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| D | softmax_op.cc | 58 const int total_nnz = logits_matrix->total_nnz(); in Compute() local
62 TensorShape({total_nnz}), &output_values_t)); in Compute()
75 if (total_nnz > 0) { in Compute()
167 const int total_nnz = softmax_matrix->total_nnz(); in Compute() local
171 DataTypeToEnum<T>::value, TensorShape({total_nnz}), in Compute()
183 if (total_nnz > 0) { in Compute()
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| D | csr_sparse_matrix_to_dense_op.cc | 115 csr_sparse_matrix->total_nnz() / batch_size /* cost per unit */, in Compute()
145 const int64 total_nnz = csr_sparse_matrix->total_nnz(); in Compute() local
151 OP_REQUIRES_OK(c, c->allocate_temp(DT_INT64, TensorShape({total_nnz, rank}), in Compute()
156 TensorShape({total_nnz}), &values_t)); in Compute()
166 OP_REQUIRES_OK(c, c->allocate_temp(DT_INT32, TensorShape({total_nnz}), in Compute()
185 if (total_nnz > 0) { in Compute()
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| D | sparse_tensor_to_csr_sparse_matrix_op.cc | 76 const int64 total_nnz = values.NumElements(); in Compute() local
80 Tensor csr_col_ind(cpu_allocator(), DT_INT32, TensorShape({total_nnz})); in Compute()
198 int total_nnz = batch_ptr(batch_size); in ComputeAsync() local
200 c, total_nnz == values_t.NumElements(), in ComputeAsync()
204 total_nnz, " vs. ", values_t.NumElements()), in ComputeAsync()
214 c->allocate_temp(DT_INT32, TensorShape({total_nnz}), &coo_row_ind_t), in ComputeAsync()
218 c->allocate_temp(DT_INT32, TensorShape({total_nnz}), &coo_col_ind_t), in ComputeAsync()
231 if (total_nnz > 0) { in ComputeAsync()
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| D | conj_op.cc | 51 const int total_nnz = a.total_nnz(); in operator ()() local
54 DataTypeToEnum<T>::value, TensorShape({total_nnz}), &b_values_t)); in operator ()()
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| D | dense_to_csr_sparse_matrix_op.cc | 97 const int64 total_nnz = indices.NumElements() / rank; in Compute() local
104 Tensor csr_col_ind(cpu_allocator(), DT_INT32, TensorShape({total_nnz})); in Compute()
265 int total_nnz = batch_ptr(batch_size); in ComputeAsync() local
267 c, total_nnz == values_t.NumElements(), in ComputeAsync()
271 total_nnz, " vs. ", values_t.NumElements()), in ComputeAsync()
281 c->allocate_temp(DT_INT32, TensorShape({total_nnz}), &coo_row_ind_t), in ComputeAsync()
285 c->allocate_temp(DT_INT32, TensorShape({total_nnz}), &coo_col_ind_t), in ComputeAsync()
298 if (total_nnz > 0) { in ComputeAsync()
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| D | sparse_cholesky_op.cc | 104 (input_matrix->total_nnz() / batch_size) / num_rows; in Compute()
174 const int64 total_nnz = batch_ptr_vec(batch_size); in Compute() local
177 Tensor output_col_ind(cpu_allocator(), DT_INT32, TensorShape({total_nnz})); in Compute()
179 TensorShape({total_nnz})); in Compute()
190 (3 * total_nnz) / batch_size /* cost per unit */, in Compute()
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| D | kernels_gpu.cu.cc | 58 const int total_nnz = indices.dimension(0); in operator ()() local
84 /*num_samples*/ total_nnz, in operator ()()
108 /*num_samples*/ total_nnz, in operator ()()
262 const int total_nnz) { in CSRSparseMatrixBatchMulVecKernel3D() argument
277 GPU_1D_KERNEL_LOOP(i, total_nnz) { in CSRSparseMatrixBatchMulVecKernel3D()
289 const int total_nnz = a.total_nnz(); in CSRSparseMatrixBatchMulVecImpl() local
292 TensorShape({total_nnz}), &c_values_t)); in CSRSparseMatrixBatchMulVecImpl()
314 GpuLaunchConfig config = GetGpuLaunchConfig(total_nnz, d); in CSRSparseMatrixBatchMulVecImpl()
322 b.data(), c_values.data(), batch_ptr_copy.data(), batch_size, total_nnz)); in CSRSparseMatrixBatchMulVecImpl()
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| D | mul_op.cc | 130 const int total_nnz = a.total_nnz(); in Compute() local
133 DataTypeToEnum<T>::value, TensorShape({total_nnz}), &c_values_t)); in Compute()
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| D | sparse_mat_mul_op.cc | 176 input_matrix_a->total_nnz() / in Compute()
179 input_matrix_b->total_nnz() / in Compute()
212 const int64 total_nnz = batch_ptr_vec(batch_size); in Compute() local
217 Tensor output_col_ind(cpu_allocator(), DT_INT32, TensorShape({total_nnz})); in Compute()
219 TensorShape({total_nnz})); in Compute()
227 (3 * total_nnz) / batch_size /* cost per unit */, in Compute()
475 const int total_nnz = c_batch_ptr(batch_size); in Compute() local
477 OP_REQUIRES_OK(ctx, ctx->allocate_temp(DT_INT32, TensorShape({total_nnz}), in Compute()
481 TensorShape({total_nnz}), &c_values_t)); in Compute()
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| D | transpose_op.cc | 168 const int total_nnz = input_matrix.total_nnz(); in operator ()() local
177 TF_RETURN_IF_ERROR(ctx->allocate_temp(DT_INT32, TensorShape({total_nnz}), in operator ()()
180 DataTypeToEnum<T>::value, TensorShape({total_nnz}), &output_values_t)); in operator ()()
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| D | add_op.cc | 152 const int total_nnz = c_batch_ptr(batch_size); in operator ()() local
155 ctx_->allocate_temp(DT_INT32, TensorShape({total_nnz}), &c_col_ind_t)); in operator ()()
157 DataTypeToEnum<T>::value, TensorShape({total_nnz}), &c_values_t)); in operator ()()
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| D | sparse_ordering_amd_op.cc | 96 10 * num_rows * (input_matrix->total_nnz() / batch_size); in Compute()
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| D | sparse_matrix.h | 204 inline int total_nnz() const { in total_nnz() function
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | sparse_dense_binary_op_shared_test.cc | 239 const int total_nnz = B * M * nnz_inner; in MakeSparseTensor() local
242 Tensor indices(DT_INT64, TensorShape({total_nnz, kNumDims})); in MakeSparseTensor()
243 Tensor vals(DT_FLOAT, TensorShape({total_nnz})); in MakeSparseTensor()
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