/aosp_15_r20/external/tensorflow/tensorflow/core/kernels/ |
H A D | sparse_split_op_gpu.cu.cc | 86 SliceIndexer(const Index split_dim_size, const Index num_split) in SliceIndexer() 87 : split_size_(split_dim_size / num_split), in SliceIndexer() 88 residual_(split_dim_size % num_split) {} in SliceIndexer() 119 Index input_nnz, int num_split, in LaunchSparseSplitSliceIndexesKernel() argument 136 Index input_nnz, int num_split, in SparseSplitFindSliceEndsKernel() argument 139 for (int slice_index : GpuGridRangeX<int>(num_split)) { in SparseSplitFindSliceEndsKernel() 147 Index input_nnz, int num_split, in LaunchSparseSplitFindSliceEndsKernel() argument 151 num_split, device, &SparseSplitFindSliceEndsKernel<Index>, in LaunchSparseSplitFindSliceEndsKernel() 155 device.stream(), input_nnz, num_split, in LaunchSparseSplitFindSliceEndsKernel() 214 const int64_t axis, const int num_split, in operator ()() [all …]
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H A D | split_op_test.cc | 29 static Graph* MakeGraph(int split_dim, int num_split, in MakeGraph() argument 33 in_shape.set_dim(split_dim, in_shape.dim_size(split_dim) * num_split); in MakeGraph() 41 .Attr("num_split", num_split) in MakeGraph() 46 #define BM_SPLIT_1D(num_split, chunk_size) \ argument 47 static void BM_Split_1d_##num_split##_##chunk_size( \ 50 strings::Printf("1-D %d chunks of %d each", num_split, chunk_size); \ 52 auto g = MakeGraph(/* split_dim = */ 0, num_split, {chunk_size}); \ 55 num_split * chunk_size); \ 57 BENCHMARK(BM_Split_1d_##num_split##_##chunk_size)->UseRealTime(); 59 #define BM_SPLIT_2D(split_dim, num_split, chunk_size0, chunk_size1) \ argument [all …]
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H A D | split_op.cc | 58 const int32_t num_split = num_outputs(); in ComputeEasyCases() local 67 context, num_split > 0, in ComputeEasyCases() 69 "Number of ways to split should be > 0, but got ", num_split)); in ComputeEasyCases() 71 OP_REQUIRES(context, input_shape.dim_size(split_dim) % num_split == 0, in ComputeEasyCases() 76 ") ", "and num_split ", num_split)); in ComputeEasyCases() 78 if (num_split == 1) { in ComputeEasyCases() 95 const int64_t delta = input_shape.dim_size(0) / num_split; in ComputeEasyCases() 96 for (int i = 0; i < num_split; ++i) { in ComputeEasyCases() 138 const ReshapeResultType& reshape_result, int32_t num_split, in operator ()() argument 145 (num_split >= 4 && in operator ()() [all …]
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H A D | split_v_op_test.cc | 78 #define BM_SPLITV_1D(num_split, total_size) \ argument 79 static void BM_SplitV_1d_##num_split##_##total_size( \ 82 strings::Printf("1-D %d chunks totaling %d", num_split, total_size); \ 85 GenerateRandomIntsWithSum(total_size, num_split), \ 91 BENCHMARK(BM_SplitV_1d_##num_split##_##total_size)->UseRealTime(); 93 #define BM_SPLITV_2D(split_dim, num_split, dim0, dim1) \ argument 94 static void BM_SplitV_2d_##split_dim##_##num_split##dim0##dim1( \ 98 num_split, split_dim, dim0, dim1); \ 102 GenerateRandomIntsWithSum(total_size_vec[split_dim], num_split), \ 108 BENCHMARK(BM_SplitV_2d_##split_dim##_##num_split##dim0##dim1)->UseRealTime(); [all …]
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H A D | split_v_op.cc | 55 const int32_t num_split = context->num_outputs(); in ComputeEasyCases() local 71 split_tensor.dims() == 1 && split_tensor.NumElements() == num_split, in ComputeEasyCases() 85 context, num_split > 0, in ComputeEasyCases() 87 "Number of ways to split should be > 0, but got ", num_split)); in ComputeEasyCases() 98 if (num_split == 1) { in ComputeEasyCases() 161 for (int i = 0; i < num_split; ++i) { in ComputeEasyCases() 238 const int num_split = split_start_points.size(); in operator ()() local 240 (num_split >= kMinimumSplitNum && in operator ()() 241 input_element_count >= std::min(num_threads, num_split) * 4096 && in operator ()() 242 input_element_count < num_split * 180 * 1024); in operator ()() [all …]
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H A D | sparse_split_op.cc | 36 const int64_t axis, const int num_split, in operator ()() 46 sparse_tensor, axis, num_split, &outputs)); in operator ()() 48 for (int slice_index = 0; slice_index < num_split; ++slice_index) { in operator ()() 50 context->set_output(slice_index + num_split, in operator ()() 54 slice_index + 2 * num_split, in operator ()() 69 void SparseSplitOpImpl(OpKernelContext* context, int num_split, in SparseSplitOpImpl() argument 114 context, num_split >= 1 && num_split <= input_shape.vec<int64_t>()(axis), in SparseSplitOpImpl() 118 num_split), in SparseSplitOpImpl() 130 dense_shape, axis, num_split, done); in SparseSplitOpImpl()
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H A D | split_lib_gpu.cu.cc | 77 const int32 num_split = output_ptr_data.size; in SplitOpKernel() local 82 eigen_assert(split_dim_size % num_split == 0); in SplitOpKernel() 85 int32 piece_size = split_dim_size / num_split; in SplitOpKernel() 173 const int32 num_split = output_ptr_data.size; in SplitVOpKernel_fixed() local 180 int32 piece_size = suffix_dim_size / num_split; in SplitVOpKernel_fixed()
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
H A D | split_op.cc | 38 const int32_t num_split = num_outputs(); in Compile() local 58 ctx, num_split > 0, in Compile() 60 "Number of ways to split should be > 0, but got ", num_split)); in Compile() 63 ctx, input_shape.dim_size(split_dim) % num_split == 0, in Compile() 68 "and num_split ", num_split)); in Compile() 72 const int32_t slice_size = input_shape.dim_size(split_dim) / num_split; in Compile() 89 for (int i = 0; i < num_split; ++i) { in Compile() 105 const int32_t num_split = num_outputs(); in Compile() local 129 ctx, num_split > 0, in Compile() 131 "Number of ways to split should be > 0, but got ", num_split)); in Compile() [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/python/kernel_tests/sparse_ops/ |
H A D | sparse_split_op_test.py | 85 sp_input=self._SparseTensor_4x6(), num_split=2, axis=axis)) 102 sp_input=self._SparseTensor_5x7(), num_split=3, axis=axis)) 118 sp_input=self._SparseTensor_5x7(), num_split=4, axis=axis) 140 sp_input=self._SparseTensor_5x7(), num_split=2, axis=axis)) 154 sp_input=self._SparseTensor_5x7(), num_split=3, axis=axis) 172 sp_input=self._SparseTensor_4x6(), num_split=4, axis=axis)) 193 sp_input=self._SparseTensor_4x6(), num_split=3, axis=axis)) 212 sp_input=self._SparseTensor_4x6(), num_split=6, axis=axis)) 238 sp_input=sp_input, num_split=2, axis=axis) 250 sp_input=self._SparseTensor_4x6(), num_split=3, axis=axis)) [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/core/util/sparse/ |
H A D | sparse_tensor.h | 174 const int num_split, std::vector<SparseTensor>* result); 497 const int split_dim, const int num_split, in Split() argument 502 output_indices.reserve(num_split); in Split() 503 output_values.reserve(num_split); in Split() 504 output_shapes.reserve(num_split); in Split() 508 output_indices_t.reserve(num_split); in Split() 509 output_values_t.reserve(num_split); in Split() 513 std::vector<int> num_values(num_split, 0); in Split() 516 const int split_size = split_dim_size / num_split; in Split() 518 if (!(num_split > 0 && num_split <= split_dim_size)) { in Split() [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/python/kernel_tests/array_ops/ |
H A D | split_op_test.py | 129 num_split = np.random.randint(16, 25) 131 num_split = np.random.randint(2, 8) 132 size_splits = np.random.randint(2, 8, num_split, dtype=np.int32) 139 for i in range(num_split): 156 num_split = 1000 157 size_splits = np.random.randint(1, 3, num_split, dtype=np.int32) 165 for i in range(num_split): 287 num_split = np.random.randint(9, 15) 289 num_split = np.random.randint(2, 8) 290 shape[split_dim] = np.random.randint(2, 5) * num_split [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/mlir/tfr/examples/pad/ |
H A D | ops_defs.py | 63 num_split=2) 68 num_split=2) 74 num_split=2) 79 num_split=2) 110 num_split=3) 122 num_split=2) 127 num_split=2)
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/aosp_15_r20/external/tensorflow/tensorflow/core/api_def/base_api/ |
H A D | api_def_SparseSplit.pbtxt | 45 name: "num_split" 50 summary: "Split a `SparseTensor` into `num_split` tensors along one dimension." 52 If the `shape[split_dim]` is not an integer multiple of `num_split`. Slices 53 `[0 : shape[split_dim] % num_split]` gets one extra dimension. 54 For example, if `split_dim = 1` and `num_split = 2` and the input is
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H A D | api_def_Split.pbtxt | 22 `values.shape[split_dim] / num_split`. 26 name: "num_split" 32 summary: "Splits a tensor into `num_split` tensors along one dimension."
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/aosp_15_r20/external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
H A D | SparseSplit.pbtxt | 22 number_attr: "num_split" 27 number_attr: "num_split" 32 number_attr: "num_split" 35 name: "num_split"
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H A D | Split.pbtxt | 14 number_attr: "num_split" 17 name: "num_split"
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H A D | SplitV.pbtxt | 18 number_attr: "num_split" 21 name: "num_split"
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/aosp_15_r20/external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
H A D | SparseSplit.pbtxt | 22 number_attr: "num_split" 27 number_attr: "num_split" 32 number_attr: "num_split" 35 name: "num_split"
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H A D | Split.pbtxt | 14 number_attr: "num_split" 17 name: "num_split"
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H A D | SplitV.pbtxt | 18 number_attr: "num_split" 21 name: "num_split"
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/aosp_15_r20/external/tensorflow/tensorflow/java/src/test/java/org/tensorflow/ |
H A D | GraphOperationTest.java | 182 private static int split(int[] values, int num_split) { in split() argument 187 .setAttr("num_split", num_split) in split() 193 private static int splitWithInputList(int[] values, int num_split, String name) { in splitWithInputList() argument 198 .setAttr("num_split", num_split) in splitWithInputList()
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/aosp_15_r20/external/mesa3d/src/gallium/auxiliary/gallivm/ |
H A D | lp_bld_pack.c | 650 int num_split = src_type.width * src_type.length / 128; in lp_build_pack2() local 662 assert(num_split <= LP_MAX_VECTOR_WIDTH / 128); in lp_build_pack2() 664 for (i = 0; i < num_split / 2; i++) { in lp_build_pack2() 675 for (i = 0; i < num_split / 2; i++) { in lp_build_pack2() 680 tmpres[i+num_split/2] = lp_build_intrinsic_binary(builder, intrinsic, in lp_build_pack2() 684 tmpres[i+num_split/2] = LLVMBuildBitCast(builder, tmpres[i+num_split/2], in lp_build_pack2() 688 res = lp_build_concat(gallivm, tmpres, ndst_type, num_split); in lp_build_pack2()
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/mlir/tfr/python/ |
H A D | tfr_gen_test.py | 75 z, _ = array_ops.Split(axis=0, value=x, num_split=2) 82 z = array_ops.Split(axis=0, value=x, num_split=2) 139 value=lhs, size_splits=[rhs, -1], axis=0, num_split=2) 141 value=lhs, size_splits=[rhs, rhs], axis=1, num_split=2)
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/mlir/tensorflow/utils/ |
H A D | xla_sharding_util.cc | 45 mlir::LogicalResult CreateSplitOp(const int num_split, in CreateSplitOp() argument 70 if (shape[split_dimension] % num_split != 0) { in CreateSplitOp() 76 split_dimension, num_split)); in CreateSplitOp() 79 shape[split_dimension] = shape[split_dimension] / num_split; in CreateSplitOp() 88 llvm::SmallVector<mlir::Type, 4> output_types(num_split, output_type); in CreateSplitOp() 93 builder->getIntegerAttr(builder->getIntegerType(32), num_split)); in CreateSplitOp()
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/aosp_15_r20/external/tensorflow/tensorflow/core/transforms/constant_folding/tests/ |
H A D | split_removal.mlir | 11 …%Split, %ctl_3 = Split(%Const, %VariableV2) name("s1") {T = f32, num_split = 1 : i64} : (tensor<i3… 12 …%Split_4:2, %ctl_5 = Split(%Const, %VariableV2_0) name("s2") {T = f32, num_split = 2 : i64} : (ten…
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