/aosp_15_r20/external/pytorch/test/inductor/ |
H A D | test_mmdecomp.py | 50 def init_tensor(tensor_list, **kwargs) -> torch.Tensor: function 161 init_tensor([[1], [2], [3], [4]], dtype=dtype, device=device), 162 init_tensor([[1, 2, 3, 4]], dtype=dtype, device=device), 166 init_tensor([[1, 2, 3, 4]], dtype=dtype, device=device), 167 init_tensor([[1], [2], [3], [4]], dtype=dtype, device=device), 181 init_tensor([[[1], [2], [3], [4]]] * bs, dtype=dtype, device=device), 182 init_tensor([[[1, 2, 3, 4]]] * bs, dtype=dtype, device=device), 186 init_tensor([[[1, 2, 3, 4]]] * bs, dtype=dtype, device=device), 187 init_tensor([[[1], [2], [3], [4]]] * bs, dtype=dtype, device=device),
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/tests/Dialect/gml_st/ |
H A D | tiling_and_fusion.mlir | 1 // TODO(jreiffers): Remove -cse below once the duplicate init_tensor instruction 17 %init = linalg.init_tensor [%d0, %d1] : tensor<?x?xf32> 36 // CHECK-TILE: %[[INIT:.*]] = linalg.init_tensor 50 // CHECK-POINT: %[[INIT:.*]] = linalg.init_tensor 64 %init = linalg.init_tensor [%d0, %d0] : tensor<?x?xf32> 80 // CHECK-TILE: %[[INIT:.*]] = linalg.init_tensor 96 // CHECK-POINT: %[[INIT:.*]] = linalg.init_tensor 111 %init = linalg.init_tensor [%d0, %d1] : tensor<?x?xf32> 129 // CHECK-TILE: %[[INIT:.*]] = linalg.init_tensor 149 // CHECK-POINT: %[[INIT:.*]] = linalg.init_tensor [all …]
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H A D | fusion.mlir | 14 // CHECK-DAG: %[[INIT:.*]] = linalg.init_tensor [%[[S0]], %[[S1]], %[[S2]]] 43 %dst = linalg.init_tensor [%d0, %d1, %d2] : tensor<?x?x?xf32> 82 %dst = linalg.init_tensor [%d0, %d1, %d2] : tensor<?x?x?xf32> 196 %init = linalg.init_tensor [%dim_0, %concat_dim_abc] : tensor<?x?xi32> 214 // CHECK-DAG: %[[INIT:.*]] = linalg.init_tensor [32, 32] 227 %init = linalg.init_tensor [32, 32] : tensor<32x32xf32> 250 // CHECK: %[[INIT:.*]] = linalg.init_tensor [32, 32] 263 // CHECK: %[[INIT:.*]] = linalg.init_tensor [%[[D0]], %[[D1]]] 268 %init0 = linalg.init_tensor [32, 32] : tensor<32x32xf32> 282 %init1 = linalg.init_tensor [%d0, %d1] : tensor<?x?xf32> [all …]
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H A D | legacy_peeling.mlir | 13 // CHECK-TILE-2: %[[init_tensor:.*]] = linalg.init_tensor 19 // CHECK-TILE-2-SAME: outs (%[[loop_out1:.*]] = %[[init_tensor]]: tensor<?x?x?xf32>) { 92 %output = linalg.init_tensor [%dim0, %dim1, %dim2] : tensor<?x?x?xf32> 186 %output = linalg.init_tensor [%dim0, %dim1, %dim2] : tensor<?x?x?xf32> 219 %output = linalg.init_tensor [%dim0, %dim1, %dim2] : tensor<?x?x?xf32>
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H A D | tiling.mlir | 15 %init = linalg.init_tensor [%d0, %d1] : tensor<?x?xf32> 38 // CHECK-TILE: %[[INIT:.*]] = linalg.init_tensor [%[[GENERIC_D0]], %[[GENERIC_D1]]] 79 // CHECK-POINT: %[[INIT:.*]] = linalg.init_tensor [%[[GENERIC_D0]], %[[GENERIC_D1]]]
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H A D | legacy_tiling.mlir | 57 %3 = linalg.init_tensor [%0, %1, %2] : tensor<?x?x?xf32> 81 // CHECK: %[[INIT:.*]] = linalg.init_tensor
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H A D | nested_tiling.mlir | 13 // CHECK-PERFECT: %[[INIT:.*]] = linalg.init_tensor [64, 32] 42 // CHECK-IMPERFECT: %[[INIT:.*]] = linalg.init_tensor [64, 32]
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/tests/Dialect/mhlo/ |
H A D | hlo-legalize-to-linalg.mlir | 455 // CHECK: linalg.init_tensor [2, 2] : tensor<2x2xi1> 470 // CHECK: linalg.init_tensor [2, 2] : tensor<2x2xi1> 485 // CHECK: linalg.init_tensor [2, 2] : tensor<2x2xi1> 500 // CHECK: linalg.init_tensor [2] : tensor<2xi1> 515 // CHECK: linalg.init_tensor [2] : tensor<2xi1> 604 // CHECK: linalg.init_tensor [2, 2] : tensor<2x2xf32> 622 // CHECK-DAG: %[[DST:.*]] = linalg.init_tensor [2, %[[DIM]]] 642 // CHECK: linalg.init_tensor [4, 2, 1] : tensor<4x2x1xf32> 658 // CHECK: %{{.*}} = linalg.init_tensor [4, 2, 1, 4, %[[DIM]], 16] 674 // CHECK: linalg.init_tensor [7, 10, 6, 4, 5] : tensor<7x10x6x4x5xf32> [all …]
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H A D | legalize-mhlo-to-thlo.mlir | 12 …// CHECK-DAG: %[[INIT:.*]] = linalg.init_tensor [%[[SHAPE_D0]], %[[SHAPE_D1]], %[[SHAPE_D2]]] : te… 49 …// CHECK-DAG: %[[INIT:.*]] = linalg.init_tensor [%[[SHAPE_D0]], %[[SHAPE_D1]], %[[SHAPE_D2]], %[[S… 74 // CHECK-DAG: %[[INIT:.*]] = linalg.init_tensor [%[[D0]], %[[CONCAT_DIM_ABC]]] 91 // CHECK-DAG: %[[INIT:.*]] = linalg.init_tensor [64, %[[CONCAT_DIM_SUM]]] 117 // CHECK: %[[INIT:.*]] = linalg.init_tensor [3] : tensor<3xf32>
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/mlir/tfrt/tests/jit/ |
H A D | tf_jitrt_tile_reduction.mlir | 11 %init = linalg.init_tensor [%0] : tensor<?xf32> 37 // CHECK: %[[INIT:.*]] = linalg.init_tensor [%[[DIM_0]]] : [[TY_1D:.*]] 69 %init = linalg.init_tensor [8] : tensor<8xf32> 94 %init = linalg.init_tensor [%0] : tensor<?xf32> 117 // CHECK: %[[INIT:.*]] = linalg.init_tensor [%[[DIM_0]]] : [[TY_1D:.*]] 148 %init = linalg.init_tensor [%0, %1] : tensor<?x?xf32> 171 %init = linalg.init_tensor [] : tensor<f32> 194 // CHECK: %[[INIT:.*]] = linalg.init_tensor [] : tensor<f32> 198 // CHECK: %[[TMP_INIT:.*]] = linalg.init_tensor [8] : tensor<8xf32>
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H A D | tf_jitrt_vectorize_tiled_ops.mlir | 63 %init = linalg.init_tensor [80] : tensor<80xf32> 124 %0 = linalg.init_tensor [] : tensor<f32> 126 %2 = linalg.init_tensor [8] : tensor<8xf32> 175 %1 = linalg.init_tensor [5] : tensor<5xf32> 190 // CHECK: %[[INIT_TENSOR:.*]] = linalg.init_tensor [5] : tensor<5xf32> 206 %1 = linalg.init_tensor [18] : tensor<18xf32> 223 %init = linalg.init_tensor [2, 1000] : tensor<2x1000xf32> 234 %init = linalg.init_tensor [128] : tensor<128xf32>
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H A D | symbolic_shape_optimization.mlir | 22 // CHECK: %[[OUT:.*]] = linalg.init_tensor [%[[D0]]] 55 // CHECK: %[[OUT:.*]] = linalg.init_tensor [%[[D0]], 512] 94 // CHECK: %[[OUT:.*]] = linalg.init_tensor [%[[D0]]] 129 // CHECK: %[[OUT0:.*]] = linalg.init_tensor [10, %[[D1]]] 140 // CHECK: %[[OUT1:.*]] = linalg.init_tensor [10, %[[D0]]] 181 // CHECK: %[[OUT0:.*]] = linalg.init_tensor [%[[D0]], %[[D1]], %[[D2]]] 191 // CHECK: %[[OUT1:.*]] = linalg.init_tensor [%[[D0]], %[[D1]], %[[D2]]]
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H A D | tf_jitrt_fuse_fill_into_tiled_reduction.mlir | 16 %1 = linalg.init_tensor [%0] : tensor<?xf32> 62 // CHECK: %[[INIT:.*]] = linalg.init_tensor [%[[DIM_0]]] : [[TY_1D:.*]] 63 // CHECK: %[[INIT_TILE:.*]] = linalg.init_tensor [4] : tensor<4xf32> 111 %0 = linalg.init_tensor [8] : tensor<8xf32> 153 %1 = linalg.init_tensor [%0] : tensor<?xf32> 193 // CHECK: %[[INIT:.*]] = linalg.init_tensor [%[[DIM_0]]] : [[TY_1D:.*]] 194 // CHECK: %[[INIT_TILE:.*]] = linalg.init_tensor [4] : tensor<4xf32>
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H A D | tf_jitrt_codegen_transpose_detection.mlir | 14 %2 = linalg.init_tensor [%1, %0] : tensor<?x?xf32> 40 %2 = linalg.init_tensor [%1, %0] : tensor<?x?xf32> 62 %2 = linalg.init_tensor [%1, %0] : tensor<?x?xf32>
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H A D | tf_jitrt_tile_cwise.mlir | 9 %init = linalg.init_tensor [%dim0, %dim1] : tensor<?x?xf32> 30 // CHECK: %[[INIT:.*]] = linalg.init_tensor {{\[}}%[[DIM0]], %[[DIM1]]]
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H A D | detensorize_linalg.mlir | 10 %init = linalg.init_tensor [100] : tensor<100xi1>
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H A D | tf_jitrt_peel_tiled_loops.mlir | 95 %1 = linalg.init_tensor [%dim_Y] : tensor<?xf32> 171 %1 = linalg.init_tensor [%dim_X] : tensor<?xf32>
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/aosp_15_r20/external/ComputeLibrary/examples/ |
H A D | neon_permute.cpp | 40 init_tensor(TensorShape(8U, 4U, 2U), tensor_nchw, DataType::U8, DataLayout::NCHW); in do_setup() 41 init_tensor(TensorShape(2U, 8U, 4U), tensor_nhwc, DataType::U8, DataLayout::NHWC); in do_setup() 42 init_tensor(TensorShape(8U, 4U, 2U), tensor_nchw_result, DataType::U8, DataLayout::NCHW); in do_setup() 107 void init_tensor(const TensorShape shape, Tensor &tensor, DataType type, DataLayout layout) in init_tensor() function in NeonPermuteExample
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H A D | cl_cache.cpp | 66 init_tensor(TensorShape(8U, 4U, 2U), tensor_nchw, DataType::U8, DataLayout::NCHW); in do_setup() 67 init_tensor(TensorShape(2U, 8U, 4U), tensor_nhwc, DataType::U8, DataLayout::NHWC); in do_setup() 68 init_tensor(TensorShape(8U, 4U, 2U), tensor_nchw_result, DataType::U8, DataLayout::NCHW); in do_setup() 136 void init_tensor(const TensorShape shape, CLTensor &tensor, DataType type, DataLayout layout) in init_tensor() function in CLCacheExample
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H A D | neon_sgemm.cpp | 67 npy0.init_tensor(src0, DataType::F32); in do_setup() 69 npy1.init_tensor(src1, DataType::F32); in do_setup() 79 npy2.init_tensor(src2, DataType::F32); in do_setup()
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H A D | cl_sgemm.cpp | 74 npy0.init_tensor(src0, DataType::F32); in do_setup() 76 npy1.init_tensor(src1, DataType::F32); in do_setup() 86 npy2.init_tensor(src2, DataType::F32); in do_setup()
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/aosp_15_r20/external/tensorflow/tensorflow/python/ops/ |
H A D | op_selector.py | 374 def map_subgraph(init_tensor, sources, disallowed_placeholders, visited_ops, argument 399 ops_to_visit = [_as_operation(init_tensor)] 419 (repr(init_tensor), repr(op), show_path(op, init_tensor, sources)))
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/aosp_15_r20/external/tensorflow/tensorflow/python/eager/ |
H A D | lift_to_graph.py | 251 for init_tensor in init_tensors: 253 init_tensor=init_tensor,
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/aosp_15_r20/external/libaom/av1/encoder/ |
H A D | cnn.c | 45 static void init_tensor(TENSOR *tensor) { memset(tensor, 0, sizeof(*tensor)); } in init_tensor() function 126 init_tensor(&t); in concat_tensor() 919 init_tensor(&tensor1[b]); in av1_cnn_predict_c() 920 init_tensor(&tensor2[b]); in av1_cnn_predict_c()
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/aosp_15_r20/external/ComputeLibrary/utils/ |
H A D | Utils.h | 336 void init_tensor(T &tensor, arm_compute::DataType dt) in init_tensor() function
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