/external/eigen/Eigen/src/Householder/ |
H A D | BlockHouseholder.h | 22 // void make_block_householder_triangular_factor(TriangularFactorType& triFactor, const VectorsType& vectors, const CoeffsType& hCoeffs) 25 // const Index nbVecs = vectors.cols(); 26 // eigen_assert(triFactor.rows() == nbVecs && triFactor.cols() == nbVecs && vectors.rows()>=nbVecs); 30 // Index rs = vectors.rows() - i; 31 // // Warning, note that hCoeffs may alias with vectors. 32 // // It is then necessary to copy it before modifying vectors(i,i). 35 // Scalar *Vii_ptr = const_cast<Scalar*>(vectors.data() + vectors.outerStride()*i + vectors.innerStride()*i); 38 // triFactor.col(i).head(i).noalias() = -h * vectors 51 make_block_householder_triangular_factor(TriangularFactorType& triFactor, const VectorsType& vectors, const CoeffsType& hCoeffs) argument 79 apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vectors, const CoeffsType& hCoeffs, bool forward) argument [all...] |
/external/syslinux/core/ |
H A D | bios.inc | 22 ; Interrupt vectors
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/external/skia/gm/ |
H A D | imagescalealigned.cpp | 17 const SkVector vectors[] = { { 1, 0 }, { 0, 1 } }; variable 19 for (size_t i = 0; i < SK_ARRAY_COUNT(vectors); ++i) { 22 set.fVector = vectors[i]; 23 set.fImages.push_back() = MakeImage(vectors[i], SK_ColorGREEN); 25 set.fImages.push_back() = MakeImage(vectors[i], SK_ColorRED); 27 set.fImages.push_back() = MakeImage(vectors[i], SK_ColorGREEN);
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/external/skqp/gm/ |
H A D | imagescalealigned.cpp | 17 const SkVector vectors[] = { { 1, 0 }, { 0, 1 } }; variable 19 for (size_t i = 0; i < SK_ARRAY_COUNT(vectors); ++i) { 22 set.fVector = vectors[i]; 23 set.fImages.push_back() = MakeImage(vectors[i], SK_ColorGREEN); 25 set.fImages.push_back() = MakeImage(vectors[i], SK_ColorRED); 27 set.fImages.push_back() = MakeImage(vectors[i], SK_ColorGREEN);
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/external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
H A D | vector_support_library.cc | 350 std::vector<llvm::Value*> vectors, llvm::Value* init_values) { 354 vectors.size() == x86_avx_vector_elements) { 355 return ComputeAvxOptimizedHorizontalSums(std::move(vectors), init_values); 359 std::transform(vectors.begin(), vectors.end(), std::back_inserter(result), 372 std::vector<llvm::Value*> vectors, llvm::Value* init_values) { 373 while (vectors.size() != 2) { 375 for (int i = 0; i < vectors.size(); i += 2) { 376 new_vectors.push_back(AvxStyleHorizontalAdd(vectors[i], vectors[ 349 ComputeHorizontalSums( std::vector<llvm::Value*> vectors, llvm::Value* init_values) argument 371 ComputeAvxOptimizedHorizontalSums( std::vector<llvm::Value*> vectors, llvm::Value* init_values) argument [all...] |
H A D | vector_support_library.h | 206 // Compute the horizontal sum of each vector in `vectors`. The i'th element 208 // `vectors`. If `init_values` is not nullptr then the value in the i'th lane 211 std::vector<llvm::Value*> vectors, llvm::Value* init_values = nullptr); 259 std::vector<llvm::Value*> vectors, llvm::Value* init_values);
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/external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
H A D | gmm_ops_test.py | 60 vectors = [] 64 vectors.append([np.random.normal(2.0, 0.6), np.random.normal(2.0, 0.9)]) 67 vectors.append( 70 return np.asarray(vectors), classes 83 vectors = [] 87 vectors.append([ 93 return np.asarray(vectors), len(centers)
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/external/mesa3d/src/mesa/main/ |
H A D | uniform_query.cpp | 567 const unsigned vectors = MAX2(1, uni->type->matrix_columns); local 579 store->element_stride - (vectors * store->vector_stride); 581 (uint8_t *) (&uni->storage[array_index * (dmul * components * vectors)].i); 584 printf("%s: %p[%d] components=%u vectors=%u count=%u vector_stride=%u " 587 vectors, count, store->vector_stride, extra_stride); 600 memcpy(dst, src, src_vector_byte_stride * vectors); 601 src += src_vector_byte_stride * vectors; 602 dst += store->vector_stride * vectors; 608 memcpy(dst, src, src_vector_byte_stride * vectors * count); 609 src += src_vector_byte_stride * vectors * coun 919 unsigned vectors; local [all...] |
/external/v8/src/debug/ |
H A D | debug-coverage.cc | 66 // Feedback vectors are already listed to prevent losing them to GC. 78 // Iterate the heap to find all feedback vectors and accumulate the 145 // Collect existing feedback vectors. 146 std::vector<Handle<FeedbackVector>> vectors; local 155 vectors.emplace_back(vector, isolate); 158 // Add collected feedback vectors to the root list lest we lose them to GC. 160 ArrayList::New(isolate, static_cast<int>(vectors.size())); 161 for (const auto& vector : vectors) list = ArrayList::Add(list, vector);
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/external/mesa3d/src/mesa/drivers/dri/r200/ |
H A D | r200_sanity.c | 614 static struct reg vectors[512*4+1]; variable in typeref:struct:reg 636 for (i = 0, tmp = vector_names ; i < ARRAY_SIZE(vectors) ; i++) { 638 vectors[i].idx = i; 639 vectors[i].closest = tmp; 640 vectors[i].flags = ISFLOAT|ISVEC; 645 vectors[ARRAY_SIZE(vectors)-1].idx = -1; 795 for (i = 0 ; i < ARRAY_SIZE(vectors) ; i++) 796 print_reg( &vectors[i] ); 903 int sz = header.vectors [all...] |
H A D | r200_state_init.c | 174 h.vectors.cmd_type = RADEON_CMD_VECTORS; 175 h.vectors.offset = offset; 176 h.vectors.stride = stride; 177 h.vectors.count = count; 283 OUT_BATCH(h.vectors.offset | (h.vectors.stride << RADEON_VEC_INDX_OCTWORD_STRIDE_SHIFT)); \ 284 OUT_BATCH(CP_PACKET0_ONE(R200_SE_TCL_VECTOR_DATA_REG, h.vectors.count - 1)); \ 285 OUT_BATCH_TABLE((data), h.vectors.count); \
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/external/mesa3d/src/mesa/drivers/dri/radeon/ |
H A D | radeon_sanity.c | 336 static struct reg vectors[512*4+1]; variable in typeref:struct:reg 358 for (i = 0, tmp = vector_names ; i < ARRAY_SIZE(vectors) ; i++) { 360 vectors[i].idx = i; 361 vectors[i].closest = tmp; 362 vectors[i].flags = ISFLOAT|ISVEC; 367 vectors[ARRAY_SIZE(vectors)-1].idx = -1; 517 for (i = 0 ; i < ARRAY_SIZE(vectors) ; i++) 518 print_reg( &vectors[i] ); 625 int sz = header.vectors [all...] |
H A D | radeon_state_init.c | 170 h.vectors.cmd_type = RADEON_CMD_VECTORS; 171 h.vectors.offset = offset; 172 h.vectors.stride = stride; 173 h.vectors.count = count; 246 OUT_BATCH(h.vectors.offset | (h.vectors.stride << RADEON_VEC_INDX_OCTWORD_STRIDE_SHIFT)); \ 247 OUT_BATCH(CP_PACKET0_ONE(R200_SE_TCL_VECTOR_DATA_REG, h.vectors.count - 1)); \ 248 OUT_BATCH_TABLE((data), h.vectors.count); \
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/external/mmc-utils/3rdparty/hmac_sha/ |
H A D | sha2.c | 856 static const char *vectors[4][3] = local 907 printf("SHA-224 Test vectors\n"); 910 test(vectors[0][0], digest, SHA224_DIGEST_SIZE); 912 test(vectors[0][1], digest, SHA224_DIGEST_SIZE); 914 test(vectors[0][2], digest, SHA224_DIGEST_SIZE); 917 printf("SHA-256 Test vectors\n"); 920 test(vectors[1][0], digest, SHA256_DIGEST_SIZE); 922 test(vectors[1][1], digest, SHA256_DIGEST_SIZE); 924 test(vectors[1][2], digest, SHA256_DIGEST_SIZE); 927 printf("SHA-384 Test vectors\ [all...] |
H A D | hmac_sha2.c | 414 static const char *vectors[] = local 530 test(vectors[i], mac, mac_224_size); 533 test(vectors[7 + i], mac, mac_256_size); 536 test(vectors[14 + i], mac, mac_384_size); 539 test(vectors[21 + i], mac, mac_512_size);
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/external/ImageMagick/MagickCore/ |
H A D | matrix.c | 306 % This used to generate the two dimensional matrix, and vectors required 439 % double **vectors,const size_t rank,const size_t number_vectors) 445 % o vectors: the additional matrix argumenting the matrix for row reduction. 446 % Producing an 'array of column vectors'. 451 % o number_vectors: Number of vectors columns, argumenting the above matrix. 459 % However 'vectors' is a 'array of column pointers' which can have any number 465 % For example, the 'vectors' can consist of a pointer to a simple array of 484 % You can also use the 'vectors' to generate an inverse of the given 'matrix' 490 double **vectors,const size_t rank,const size_t number_vectors) 563 GaussJordanSwap(vectors[ 483 GaussJordanElimination(double **matrix, double **vectors,const size_t rank,const size_t number_vectors) argument 832 LeastSquaresAddTerms(double **matrix,double **vectors, const double *terms,const double *results,const size_t rank, const size_t number_vectors) argument [all...] |
H A D | distort.c | 545 **vectors, 551 /* create matrix, and a fake vectors matrix */ 553 vectors = (double **) AcquireQuantumMemory(number_values,sizeof(*vectors)); 554 if (matrix == (double **) NULL || vectors == (double **) NULL) 557 vectors = (double **) RelinquishMagickMemory(vectors); 564 /* fake a number_values x3 vectors matrix from coefficients array */ 566 vectors[i] = &(coeff[i*3]); 572 LeastSquaresAddTerms(matrix,vectors,term 541 **vectors, local 778 *vectors[1], local 897 **vectors, local 1035 **vectors, local [all...] |
/external/antlr/antlr-3.4/tool/src/main/resources/org/antlr/codegen/templates/C/ |
H A D | AST.stg | 35 pANTLR3_VECTOR_FACTORY vectors; 46 ctx->vectors = antlr3VectorFactoryNew(0); 50 ctx->vectors->close(ctx->vectors); 207 list_<label>=ctx->vectors->newVector(ctx->vectors); 230 list_<label>=ctx->vectors->newVector(ctx->vectors);
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/external/curl/packages/vms/ |
H A D | generate_vax_transfer.com | 5 $! File to generate and compile the VAX transfer vectors from reading in the 82 $ write vopt ";", tab, "Exact case and upper case transfer vectors" 103 $ "This procedure can only handle procedure vectors" 105 "Data vectors require manual construction for which this procedure or" 210 ; VAX transfer vectors 217 ; There are three sets of symbols for transfer vectors here. 220 ; VAX transfer vectors. 227 ; case transfer vectors, with exact case entry symbols. 230 ; vectors for both upper and exact case, and then additional entry points
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/external/webrtc/tools/matlab/ |
H A D | rtpAnalyze.m | 36 % streams from the data vectors. If there is only one stream, the 37 % vectors are good to use as they are. 53 % This is where the data vectors are trimmed. 180 %IMPORTFILE Import numeric data from a text file as column vectors.
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/external/compiler-rt/test/builtins/Unit/ |
H A D | comparedf2_test.c | 145 static const struct TestVector vectors[] = { variable in typeref:struct:TestVector 473 const int numVectors = sizeof vectors / sizeof vectors[0]; 476 if (test__cmpdf2(&vectors[i])) return 1;
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/external/tensorflow/tensorflow/contrib/kfac/python/kernel_tests/ |
H A D | loss_functions_test.py | 125 vectors = [vector, vector.reshape(1, -1), np.stack([vector] * 4)] 130 for vector in vectors:
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/external/skia/tests/ |
H A D | MatrixTest.cpp | 270 // test a bunch of vectors. All should be scaled by between minScale and maxScale 275 SkVector vectors[1000]; local 276 for (size_t i = 0; i < SK_ARRAY_COUNT(vectors); ++i) { 277 vectors[i].fX = rand.nextSScalar1(); 278 vectors[i].fY = rand.nextSScalar1(); 279 if (!vectors[i].normalize()) { 284 mat.mapVectors(vectors, SK_ARRAY_COUNT(vectors)); 285 for (size_t i = 0; i < SK_ARRAY_COUNT(vectors); ++i) { 286 SkScalar d = vectors[ [all...] |
/external/skqp/tests/ |
H A D | MatrixTest.cpp | 270 // test a bunch of vectors. All should be scaled by between minScale and maxScale 275 SkVector vectors[1000]; local 276 for (size_t i = 0; i < SK_ARRAY_COUNT(vectors); ++i) { 277 vectors[i].fX = rand.nextSScalar1(); 278 vectors[i].fY = rand.nextSScalar1(); 279 if (!vectors[i].normalize()) { 284 mat.mapVectors(vectors, SK_ARRAY_COUNT(vectors)); 285 for (size_t i = 0; i < SK_ARRAY_COUNT(vectors); ++i) { 286 SkScalar d = vectors[ [all...] |
/external/libvpx/libvpx/vp9/encoder/x86/ |
H A D | vp9_error_sse2.asm | 73 ; Compute the sum of squared difference between two tran_low_t vectors.
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