/frameworks/opt/gamesdk/third_party/protobuf-3.0.0/java/compatibility_tests/v2.5.0/ |
D | test.sh | 26 3.0.0-beta-1) 27 OLD_VERSION=3.0.0-beta-1 28 …=http://repo1.maven.org/maven2/com/google/protobuf/protoc/3.0.0-beta-1/protoc-3.0.0-beta-1-linux-x… 30 3.0.0-beta-2) 31 OLD_VERSION=3.0.0-beta-2 32 …=http://repo1.maven.org/maven2/com/google/protobuf/protoc/3.0.0-beta-2/protoc-3.0.0-beta-2-linux-x… 34 3.0.0-beta-3) 35 OLD_VERSION=3.0.0-beta-3 36 …=http://repo1.maven.org/maven2/com/google/protobuf/protoc/3.0.0-beta-3/protoc-3.0.0-beta-3-linux-x… 38 3.0.0-beta-4) [all …]
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/frameworks/rs/cpu_ref/ |
D | rsCpuBLASDispatch.h | 27 const float *X, const int incX, const float beta, 33 const int incX, const float beta, float *Y, const int incY); 60 const double *X, const int incX, const double beta, 66 const int incX, const double beta, double *Y, const int incY); 93 const void *X, const int incX, const void *beta, 99 const int incX, const void *beta, void *Y, const int incY); 126 const void *X, const int incX, const void *beta, 132 const int incX, const void *beta, void *Y, const int incY); 163 const float beta, float *Y, const int incY); 167 const float beta, float *Y, const int incY); [all …]
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D | rsCpuIntrinsicBLAS.cpp | 144 static void walk_tiled_gemm(Func blasFunc, T_param alpha, T_param beta, int vecSize, in walk_tiled_gemm() argument 186 (T_data *)B + nStart * nStride * vecSize, ldb, beta, in walk_tiled_gemm() 197 float beta = call->beta.f; in walk_2d_sgemm() local 199 walk_tiled_gemm<float, float, FnPtr_cblas_sgemm>(cblas_sgemm, alpha, beta, 1, call, mtls); in walk_2d_sgemm() 208 double beta = call->beta.d; in walk_2d_dgemm() local 210 walk_tiled_gemm<double, double, FnPtr_cblas_dgemm>(cblas_dgemm, alpha, beta, 1, call, mtls); in walk_2d_dgemm() 219 void * beta = (void *)&call->beta.c; in walk_2d_cgemm() local 221 walk_tiled_gemm<float, void *, FnPtr_cblas_cgemm>(cblas_cgemm, alpha, beta, 2, call, mtls); in walk_2d_cgemm() 230 void * beta = (void *)&call->beta.z; in walk_2d_zgemm() local 232 walk_tiled_gemm<double, void *, FnPtr_cblas_zgemm>(cblas_zgemm, alpha, beta, 2, call, mtls); in walk_2d_zgemm() [all …]
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/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | log_softmax.mod.py | 19 def test(input0, output0, input_data, beta, axis, output_data): argument 20 model = Model().Operation("LOG_SOFTMAX", input0, beta, axis).To(output0) 31 beta=1.0, 44 beta=1.0, 57 beta=1.0, 68 beta=10.0,
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/frameworks/ml/nn/common/operations/ |
D | Normalization.cpp | 30 int32_t radius, float bias, float alpha, float beta, in localResponseNormFloat32Impl() argument 51 float multiplier = std::pow(bias + alpha * sum, -beta); in localResponseNormFloat32Impl() 60 float bias, float alpha, float beta, int32_t axis, in localResponseNormFloat16() argument 67 localResponseNormFloat32(inputDataFloat32.data(), inputShape, radius, bias, alpha, beta, axis, in localResponseNormFloat16() 75 float bias, float alpha, float beta, int32_t axis, float* outputData, in localResponseNormFloat32() argument 83 .range = radius, .bias = bias, .alpha = alpha, .beta = beta}; in localResponseNormFloat32() 89 return localResponseNormFloat32Impl(inputData, inputShape, radius, bias, alpha, beta, axis, in localResponseNormFloat32()
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D | Softmax.cpp | 42 inline bool softmaxSlowFloat32(const float* inputData, const Shape& inputShape, const float beta, in softmaxSlowFloat32() argument 62 sum += std::exp((*p - maxValue) * beta); in softmaxSlowFloat32() 67 *pOut = std::exp((*p - maxValue) * beta) / sum; in softmaxSlowFloat32() 74 bool softmaxFloat32(const float* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxFloat32() argument 81 tflite::SoftmaxParams param = {.beta = beta}; in softmaxFloat32() 86 return softmaxSlowFloat32(inputData, inputShape, beta, axis, outputData, outputShape); in softmaxFloat32() 90 bool softmaxFloat16(const _Float16* inputData, const Shape& inputShape, const float beta, in softmaxFloat16() argument 97 softmaxFloat32(inputData_float32.data(), inputShape, beta, axis, outputData_float32.data(), in softmaxFloat16() 104 bool softmaxQuant8Impl(const uint8_t* inputData, const Shape& inputShape, const float beta, in softmaxQuant8Impl() argument 186 bool softmaxQuant8(const uint8_t* inputData, const Shape& inputShape, const float beta, in softmaxQuant8() argument [all …]
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/frameworks/ml/nn/runtime/test/generated/models/ |
D | softmax_float_1_relaxed.model.cpp | 8 auto beta = model->addOperand(&type1); in CreateModel() local 12 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 13 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel() 34 auto beta = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 38 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 39 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | softmax_float_1.model.cpp | 8 auto beta = model->addOperand(&type1); in CreateModel() local 12 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 13 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel() 32 auto beta = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 36 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 37 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | softmax_quant8_2.model.cpp | 9 auto beta = model->addOperand(&type1); in CreateModel() local 13 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 14 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel() 33 auto beta = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 37 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 38 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | softmax_quant8_1.model.cpp | 9 auto beta = model->addOperand(&type1); in CreateModel() local 13 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 14 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel() 33 auto beta = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 37 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 38 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | softmax_float_2.model.cpp | 8 auto beta = model->addOperand(&type1); in CreateModel() local 12 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 13 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel() 32 auto beta = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 36 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 37 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | softmax_float_2_relaxed.model.cpp | 8 auto beta = model->addOperand(&type1); in CreateModel() local 12 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 13 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel() 34 auto beta = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 38 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 39 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_3.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 46 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 56 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 57 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_1.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 46 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 56 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 57 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_4.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 46 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 56 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 57 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_4_relaxed.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 48 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 58 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 59 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_2_relaxed.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 48 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 58 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 59 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_2.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 46 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 56 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 57 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_3_relaxed.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 48 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 58 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 59 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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D | local_response_norm_float_1_relaxed.model.cpp | 12 auto beta = model->addOperand(&type2); in CreateModel() local 22 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel() 23 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel() 48 auto beta = model->addOperand(&type2); in CreateModel_dynamic_output_shape() local 58 model->setOperandValue(beta, beta_init, sizeof(float) * 1); in CreateModel_dynamic_output_shape() 59 …ration(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); in CreateModel_dynamic_output_shape()
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/frameworks/rs/cpp/ |
D | ScriptIntrinsicBLAS.cpp | 73 call.beta.f = betaF; in setUpBLASCall() 78 call.beta.d = betaD; in setUpBLASCall() 84 call.beta.c.r = betaCX; in setUpBLASCall() 85 call.beta.c.i = betaCY; in setUpBLASCall() 91 call.beta.z.r = betaZX; in setUpBLASCall() 92 call.beta.z.i = betaZY; in setUpBLASCall() 110 float beta, RsAllocation C, int incX, int incY, int KL, int KU) { in nScriptIntrinsicBLAS_Single() argument 112 M, N, K, incX, incY, KL, KU, alpha, beta, 0.0, 0.0, in nScriptIntrinsicBLAS_Single() 124 double beta, RsAllocation C, int incX, int incY, int KL, int KU) { in nScriptIntrinsicBLAS_Double() argument 126 M, N, K, incX, incY, KL, KU, 0.0f, 0.0f, alpha, beta, in nScriptIntrinsicBLAS_Double() [all …]
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D | rsCppStructs.h | 1851 float beta, const sp<Allocation>& Y, int incY); 1870 double beta, const sp<Allocation>& Y, int incY); 1889 Float2 beta, const sp<Allocation>& Y, int incY); 1908 Double2 beta, const sp<Allocation>& Y, int incY); 1936 float beta, const sp<Allocation>& Y, int incY); 1964 int incX, double beta, const sp<Allocation>& Y, int incY); 1992 int incX, Float2 beta, const sp<Allocation>& Y, int incY); 2020 Double2 beta, const sp<Allocation>& Y, int incY); 2550 int incX, float beta, const sp<Allocation>& Y, int incY); 2576 int incX, float beta, const sp<Allocation>& Y, int incY); [all …]
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/frameworks/base/rs/java/android/renderscript/ |
D | ScriptIntrinsicBLAS.java | 320 …pose int TransA, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int … in SGEMV() argument 324 …as_sgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX… in SGEMV() local 342 …se int TransA, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int … in DGEMV() argument 346 …as_dgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX… in DGEMV() local 364 …se int TransA, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int … in CGEMV() argument 368 …A, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS)… in CGEMV() 386 … int TransA, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int … in ZGEMV() argument 390 …A, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, A.getID(mRS), X.getID(mRS), beta.x, beta.y, Y.getID(mRS)… in ZGEMV() 417 … int KL, int KU, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int … in SGBMV() argument 425 …as_sgbmv, TransA, 0, 0, 0, 0, M, N, 0, alpha, A.getID(mRS), X.getID(mRS), beta, Y.getID(mRS), incX… in SGBMV() local [all …]
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/frameworks/av/tools/resampler_tools/ |
D | fir.cpp | 61 static double kaiser(int k, int N, double beta) { in kaiser() argument 64 return I0(beta * sqrt(1.0 - sqr((2.0*k)/N - 1.0))) / I0(beta); in kaiser() 135 double beta = 7.865; in main() local 208 beta = atof(optarg); in main() 260 double y = kaiser(ix+N, 2*N, beta) * sinc(x) * 2.0 * Fcr; in main() 291 double y = kaiser(i+N, 2*N, beta) * sinc(x) * 2.0 * Fcr;; in main()
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/frameworks/rs/support/java/src/androidx/renderscript/ |
D | ScriptIntrinsicBLAS.java | 327 …pose int TransA, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int … in SGEMV() argument 341 …e(getID(mRS), RsBlas_sgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha, aID, xID, beta, yID, incX, incY, 0… in SGEMV() local 359 …se int TransA, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int … in DGEMV() argument 373 …e(getID(mRS), RsBlas_dgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha, aID, xID, beta, yID, incX, incY, 0… in DGEMV() local 391 …se int TransA, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int … in CGEMV() argument 405 …sBlas_cgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, aID, xID, beta.x, beta.y, yID, incX, i… in CGEMV() 423 … int TransA, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int … in ZGEMV() argument 437 …sBlas_zgemv, TransA, 0, 0, 0, 0, M, N, 0, alpha.x, alpha.y, aID, xID, beta.x, beta.y, yID, incX, i… in ZGEMV() 464 … int KL, int KU, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int … in SGBMV() argument 482 …e(getID(mRS), RsBlas_sgbmv, TransA, 0, 0, 0, 0, M, N, 0, alpha, aID, xID, beta, yID, incX, incY, K… in SGBMV() local [all …]
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