operators (full) in projects: aosp_15_r20

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/aosp_15_r20/prebuilts/tools/common/m2/repository/io/reactivex/rxjava2/rxjava/2.2.9/
H D	rxjava-2.2.9-sources.jar	`META-INF/ META-INF/MANIFEST.MF io/ io/reactivex/ io/ ...`
H D	rxjava-2.2.9.jar	`META-INF/ META-INF/MANIFEST.MF io/ io/reactivex/ io/ ...`
/aosp_15_r20/external/tensorflow/tensorflow/python/ops/linalg/
H A D	linear_operator_composition.py	35 This operator composes one or more linear operators `[op1,...,opJ]`, 51 the defining operators' methods. 54 # Create a 2 x 2 linear operator composed of two 2 x 2 operators. 73 # Create a [2, 3] batch of 4 x 5 linear operators. 77 # Create a [2, 3] batch of 5 x 6 linear operators. 81 # Compose to create a [2, 3] batch of 4 x 6 operators. 93 the sum of the individual operators' operations. 112 operators, argument 120 `LinearOperatorComposition` is initialized with a list of operators 126 operators: Iterable of `LinearOperator` objects, each with [all …]
H A D	linear_operator_kronecker.py	65 This operator composes one or more linear operators `[op1,...,opJ]`, 72 where the product is over all operators. 75 # Create a 4 x 4 linear operator composed of two 2 x 2 operators. 96 # Create a [2, 3] batch of 4 x 5 linear operators. 100 # Create a [2, 3] batch of 5 x 6 linear operators. 104 # Compose to create a [2, 3] batch of 20 x 30 operators. 116 the sum of the individual operators' operations. 134 operators, argument 142 `LinearOperatorKronecker` is initialized with a list of operators 146 operators: Iterable of `LinearOperator` objects, each with [all …]
H A D	linear_operator_block_diag.py	37 This operator combines one or more linear operators `[op1,...,opJ]`, 66 # Create a 4 x 4 linear operator combined of two 2 x 2 operators. 106 # Create a [2, 3] batch of 4 x 4 linear operators. 110 # Create a [1, 3] batch of 5 x 5 linear operators. 114 # Combine to create a [2, 3] batch of 9 x 9 operators. 131 the sum of the individual operators' operations. 150 operators, argument 158 `LinearOperatorBlockDiag` is initialized with a list of operators 162 operators: Iterable of `LinearOperator` objects, each with 175 operators names joined with `_o_`. [all …]
H A D	linear_operator_block_lower_triangular.py	40 This operator is initialized with a nested list of linear operators, which 71 operators' methods. 74 operators: 125 Create a [2, 3] batch of 4 x 4 linear operators: 129 Create a [1, 3] batch of 5 x 4 linear operators: 133 Create a [1, 3] batch of 5 x 5 linear operators: 137 Combine to create a [2, 3] batch of 9 x 9 operators: 163 operators is `N = D * (D + 1) // 2`. 166 complexities of the individual operators. 168 of the operators on the diagonal and the `matmul` complexities of the [all …]
H A D	linear_operator_addition.py	32 def add_operators(operators, argument 36 """Efficiently add one or more linear operators. 38 Given operators `[A1, A2,...]`, this `Op` returns a possibly shorter list of 39 operators `[B1, B2,...]` such that 43 The operators `Bk` result by adding some of the `Ak`, as allowed by 46 Example of efficient adding of diagonal operators. 75 operators: Iterable of `LinearOperator` objects with same `dtype`, domain 89 ValueError: If `operators` argument is empty. 97 check_ops.assert_proper_iterable(operators) 98 operators = list(reversed(operators)) [all …]
/aosp_15_r20/external/pytorch/test/
H A D	test_namedtuple_return_api.py	65 'operators are allowed to have named ' 78 op = namedtuple('op', ['operators', 'input', 'names', 'hasout']) 79 operators = [ 80 …op(operators=['max', 'min', 'median', 'nanmedian', 'mode', 'sort', 'topk', 'cummax', 'cummin'], in… 82 op(operators=['kthvalue'], input=(1, 0), 84 op(operators=['svd'], input=(), names=('U', 'S', 'V'), hasout=True), 85 … op(operators=['linalg_svd', '_linalg_svd'], input=(), names=('U', 'S', 'Vh'), hasout=True), 86 … op(operators=['slogdet', 'linalg_slogdet'], input=(), names=('sign', 'logabsdet'), hasout=True), 87 …op(operators=['_linalg_slogdet'], input=(), names=('sign', 'logabsdet', 'LU', 'pivots'), hasout=Tr… 88 op(operators=['qr', 'linalg_qr'], input=(), names=('Q', 'R'), hasout=True), [all …]
/aosp_15_r20/external/executorch/docs/source/
H A D	ir-ops-set-definition.md	5 The list of operators that have been identified as a Core ATen operator can be found on the [IRs pa… 9 …operators is the [ATen library](https://pytorch.org/cppdocs/#aten); outside of ATen operators, dev… 11 An “ATen operator set” or “ATen opset” is the set of ATen operators that can be used to represent a… 15 …operators (i.e. operators that do not mutate or alias inputs). Therefore, `torch.export` produces … 19 …ions. This process will replace specified ATen operators with equivalent sequences of other ATen o… 21 …operators will be decomposed. ATen operators that are a part of the core ATen opset (i.e. core ATe… 23 …operators that need to be handled by PyTorch backends and compilers once a model is exported. Not … 27 …possible; the vast majority of use-cases will not want to decompose the operators contained within… 31 …operators created by surveying models in public GitHub repositories in addition to well-known open… 35 …itions of the operators; the decomposition should be a relatively straightforward re-expression of… [all …]
H A D	concepts.md	23 … consists of functional ATen operators, higher order operators (like control flow operators) and r… 36 …des only differentiable ATen operators, along with higher order operators (control flow ops) and r… 44 …contain operators or submodules that are only meaningful to the target backend. This dialect allow… 52 …operators that are not part of ATen dialect or Edge dialect. Backend specific operators are only i… 68 …ator information from models and/or other sources and only includes the operators required by them… 74 …dialect contains the core ATen operators along with higher order operators (control flow) and regi… 76 ## [Core ATen operators / Canonical ATen operator set](./ir-ops-set-definition.md) 78 A select subset of the PyTorch ATen operator library. Core ATen operators will not be decomposed wh… 82 …of other operators. During the AOT process, a default list of decompositions is employed, breaking… 86 …hese are operators that aren't part of the ATen library, but which appear in [eager mode](./concep… [all …]
H A D	build-run-xtensa.md	10 …operators and compiler passes to enhance the model and make it more suitable to running on Xtensa … 76 │ │ ├── operators 81 │ ├── operators 87 └── operators 92 …h/executorch/blob/main/backends/cadence/aot/quantizer.py), will replace operators with custom ones… 94 *Operators: 96 …operators folder contains two kinds of operators: existing operators from the [ExecuTorch portable… 115 Quantized Operators*: 117 The other, more complex model are custom operators, including: 118 …[here](https://github.com/pytorch/executorch/blob/main/examples/cadence/operators/quantized_linear… [all …]
/aosp_15_r20/external/tensorflow/tensorflow/python/autograph/operators/
H A D	__init__.py	15 """This module implements operators that AutoGraph overloads. 32 # All operators may accept a final argument named "opts", of a type that 36 from tensorflow.python.autograph.operators.conditional_expressions import if_exp 37 from tensorflow.python.autograph.operators.control_flow import for_stmt 38 from tensorflow.python.autograph.operators.control_flow import if_stmt 39 from tensorflow.python.autograph.operators.control_flow import while_stmt 40 from tensorflow.python.autograph.operators.data_structures import list_append 41 from tensorflow.python.autograph.operators.data_structures import list_pop 42 from tensorflow.python.autograph.operators.data_structures import list_stack 43 from tensorflow.python.autograph.operators.data_structures import ListPopOpts [all …]
/aosp_15_r20/external/pytorch/tools/code_analyzer/
H A D	gen_operators_yaml.py	24 # Generate YAML file containing the operators used for a specific PyTorch model. 39 # operators: 63 # 1. Inference Root Operators (--root-ops): Root operators (called directly 66 # 2. Training Root Operators (--training-root-ops): Root operators used 67 # by training use-cases. Currently, this list is the list of all operators 68 # used by training, and not just the root operators. All Training ops are 72 # operator dependency graph used to determine which operators depend on 73 # which other operators for correct functioning. This is used for 74 # generating the transitive closure of all the operators used by the 75 # model based on the root operators when static selective build is used. [all …]
/aosp_15_r20/external/pytorch/torchgen/selective_build/
H A D	selector.py	`27 # operators that should be included in the build. 32 # operators. 39 operators: dict[str, SelectiveBuildOperator] 80 "operators", 103 operators = {} 104 operators_dict = data.get("operators", {}) 108 operators[k] = SelectiveBuildOperator.from_yaml_dict(k, v) 134 operators, 157 operators = {} 159 operators[op] = { [all …]`
/aosp_15_r20/external/armnn/docs/
H A D	05_01_parsers.dox	29 ## ONNX operators that the Arm NN SDK supports 31 This reference guide provides a list of ONNX operators the Arm NN SDK currently supports. 33 The Arm NN SDK ONNX parser currently only supports fp32 operators. 38 …- See the ONNX [Add documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Add)… 41 …veragePool documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#AveragePool) … 44 …- See the ONNX [Concat documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#C… 47 …- See the ONNX [Constant documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md… 50 …- See the ONNX [Clip documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Cli… 53 …- See the ONNX [Flatten documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#… 56 …- See the ONNX [Gather documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#G… [all …]
/aosp_15_r20/external/tensorflow/tensorflow/lite/toco/tflite/
H A D	export_test.cc	42 void ResetOperators() { input_model_.operators.clear(); } in ResetOperators() 61 input_model_.operators.emplace_back(op); in AddOperatorsByName() 72 input_model_.operators.emplace_back(op); in AddOperatorsByName() 86 input_model_.operators.emplace_back(op); in AddOperatorsByName() 98 input_model_.operators.emplace_back(op); in AddOperatorsByName() 102 input_model_.operators.emplace_back(op); in AddOperatorsByName() 145 input_model_.operators.emplace_back(op); in BuildQuantizableTestModel() 157 input_model_.operators.emplace_back(op); in BuildQuantizableTestModel() 201 auto operators = (model->subgraphs())[0]->operators(); in ExportAndGetOperatorIndices() local 202 for (const auto op : *operators) { in ExportAndGetOperatorIndices() [all …]
H A D	import_test.cc	109 Offset<Vector<Offset<::tflite::Operator>>> operators, in BuildSubGraphs() argument 117 builder_.CreateVector(outputs), operators, in BuildSubGraphs() 125 // conversions multiple times, and the conversion of operators is tested by 131 auto operators = BuildOperators(); in BuildTestModel() local 132 auto subgraphs = BuildSubGraphs(tensors, operators); in BuildTestModel() 160 details::OperatorsTable operators; in TEST_F() local 161 details::LoadOperatorsTable(*input_model_, &operators); in TEST_F() 162 EXPECT_THAT(operators, ElementsAre("MAX_POOL_2D", "CONV_2D")); in TEST_F() 193 auto operators = BuildOperators(); in TEST_F() local 194 auto subgraphs = BuildSubGraphs(tensors, operators); in TEST_F() [all …]
/aosp_15_r20/external/ComputeLibrary/
H A D	Android.bp	`97 "src/c/operators/AclActivation.cpp", 463 "src/cpu/operators/CpuActivation.cpp", 464 "src/cpu/operators/CpuAdd.cpp", 465 "src/cpu/operators/CpuAddMulAdd.cpp", 466 "src/cpu/operators/CpuCast.cpp", 467 "src/cpu/operators/CpuConcatenate.cpp", 468 "src/cpu/operators/CpuConv2d.cpp", 469 "src/cpu/operators/CpuConvertFullyConnectedWeights.cpp", 470 "src/cpu/operators/CpuCopy.cpp", 471 "src/cpu/operators/CpuDepthwiseConv2d.cpp", [all …]`
H A D	filelist.json	`98 "operators": array 100 "src/c/operators/AclActivation.cpp" 149 "operators": { object 154 "src/gpu/cl/operators/ClActivation.cpp", 172 "src/gpu/cl/operators/ClAdd.cpp" 235 "src/gpu/cl/operators/ClCast.cpp", 265 "src/gpu/cl/operators/ClConcatenate.cpp", 294 "src/gpu/cl/operators/ClConv2d.cpp", 295 "src/gpu/cl/operators/ClDirectConv2d.cpp", 296 "src/gpu/cl/operators/ClGemmConv2d.cpp", [all …]`
/aosp_15_r20/external/tensorflow/tensorflow/lite/tools/optimize/
H A D	modify_model_interface_test.cc	75 model->subgraphs[0]->operators.push_back(std::move(quant_op)); in CreateQuantizedModelSingleInputOutput() 76 model->subgraphs[0]->operators.push_back(std::move(fc_op)); in CreateQuantizedModelSingleInputOutput() 77 model->subgraphs[0]->operators.push_back(std::move(dequant_op)); in CreateQuantizedModelSingleInputOutput() 178 model->subgraphs[0]->operators.push_back(std::move(quant_op_1)); in CreateQuantizedModelMultipleInputOutput() 179 model->subgraphs[0]->operators.push_back(std::move(quant_op_2)); in CreateQuantizedModelMultipleInputOutput() 180 model->subgraphs[0]->operators.push_back(std::move(fc_op)); in CreateQuantizedModelMultipleInputOutput() 181 model->subgraphs[0]->operators.push_back(std::move(dequant_op_1)); in CreateQuantizedModelMultipleInputOutput() 182 model->subgraphs[0]->operators.push_back(std::move(dequant_op_2)); in CreateQuantizedModelMultipleInputOutput() 281 model->subgraphs[0]->operators.push_back(std::move(fc_op)); in CreateFloatModel() 329 EXPECT_EQ(model->subgraphs[0]->operators.size(), 1); in TEST_P() [all …]
H A D	quantize_model_test.cc	127 // TODO(jianlijianli): Compare operators as well. in ExpectSameModels() 235 ASSERT_EQ(quantized_graph->operators.size(), in TEST_P() 236 float_graph->operators()->size()); in TEST_P() 237 for (size_t i = 0; i < quantized_graph->operators.size(); i++) { in TEST_P() 238 const auto quant_op = quantized_graph->operators[i].get(); in TEST_P() 239 const auto float_op = float_graph->operators()->Get(i); in TEST_P() 279 EXPECT_EQ(subgraph->operators.size(), in TEST_P() 280 readonly_subgraph->operators()->size() + 2); in TEST_P() 282 const auto& quant_op = subgraph->operators[0]; in TEST_P() 284 subgraph->operators[subgraph->operators.size() - 1]; in TEST_P() [all …]
/aosp_15_r20/external/jsilver/src/com/google/clearsilver/jsilver/functions/bundles/
H A D	CoreOperators.java	20 import com.google.clearsilver.jsilver.functions.operators.AddFunction; 21 import com.google.clearsilver.jsilver.functions.operators.AndFunction; 22 import com.google.clearsilver.jsilver.functions.operators.DivideFunction; 23 import com.google.clearsilver.jsilver.functions.operators.EqualFunction; 24 import com.google.clearsilver.jsilver.functions.operators.ExistsFunction; 25 import com.google.clearsilver.jsilver.functions.operators.GreaterFunction; 26 import com.google.clearsilver.jsilver.functions.operators.GreaterOrEqualFunction; 27 import com.google.clearsilver.jsilver.functions.operators.LessFunction; 28 import com.google.clearsilver.jsilver.functions.operators.LessOrEqualFunction; 29 import com.google.clearsilver.jsilver.functions.operators.ModuloFunction; [all …]
/aosp_15_r20/external/pytorch/benchmarks/operator_benchmark/
H A D	README.md	3 This benchmark suite provides a systemic way to measure the performance of operators for a wide ran… 33 Note: we set the number of OpenMP and MKL threads both to 1. If you want to benchmark operators wit… 52 …rch operators to the benchmark suite. Existing benchmarks for operators are in the `pt` directory … 104 … `Tag` allows you to only run some of the inputs. Most of the inputs to operators being supported … 127 List all the supported operators: 139 python -m benchmark_all_test --operators add --omp-num-threads 1 --mkl-num-threads 1 148 ## Adding New Operators to the Benchmark Suite 149 …operators in the benchmark suite. In the following sections, we'll step through the complete flow … 195 #### Part 1. Specify Inputs to Operators 218 1\. `op_bench.config_list` is a helper function which specifies a list of inputs to operators. It t… [all …]
/aosp_15_r20/external/pytorch/torch/_dynamo/
H A D	profiler.py	`14 operators: int = 0 variable in ProfileMetrics 20 self.operators += other.operators 28 self.operators + other.operators, 37 self.operators / max(1, other.operators), 42 return f"{self.operators:4.0%} ops {self.microseconds:4.0%} time" 45 return [self.operators, self.microseconds] 66 f"{self.captured.operators:4}/{self.total.operators:4} = " 74 self.captured.operators, 75 self.total.operators, 137 operators=captured_ops, [all …]`
/aosp_15_r20/external/sdv/vsomeip/third_party/boost/utility/
D	operators.htm	9 <title>Header <boost/operators.hpp> Documentation</title> 15 "../../boost/operators.hpp">boost/operators.hpp</a>></cite></h1> 18 "../../boost/operators.hpp">boost/operators.hpp</a>></cite> supplies 20 templates define operators at namespace scope in terms of a minimal 21 number of fundamental operators provided by the class.</p> 65 <a href="#arithmetic">Arithmetic operators</a> 69 <a href="#smpl_oprs">Simple Arithmetic Operators</a> 78 <li><a href="#grpd_oprs">Grouped Arithmetic Operators</a></li> 82 <li><a href="#a_demo">Arithmetic Operators Demonstration and Test 88 <a href="#deref">Dereference Operators and Iterator Helpers</a> [all …]

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