| /external/android-nn-driver/1.3/ |
| D | HalPolicy.hpp | 26 using Model = V1_3::Model; typedef in armnn_driver::hal_1_3::HalPolicy
36 …static bool ConvertOperation(const Operation& operation, const Model& model, ConversionData& data);
40 const Model& model,
44 …static bool ConvertAveragePool2d(const Operation& operation, const Model& model, ConversionData& d…
46 …static bool ConvertBatchToSpaceNd(const Operation& operation, const Model& model, ConversionData& …
48 static bool ConvertCast(const Operation& operation, const Model& model, ConversionData& data);
50 …static bool ConvertChannelShuffle(const Operation& operation, const Model& model, ConversionData& …
53 const Model& model,
57 …static bool ConvertConcatenation(const Operation& operation, const Model& model, ConversionData& d…
59 static bool ConvertConv2d(const Operation& operation, const Model& model, ConversionData& data);
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| D | HalPolicy.cpp | 20 bool HalPolicy::ConvertOperation(const Operation& operation, const Model& model, ConversionData& da… in ConvertOperation() argument
25 return ConvertElementwiseUnary(operation, model, data, UnaryOperation::Abs); in ConvertOperation()
27 return ConvertElementwiseBinary(operation, model, data, BinaryOperation::Add); in ConvertOperation()
29 return ConvertArgMinMax(operation, model, data, ArgMinMaxFunction::Max); in ConvertOperation()
31 return ConvertArgMinMax(operation, model, data, ArgMinMaxFunction::Min); in ConvertOperation()
33 return ConvertAveragePool2d(operation, model, data); in ConvertOperation()
35 return ConvertBatchToSpaceNd(operation, model, data); in ConvertOperation()
37 return ConvertCast(operation, model, data); in ConvertOperation()
39 return ConvertChannelShuffle(operation, model, data); in ConvertOperation()
41 return ConvertConcatenation(operation, model, data); in ConvertOperation()
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| /external/armnn/shim/sl/canonical/ |
| D | Converter.hpp | 24 using Model = ::android::nn::Model; typedef in armnn_driver::Converter
31 …static bool ConvertOperation(const Operation& operation, const Model& model, ConversionData& data);
34 static bool ConvertAdd(const Operation& operation, const Model& model, ConversionData& data);
37 const Model& model,
41 …static bool ConvertAveragePool2d(const Operation& operation, const Model& model, ConversionData& d…
43 …static bool ConvertBatchMatMul(const Operation& operation, const Model& model, ConversionData& dat…
45 …static bool ConvertBatchToSpaceNd(const Operation& operation, const Model& model, ConversionData& …
47 static bool ConvertCast(const Operation& operation, const Model& model, ConversionData& data);
50 const Model& model,
54 …static bool ConvertConcatenation(const Operation& operation, const Model& model, ConversionData& d…
[all …]
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| /external/android-nn-driver/1.2/ |
| D | HalPolicy.hpp | 26 using Model = V1_2::Model; typedef in armnn_driver::hal_1_2::HalPolicy
39 …static bool ConvertOperation(const Operation& operation, const Model& model, ConversionData& data);
43 const Model& model,
47 …static bool ConvertAveragePool2d(const Operation& operation, const Model& model, ConversionData& d…
49 …static bool ConvertBatchToSpaceNd(const Operation& operation, const Model& model, ConversionData& …
51 static bool ConvertCast(const Operation& operation, const Model& model, ConversionData& data);
53 …static bool ConvertChannelShuffle(const Operation& operation, const Model& model, ConversionData& …
56 const Model& model,
60 …static bool ConvertConcatenation(const Operation& operation, const Model& model, ConversionData& d…
62 static bool ConvertConv2d(const Operation& operation, const Model& model, ConversionData& data);
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| D | HalPolicy.cpp | 48 bool HalPolicy::ConvertOperation(const Operation& operation, const Model& model, ConversionData& da… in ConvertOperation() argument
53 return ConvertElementwiseUnary(operation, model, data, UnaryOperation::Abs); in ConvertOperation()
55 return ConvertElementwiseBinary(operation, model, data, BinaryOperation::Add); in ConvertOperation()
57 return ConvertArgMinMax(operation, model, data, ArgMinMaxFunction::Max); in ConvertOperation()
59 return ConvertArgMinMax(operation, model, data, ArgMinMaxFunction::Min); in ConvertOperation()
61 return ConvertAveragePool2d(operation, model, data); in ConvertOperation()
63 return ConvertBatchToSpaceNd(operation, model, data); in ConvertOperation()
65 return ConvertCast(operation, model, data); in ConvertOperation()
67 return ConvertChannelShuffle(operation, model, data); in ConvertOperation()
69 return ConvertConcatenation(operation, model, data); in ConvertOperation()
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | select_test.cc | 88 SelectOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, {1, 1, 1, 4}, in TEST() local
91 model.PopulateTensor<bool>(model.input1(), {true, false, true, false}); in TEST()
92 model.PopulateTensor<bool>(model.input2(), {false, false, false, false}); in TEST()
93 model.PopulateTensor<bool>(model.input3(), {true, true, true, true}); in TEST()
94 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
96 EXPECT_THAT(model.GetOutput<bool>(), in TEST()
98 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 1, 4})); in TEST()
102 SelectOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, {1, 1, 1, 4}, in TEST() local
105 model.PopulateTensor<bool>(model.input1(), {true, false, true, false}); in TEST()
106 model.PopulateTensor<float>(model.input2(), {0.1, 0.2, 0.3, 0.4}); in TEST()
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| D | comparisons_test.cc | 103 ComparisonOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, TensorType_BOOL, in TEST() local
105 model.PopulateTensor<bool>(model.input1(), {true, false, true, false}); in TEST()
106 model.PopulateTensor<bool>(model.input2(), {true, true, false, false}); in TEST()
107 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
109 EXPECT_THAT(model.GetOutput(), ElementsAre(true, false, false, true)); in TEST()
110 EXPECT_THAT(model.GetOutputShape(), ElementsAre(1, 1, 1, 4)); in TEST()
114 ComparisonOpModel model({1, 1, 1, 4}, {1, 1, 1, 4}, TensorType_FLOAT32, in TEST() local
116 model.PopulateTensor<float>(model.input1(), {0.1, 0.9, 0.7, 0.3}); in TEST()
117 model.PopulateTensor<float>(model.input2(), {0.1, 0.2, 0.6, 0.5}); in TEST()
118 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
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| D | range_test.cc | 56 RangeOpModel<int32_t> model(TensorType_INT32); in TEST() local
57 model.PopulateTensor<int32_t>(model.start(), {0}); in TEST()
58 model.PopulateTensor<int32_t>(model.limit(), {4}); in TEST()
59 model.PopulateTensor<int32_t>(model.delta(), {1}); in TEST()
60 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
61 EXPECT_THAT(model.GetOutputShape(), ElementsAre(4)); in TEST()
62 EXPECT_THAT(model.GetOutput(), ElementsAre(0, 1, 2, 3)); in TEST()
66 RangeOpModel<int32_t> model(TensorType_INT32); in TEST() local
67 model.PopulateTensor<int32_t>(model.start(), {2}); in TEST()
68 model.PopulateTensor<int32_t>(model.limit(), {9}); in TEST()
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| D | unsorted_segment_test.cc | 31 UnsortedSegmentModel<int32_t> model = in TEST_P() local
34 model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4, 5, 6}); in TEST_P()
35 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 1}); in TEST_P()
36 model.PopulateTensor<int32_t>(model.num_segments(), {2}); in TEST_P()
37 ASSERT_EQ(model.Invoke(), kTfLiteError); in TEST_P()
41 UnsortedSegmentModel<int32_t> model = in TEST_P() local
44 model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4}); in TEST_P()
45 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 1}); in TEST_P()
46 model.PopulateTensor<int32_t>(model.num_segments(), {1}); in TEST_P()
47 ASSERT_EQ(model.Invoke(), kTfLiteError); in TEST_P()
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| D | pack_test.cc | 61 PackOpModel<float> model({TensorType_FLOAT32, {2}}, 0, 3); in TEST() local
62 model.SetInput(0, {1, 4}); in TEST()
63 model.SetInput(1, {2, 5}); in TEST()
64 model.SetInput(2, {3, 6}); in TEST()
65 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
66 EXPECT_THAT(model.GetOutputShape(), ElementsAre(3, 2)); in TEST()
67 EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 4, 2, 5, 3, 6})); in TEST()
71 PackOpModel<float> model({TensorType_FLOAT32, {2}}, 1, 3); in TEST() local
72 model.SetInput(0, {1, 4}); in TEST()
73 model.SetInput(1, {2, 5}); in TEST()
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| D | reverse_test.cc | 57 ReverseOpModel<float> model({TensorType_FLOAT32, {4}}, in TEST() local
59 model.PopulateTensor<float>(model.input(), {1, 2, 3, 4}); in TEST()
60 model.PopulateTensor<int32_t>(model.axis(), {0}); in TEST()
61 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
63 EXPECT_THAT(model.GetOutputShape(), ElementsAre(4)); in TEST()
64 EXPECT_THAT(model.GetOutput(), ElementsAreArray({4, 3, 2, 1})); in TEST()
68 ReverseOpModel<float> model({TensorType_FLOAT32, {4, 3, 2}}, in TEST() local
70 model.PopulateTensor<float>(model.input(), in TEST()
73 model.PopulateTensor<int32_t>(model.axis(), {1}); in TEST()
74 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
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| D | mirror_pad_test.cc | 54 BaseMirrorPadOpModel<int> model( in TEST() local
57 model.PopulateTensor<int>(model.input_tensor_id(), {1, 2, 3, 4, 5, 6}); in TEST()
58 model.PopulateTensor<int>(model.padding_matrix_tensor_id(), {0, 0, 0, 0}); in TEST()
59 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
60 EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6})); in TEST()
64 BaseMirrorPadOpModel<int> model( in TEST() local
67 model.PopulateTensor<int>(model.input_tensor_id(), {1, 2, 3, 4, 5, 6}); in TEST()
68 model.PopulateTensor<int>(model.padding_matrix_tensor_id(), {0, 1, 0, 1}); in TEST()
69 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
70 EXPECT_THAT(model.GetOutput(), in TEST()
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| D | segment_sum_test.cc | 51 SegmentSumOpModel<int32_t> model({TensorType_INT32, {3, 4}}, in TEST() local
53 model.PopulateTensor<int32_t>(model.data(), in TEST()
55 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 0, 1}); in TEST()
56 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
57 EXPECT_THAT(model.GetOutput(), ElementsAreArray({5, 5, 5, 5, 5, 6, 7, 8})); in TEST()
58 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2, 4})); in TEST()
62 SegmentSumOpModel<int32_t> model({TensorType_INT32, {3}}, in TEST() local
64 model.PopulateTensor<int32_t>(model.data(), {1, 2, 3}); in TEST()
65 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 0, 1}); in TEST()
66 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
[all …]
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| D | unsorted_segment_sum_test.cc | 55 UnsortedSegmentSumModel<int32_t> model({TensorType_INT32, {7}}, in TEST() local
58 model.PopulateTensor<int32_t>(model.data(), {5, 1, 7, 2, 3, 4, 10}); in TEST()
59 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 0, 1, 1, 0, 1, 0}); in TEST()
60 model.PopulateTensor<int32_t>(model.num_segments(), {2}); in TEST()
61 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
62 EXPECT_THAT(model.GetOutput(), ElementsAreArray({19, 13})); in TEST()
63 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2})); in TEST()
67 UnsortedSegmentSumModel<int32_t> model({TensorType_INT32, {3, 4}}, in TEST() local
70 model.PopulateTensor<int32_t>(model.data(), in TEST()
72 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 1, 0}); in TEST()
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| D | arg_min_max_test.cc | 126 void ValidateOutput(const ArgBaseOpModel& model, in ValidateOutput() argument
129 EXPECT_THAT(model.GetInt32Output(), ElementsAreArray(expected_output)); in ValidateOutput()
131 EXPECT_THAT(model.GetInt64Output(), ElementsAreArray(expected_output)); in ValidateOutput()
143 ArgMaxOpModel model({1, 1, 1, 4}, TensorType_FLOAT32, 3, AxisType(), in TEST_P() local
145 model.PopulateTensor<float>(model.input(), {0.1, 0.9, 0.7, 0.3}); in TEST_P()
146 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST_P()
148 ValidateOutput(model, {1}); in TEST_P()
149 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 1})); in TEST_P()
153 ArgMaxOpModel model({1, 1, 1, 4}, TensorType_UINT8, 3, AxisType(), in TEST_P() local
155 model.PopulateTensor<uint8_t>(model.input(), {1, 9, 7, 3}); in TEST_P()
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| /external/tensorflow/tensorflow/python/keras/ |
| D | models.py | 16 """Code for model cloning, plus model-related API entries."""
41 Model = training.Model # pylint: disable=invalid-name variable
60 def _insert_ancillary_layers(model, ancillary_layers, metrics_names, new_nodes): argument
61 """Inserts ancillary layers into the model with the proper order."""
70 model._insert_layers(ancillary_layers, relevant_nodes=list(new_nodes))
79 layer_map: Map from layers in `model` to new layers.
80 tensor_map: Map from tensors in `model` to newly compute tensors.
85 # Iterated over every node in the reference model, in depth order.
129 def _clone_functional_model(model, input_tensors=None, layer_fn=_clone_layer): argument
130 """Clone a functional `Model` instance.
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| /external/tflite-support/tensorflow_lite_support/custom_ops/kernel/ |
| D | unsorted_segment_test.cc | 31 UnsortedSegmentModel<int32_t> model = in TEST_P() local
34 model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4, 5, 6}); in TEST_P()
35 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 1}); in TEST_P()
36 model.PopulateTensor<int32_t>(model.num_segments(), {2}); in TEST_P()
37 ASSERT_EQ(model.Invoke(), kTfLiteError); in TEST_P()
41 UnsortedSegmentModel<int32_t> model = in TEST_P() local
44 model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4}); in TEST_P()
45 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 1}); in TEST_P()
46 model.PopulateTensor<int32_t>(model.num_segments(), {1}); in TEST_P()
47 ASSERT_EQ(model.Invoke(), kTfLiteError); in TEST_P()
[all …]
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| D | unsorted_segment_sum_test.cc | 55 UnsortedSegmentSumModel<int32_t> model({TensorType_INT32, {7}}, in TEST() local
58 model.PopulateTensor<int32_t>(model.data(), {5, 1, 7, 2, 3, 4, 10}); in TEST()
59 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 0, 1, 1, 0, 1, 0}); in TEST()
60 model.PopulateTensor<int32_t>(model.num_segments(), {2}); in TEST()
61 ASSERT_EQ(model.Invoke(), kTfLiteOk); in TEST()
62 EXPECT_THAT(model.GetOutput(), ElementsAreArray({19, 13})); in TEST()
63 EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2})); in TEST()
67 UnsortedSegmentSumModel<int32_t> model({TensorType_INT32, {3, 4}}, in TEST() local
70 model.PopulateTensor<int32_t>(model.data(), in TEST()
72 model.PopulateTensor<int32_t>(model.segment_ids(), {0, 1, 0}); in TEST()
[all …]
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| /external/android-nn-driver/1.0/ |
| D | HalPolicy.hpp | 22 using Model = V1_0::Model; typedef in armnn_driver::hal_1_0::HalPolicy
31 …static bool ConvertOperation(const Operation& operation, const Model& model, ConversionData& data);
34 …static bool ConvertAveragePool2d(const Operation& operation, const Model& model, ConversionData& d…
36 …static bool ConvertConcatenation(const Operation& operation, const Model& model, ConversionData& d…
38 static bool ConvertConv2d(const Operation& operation, const Model& model, ConversionData& data);
40 …static bool ConvertDepthToSpace(const Operation& operation, const Model& model, ConversionData& da…
42 …static bool ConvertDepthwiseConv2d(const Operation& operation, const Model& model, ConversionData&…
44 …static bool ConvertDequantize(const Operation& operation, const Model& model, ConversionData& data…
47 const Model& model,
51 static bool ConvertFloor(const Operation& operation, const Model& model, ConversionData& data);
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| /external/XNNPACK/bench/ |
| D | qs8-gemm-e2e.cc | 61 state.SkipWithError("failed to create a model"); in GEMMEnd2EndBenchmark()
69 state.SkipWithError("failed to run a model"); in GEMMEnd2EndBenchmark()
83 …mm_4x8c4__aarch32_neondot_cortex_a55(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_4x8c4__aarch32_neondot_cortex_a55() argument
84 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_4x8c4__aarch32_neondot_cortex_a55()
93 …qs8_gemm_4x8c4__aarch32_neondot_ld64(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_4x8c4__aarch32_neondot_ld64() argument
94 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_4x8c4__aarch32_neondot_ld64()
110 …8__aarch32_neon_mlal_lane_cortex_a53(benchmark::State& state, models::ExecutionPlanFactory model) { in BENCHMARK_QS8_END2END()
111 GEMMEnd2EndBenchmark(state, model, in BENCHMARK_QS8_END2END()
120 …rch32_neon_mlal_lane_prfm_cortex_a53(benchmark::State& state, models::ExecutionPlanFactory model) { in qs8_gemm_4x8__aarch32_neon_mlal_lane_prfm_cortex_a53() argument
121 GEMMEnd2EndBenchmark(state, model, in qs8_gemm_4x8__aarch32_neon_mlal_lane_prfm_cortex_a53()
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| D | qu8-gemm-e2e.cc | 61 state.SkipWithError("failed to create a model"); in GEMMEnd2EndBenchmark()
69 state.SkipWithError("failed to run a model"); in GEMMEnd2EndBenchmark()
82 …8__aarch32_neon_mlal_lane_cortex_a53(benchmark::State& state, models::ExecutionPlanFactory model) { in qu8_gemm_4x8__aarch32_neon_mlal_lane_cortex_a53() argument
83 GEMMEnd2EndBenchmark(state, model, in qu8_gemm_4x8__aarch32_neon_mlal_lane_cortex_a53()
92 …rch32_neon_mlal_lane_prfm_cortex_a53(benchmark::State& state, models::ExecutionPlanFactory model) { in qu8_gemm_4x8__aarch32_neon_mlal_lane_prfm_cortex_a53() argument
93 GEMMEnd2EndBenchmark(state, model, in qu8_gemm_4x8__aarch32_neon_mlal_lane_prfm_cortex_a53()
102 …x8__aarch32_neon_mlal_lane_cortex_a7(benchmark::State& state, models::ExecutionPlanFactory model) { in qu8_gemm_4x8__aarch32_neon_mlal_lane_cortex_a7() argument
103 GEMMEnd2EndBenchmark(state, model, in qu8_gemm_4x8__aarch32_neon_mlal_lane_cortex_a7()
112 …arch32_neon_mlal_lane_prfm_cortex_a7(benchmark::State& state, models::ExecutionPlanFactory model) { in qu8_gemm_4x8__aarch32_neon_mlal_lane_prfm_cortex_a7() argument
113 GEMMEnd2EndBenchmark(state, model, in qu8_gemm_4x8__aarch32_neon_mlal_lane_prfm_cortex_a7()
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| /external/javaparser/javaparser-symbol-solver-testing/src/test/test_sourcecode/javasymbolsolver_0_6_0/expected_output/java-symbol-solver-core/ |
| D | com_github_javaparser_symbolsolver_javaparsermodel_contexts_MethodCallExprContext.txt | 4 …r.javaparsermodel.JavaParserFacade.get(com.github.javaparser.symbolsolver.model.resolution.TypeSol…
7 …().getGenericParameterByName(name) ==> com.github.javaparser.symbolsolver.model.typesystem.Referen…
8 …Line 66) typeOfScope.asReferenceType() ==> com.github.javaparser.symbolsolver.model.typesystem.Typ…
16 …on.Context.solveType(java.lang.String, com.github.javaparser.symbolsolver.model.resolution.TypeSol…
17 …Line 86) ref.isSolved() ==> com.github.javaparser.symbolsolver.model.resolution.SymbolReference.is…
18 …model.declarations.TypeDeclaration, java.lang.String, java.util.List<com.github.javaparser.symbols…
19 …Line 87) ref.getCorrespondingDeclaration() ==> com.github.javaparser.symbolsolver.model.resolution…
20 …Line 88) m.isSolved() ==> com.github.javaparser.symbolsolver.model.resolution.SymbolReference.isSo…
21 …Line 89) m.getCorrespondingDeclaration() ==> com.github.javaparser.symbolsolver.model.resolution.S…
22 …itList(com.github.javaparser.symbolsolver.model.resolution.TypeSolver, com.github.javaparser.symbo…
[all …]
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| /external/tensorflow/tensorflow/lite/tools/optimize/ |
| D | modify_model_interface_test.cc | 23 #include "tensorflow/lite/model.h"
31 // Create a model with 1 quant, 1 FC, 1 dequant
34 auto model = std::make_unique<ModelT>(); in CreateQuantizedModelSingleInputOutput() local
44 model->subgraphs.push_back(std::move(subgraph)); in CreateQuantizedModelSingleInputOutput()
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()
79 model->operator_codes.push_back(std::move(quant_op_code)); in CreateQuantizedModelSingleInputOutput()
80 model->operator_codes.push_back(std::move(fc_op_code)); in CreateQuantizedModelSingleInputOutput()
81 model->operator_codes.push_back(std::move(dequant_op_code)); in CreateQuantizedModelSingleInputOutput()
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| /external/llvm/test/Analysis/CostModel/X86/ |
| D | alternate-shuffle-cost.ll | 1 ; RUN: opt < %s -mtriple=x86_64-unknown-linux-gnu -mattr=+sse2,-ssse3 -cost-model -analyze | FileCh…
2 ; RUN: opt < %s -mtriple=x86_64-unknown-linux-gnu -mattr=+sse2,+sse3,+ssse3 -cost-model -analyze | …
3 ; RUN: opt < %s -mtriple=x86_64-unknown-linux-gnu -mcpu=corei7 -cost-model -analyze | FileCheck %s …
4 ; RUN: opt < %s -mtriple=x86_64-unknown-linux-gnu -mcpu=corei7-avx -cost-model -analyze | FileCheck…
5 ; RUN: opt < %s -mtriple=x86_64-unknown-linux-gnu -mcpu=core-avx2 -cost-model -analyze | FileCheck …
8 ; Verify the cost model for alternate shuffles.
18 ; CHECK: Printing analysis 'Cost Model Analysis' for function 'test_v2i32':
19 ; SSE2: Cost Model: {{.*}} 1 for instruction: %1 = shufflevector
20 ; SSSE3: Cost Model: {{.*}} 1 for instruction: %1 = shufflevector
21 ; SSE41: Cost Model: {{.*}} 1 for instruction: %1 = shufflevector
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| /external/google-cloud-java/java-aiplatform/proto-google-cloud-aiplatform-v1/src/main/java/com/google/cloud/aiplatform/v1/ |
| D | UpdateModelRequest.java | 70 private com.google.cloud.aiplatform.v1.Model model_;
75 * Required. The Model which replaces the resource on the server.
76 * When Model Versioning is enabled, the model.name will be used to determine
77 * whether to update the model or model version.
78 * 1. model.name with the @ value, e.g. models/123@1, refers to a version
80 * 2. model.name without the @ value, e.g. models/123, refers to a model
82 * 3. model.name with @-, e.g. models/123@-, refers to a model update.
83 * 4. Supported model fields: display_name, description; supported
85 * scenarios. Both the model labels and the version labels are merged when a
86 * model is returned. When updating labels, if the request is for
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