| /packages/modules/NeuralNetworks/tools/test_generator/tests/P_variation/ |
| D | stdout.txt.expect | 12 // Generated model constructor
16 void CreateModel_none(Model *model) {
22 auto op1 = model->addOperand(&type0);
23 auto op2 = model->addOperand(&type1);
24 auto op3 = model->addOperand(&type2);
25 auto param = model->addOperand(&type3);
26 auto param1 = model->addOperand(&type3);
27 auto param2 = model->addOperand(&type3);
28 auto act = model->addOperand(&type3);
29 auto layout = model->addOperand(&type3);
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| /packages/modules/NeuralNetworks/tools/test_generator/tests/P_implicit_variation/ |
| D | stdout.txt.expect | 12 // Generated model constructor
16 void CreateModel_relu(Model *model) {
22 auto op1 = model->addOperand(&type0);
23 auto op2 = model->addOperand(&type1);
24 auto op3 = model->addOperand(&type2);
25 auto param = model->addOperand(&type3);
26 auto param1 = model->addOperand(&type3);
27 auto param2 = model->addOperand(&type3);
28 auto act = model->addOperand(&type3);
29 auto layout = model->addOperand(&type3);
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| /packages/modules/NeuralNetworks/tools/test_generator/tests/P_naming/ |
| D | stdout.txt.expect | 12 // Generated model constructor
16 void CreateModel_model_name_nhwc_act_w_as_param_float(Model *model) {
22 auto op1 = model->addOperand(&type0);
23 auto op2 = model->addOperand(&type1);
24 auto op3 = model->addOperand(&type2);
25 auto param = model->addOperand(&type3);
26 auto param1 = model->addOperand(&type3);
27 auto param2 = model->addOperand(&type3);
28 auto act = model->addOperand(&type3);
29 auto layout = model->addOperand(&type3);
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| /packages/modules/NeuralNetworks/runtime/test/ |
| D | TestCompliance.cpp | 48 Model model = modelBuilder->makeModel(); in testAvailableSinceVersion() local
49 const auto modelVersion = validate(model); in testAvailableSinceVersion()
69 WrapperModel model; in TEST_F() local
70 auto op1 = model.addOperand(&kTypeTensorFloatRank0); in TEST_F()
71 auto op2 = model.addOperand(&kTypeTensorFloatRank0); in TEST_F()
72 auto op3 = model.addOperand(&kTypeTensorFloat); in TEST_F()
73 auto act = model.addConstantOperand(&kTypeInt32, kNoActivation); in TEST_F()
74 model.addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3}); in TEST_F()
75 model.identifyInputsAndOutputs({op1, op2}, {op3}); in TEST_F()
76 ASSERT_TRUE(model.isValid()); in TEST_F()
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| D | TestValidateModel.cpp | 29 ANeuralNetworksModel* model = nullptr; in TEST_F() local
30 ASSERT_EQ(ANeuralNetworksModel_create(&model), ANEURALNETWORKS_NO_ERROR); in TEST_F()
36 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_0), ANEURALNETWORKS_NO_ERROR); in TEST_F()
42 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_1), ANEURALNETWORKS_NO_ERROR); in TEST_F()
50 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_2), ANEURALNETWORKS_NO_ERROR); in TEST_F()
58 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_3), ANEURALNETWORKS_NO_ERROR); in TEST_F()
66 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_4), ANEURALNETWORKS_NO_ERROR); in TEST_F()
74 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_5), ANEURALNETWORKS_NO_ERROR); in TEST_F()
82 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_6), ANEURALNETWORKS_NO_ERROR); in TEST_F()
90 ASSERT_EQ(ANeuralNetworksModel_addOperand(model, &operand_7), ANEURALNETWORKS_NO_ERROR); in TEST_F()
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| D | TestMemory.cpp | 64 WrapperModel model; in TEST_F() local
68 auto a = model.addOperand(&matrixType); in TEST_F()
69 auto b = model.addOperand(&matrixType); in TEST_F()
70 auto c = model.addOperand(&matrixType); in TEST_F()
71 auto d = model.addOperand(&matrixType); in TEST_F()
72 auto e = model.addOperand(&matrixType); in TEST_F()
73 auto f = model.addOperand(&scalarType); in TEST_F()
75 model.setOperandValueFromMemory(e, &weights, offsetForMatrix2, sizeof(Matrix3x4)); in TEST_F()
76 model.setOperandValueFromMemory(a, &weights, offsetForMatrix3, sizeof(Matrix3x4)); in TEST_F()
77 model.setOperandValue(f, &activation, sizeof(activation)); in TEST_F()
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| D | TestMemoryInternal.cpp | 123 WrapperModel model; in TEST_F() local
127 auto a = model.addOperand(&matrixType); in TEST_F()
128 auto b = model.addOperand(&matrixType); in TEST_F()
129 auto c = model.addOperand(&matrixType); in TEST_F()
130 auto d = model.addOperand(&matrixType); in TEST_F()
131 auto e = model.addOperand(&matrixType); in TEST_F()
132 auto f = model.addOperand(&scalarType); in TEST_F()
134 model.setOperandValueFromMemory(e, &weights, offsetForMatrix2, sizeof(Matrix3x4)); in TEST_F()
135 model.setOperandValueFromMemory(a, &weights, offsetForMatrix3, sizeof(Matrix3x4)); in TEST_F()
136 model.setOperandValue(f, &activation, sizeof(activation)); in TEST_F()
[all …]
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| D | TestFree.cpp | 31 ANeuralNetworksModel* model = nullptr; in createUnfinishedModel() local
32 EXPECT_EQ(ANeuralNetworksModel_create(&model), ANEURALNETWORKS_NO_ERROR); in createUnfinishedModel()
37 EXPECT_EQ(ANeuralNetworksModel_addOperand(model, &type), ANEURALNETWORKS_NO_ERROR); in createUnfinishedModel()
38 EXPECT_EQ(ANeuralNetworksModel_addOperand(model, &type), ANEURALNETWORKS_NO_ERROR); in createUnfinishedModel()
43 ANeuralNetworksModel_addOperation(model, ANEURALNETWORKS_FLOOR, 1, inList, 1, outList), in createUnfinishedModel()
45 EXPECT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(model, 1, inList, 1, outList), in createUnfinishedModel()
48 return model; in createUnfinishedModel()
52 ANeuralNetworksModel* const model = createUnfinishedModel(); in createFinishedModel() local
53 EXPECT_EQ(ANeuralNetworksModel_finish(model), ANEURALNETWORKS_NO_ERROR); in createFinishedModel()
54 return model; in createFinishedModel()
[all …]
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| D | TestPartitioning.cpp | 289 uint32_t lookupOperation(const HidlModel& model, const V1_3::Subgraph& subgraph, in lookupOperation() argument
298 [&model](uint32_t offset) { return &model.operandValues[offset]; }, operationIndex); in lookupOperation()
303 void dump(const char* name, const ModelBuilder* model) { in dump() argument
304 const HidlModel hidlModel = model->makeHidlModel(); in dump()
354 const V1_3::Model& model, V1_1::ExecutionPreference preference, V1_3::Priority priority, in prepareModel_1_3() argument
360 for (const auto& operation : model.main.operations) { in prepareModel_1_3()
371 model, [&outStatus](V1_3::ErrorStatus inStatus, in prepareModel_1_3()
381 return SampleDriver::prepareModel_1_3(model, preference, priority, deadline, modelCache, in prepareModel_1_3()
398 hardware::Return<void> getSupportedOperations_1_3(const V1_3::Model& model, in getSupportedOperations_1_3() argument
400 if (!android::nn::validateModel(model)) { in getSupportedOperations_1_3()
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
| D | mobilenet_224_gender_basic_fixed_relaxed.mod.py | 19 model = Model() variable
238 model = model.Operation("CONV_2D", i86, i2, i1, i87, i88, i89, i90).To(i0) variable
239 model = model.Operation("DEPTHWISE_CONV_2D", i0, i29, i28, i91, i92, i93, i94, i95).To(i27) variable
240 model = model.Operation("CONV_2D", i27, i32, i31, i96, i97, i98, i99).To(i30) variable
241 model = model.Operation("DEPTHWISE_CONV_2D", i30, i35, i34, i100, i101, i102, i103, i104).To(i33) variable
242 model = model.Operation("CONV_2D", i33, i38, i37, i105, i106, i107, i108).To(i36) variable
243 model = model.Operation("DEPTHWISE_CONV_2D", i36, i41, i40, i109, i110, i111, i112, i113).To(i39) variable
244 model = model.Operation("CONV_2D", i39, i44, i43, i114, i115, i116, i117).To(i42) variable
245 model = model.Operation("DEPTHWISE_CONV_2D", i42, i47, i46, i118, i119, i120, i121, i122).To(i45) variable
246 model = model.Operation("CONV_2D", i45, i50, i49, i123, i124, i125, i126).To(i48) variable
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_0/ |
| D | mobilenet_224_gender_basic_fixed.mod.py | 3 model = Model() variable
222 model = model.Operation("CONV_2D", i86, i2, i1, i87, i88, i89, i90).To(i0) variable
223 model = model.Operation("DEPTHWISE_CONV_2D", i0, i29, i28, i91, i92, i93, i94, i95).To(i27) variable
224 model = model.Operation("CONV_2D", i27, i32, i31, i96, i97, i98, i99).To(i30) variable
225 model = model.Operation("DEPTHWISE_CONV_2D", i30, i35, i34, i100, i101, i102, i103, i104).To(i33) variable
226 model = model.Operation("CONV_2D", i33, i38, i37, i105, i106, i107, i108).To(i36) variable
227 model = model.Operation("DEPTHWISE_CONV_2D", i36, i41, i40, i109, i110, i111, i112, i113).To(i39) variable
228 model = model.Operation("CONV_2D", i39, i44, i43, i114, i115, i116, i117).To(i42) variable
229 model = model.Operation("DEPTHWISE_CONV_2D", i42, i47, i46, i118, i119, i120, i121, i122).To(i45) variable
230 model = model.Operation("CONV_2D", i45, i50, i49, i123, i124, i125, i126).To(i48) variable
[all …]
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| /packages/apps/DeskClock/tests/src/com/android/deskclock/uidata/ |
| D | FormattedStringModelTest.java | 34 private FormattedStringModel model; field in FormattedStringModelTest
39 model = new FormattedStringModel(context); in setUp()
44 model = null; in tearDown()
49 assertEquals("0", model.getFormattedNumber(0)); in positiveFormattedNumberWithNoPadding()
50 assertEquals("9", model.getFormattedNumber(9)); in positiveFormattedNumberWithNoPadding()
51 assertEquals("10", model.getFormattedNumber(10)); in positiveFormattedNumberWithNoPadding()
52 assertEquals("99", model.getFormattedNumber(99)); in positiveFormattedNumberWithNoPadding()
53 assertEquals("100", model.getFormattedNumber(100)); in positiveFormattedNumberWithNoPadding()
58 assertEquals("0", model.getFormattedNumber(false, 0, 1)); in positiveFormattedNumber()
59 assertEquals("00", model.getFormattedNumber(false, 0, 2)); in positiveFormattedNumber()
[all …]
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| /packages/modules/NeuralNetworks/tools/test_generator/tests/P_internal/ |
| D | stdout.txt.expect | 12 // Generated model constructor
16 void CreateModel(Model *model) {
20 auto o0 = model->addOperand(&type0);
21 auto o1 = model->addOperand(&type0);
22 auto act = model->addOperand(&type1);
23 auto o2 = model->addOperand(&type0);
24 auto p0 = model->addOperand(&type0);
25 auto t5 = model->addOperand(&type0);
26 auto t6 = model->addOperand(&type0);
27 auto i2 = model->addOperand(&type0);
[all …]
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| /packages/modules/NeuralNetworks/common/ |
| D | ModelUtils.cpp | 79 std::vector<bool> identifyUsedOperands(const Model& model) { in identifyUsedOperands() argument
80 std::vector<bool> used(model.main.operands.size(), false); in identifyUsedOperands()
85 for (const auto& operation : model.main.operations) { in identifyUsedOperands()
89 markUsed(model.main.inputIndexes); in identifyUsedOperands()
90 CHECK_EQ(used.size(), model.main.operands.size()); in identifyUsedOperands()
134 std::vector<bool> identifyUsedSubgraphs(const Model& model) { in identifyUsedSubgraphs() argument
135 std::vector<bool> used(model.referenced.size(), false); in identifyUsedSubgraphs()
136 identifyUsedSubgraphs(model.main.operands, model.referenced, &used); in identifyUsedSubgraphs()
137 CHECK_EQ(used.size(), model.referenced.size()); in identifyUsedSubgraphs()
155 std::vector<bool> identifyUsedPools(const Model& model) { in identifyUsedPools() argument
[all …]
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| D | LegacyHalUtils.cpp | 124 void logModelToInfo(const V1_0::Model& model) { in logModelToInfo() argument
126 LOG(INFO) << "operands" << toString(model.operands); in logModelToInfo()
127 LOG(INFO) << "operations" << toString(model.operations); in logModelToInfo()
128 LOG(INFO) << "inputIndexes" << toString(model.inputIndexes); in logModelToInfo()
129 LOG(INFO) << "outputIndexes" << toString(model.outputIndexes); in logModelToInfo()
130 LOG(INFO) << "operandValues size" << model.operandValues.size(); in logModelToInfo()
131 LOG(INFO) << "pools" << SHOW_IF_DEBUG(toString(model.pools)); in logModelToInfo()
134 void logModelToInfo(const V1_1::Model& model) { in logModelToInfo() argument
136 LOG(INFO) << "operands" << toString(model.operands); in logModelToInfo()
137 LOG(INFO) << "operations" << toString(model.operations); in logModelToInfo()
[all …]
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
| D | strided_slice_quant8_signed.mod.py | 17 model = Model() variable
28 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM… variable
42 model = Model() variable
53 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM… variable
67 model = Model() variable
78 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM… variable
92 model = Model() variable
103 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM… variable
117 model = Model() variable
128 model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisM… variable
[all …]
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| D | while_sum_of_powers_quant8.mod.py | 44 model = Model()
45 model.IdentifyInputs(xi, j, i, x)
46 model.IdentifyOutputs(out)
47 model.Operation("LESS", j, i).To(out)
48 return model
57 model = Model()
58 model.IdentifyInputs(xi, j, i, x)
59 model.IdentifyOutputs(xi_out, j_out)
60 model.Operation("MUL", xi, x, 0).To(xi_out)
61 model.Operation("ADD", j, [1], 0).To(j_out)
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| D | while_sum_of_powers_quant8_signed.mod.py | 44 model = Model()
45 model.IdentifyInputs(xi, j, i, x)
46 model.IdentifyOutputs(out)
47 model.Operation("LESS", j, i).To(out)
48 return model
57 model = Model()
58 model.IdentifyInputs(xi, j, i, x)
59 model.IdentifyOutputs(xi_out, j_out)
60 model.Operation("MUL", xi, x, 0).To(xi_out)
61 model.Operation("ADD", j, [1], 0).To(j_out)
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| D | while_sum_of_powers.mod.py | 40 model = Model()
41 model.IdentifyInputs(xi, j, i, x)
42 model.IdentifyOutputs(out)
43 model.Operation("LESS", j, i).To(out)
44 return model
53 model = Model()
54 model.IdentifyInputs(xi, j, i, x)
55 model.IdentifyOutputs(xi_out, j_out)
56 model.Operation("MUL", xi, x, 0).To(xi_out)
57 model.Operation("ADD", j, [1], 0).To(j_out)
[all …]
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| D | resize_quant8_signed.mod.py | 39 Example(test1, model=model_shape).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefau…
40 Example(test1, model=model_scale).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefau…
63 Example(test2, model=model_shape).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefau…
64 Example(test2, model=model_scale).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefau…
87 Example(test3, model=model_shape).AddVariations(quant8_signed, includeDefault=False)
88 Example(test3, model=model_scale).AddVariations(quant8_signed, includeDefault=False)
100 model = Model("zero_sized").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3… variable
105 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized) variable
109 model = model.Operation("RESIZE_BILINEAR", zero_sized, 3, 3, layout).To(o3) variable
138 model = Model("zero_sized").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3… variable
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| D | fully_connected_quant8_signed.mod.py | 17 model = Model() variable
26 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) variable
40 model = Model() variable
46 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) variable
59 model = Model() variable
65 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) variable
82 model = Model() variable
88 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) variable
101 model = Model() variable
107 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) variable
[all …]
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| /packages/apps/Contacts/ |
| D | proguard.flags | 1 -keep class com.android.contacts.model.Sources {
40 -keep class com.android.contacts.model.account.AccountDisplayInfo { *; }
41 -keep class com.android.contacts.model.account.AccountDisplayInfoFactory { *; }
42 -keep class com.android.contacts.model.account.AccountInfo { *; }
43 -keep class com.android.contacts.model.account.AccountType { *; }
44 -keep class com.android.contacts.model.account.AccountType$* { *; }
45 -keep class com.android.contacts.model.account.AccountTypeWithDataSet { *; }
46 -keep class com.android.contacts.model.account.AccountWithDataSet { *; }
47 -keep class com.android.contacts.model.account.BaseAccountType { *; }
48 -keep class com.android.contacts.model.account.BaseAccountType$* { *; }
[all …]
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| /packages/modules/NeuralNetworks/tools/test_generator/tests/P_backward_compatibility_float/ |
| D | stdout.txt.expect | 12 // Generated model constructor
16 void CreateModel(Model *model) {
28 auto input = model->addOperand(&type0);
29 auto input_to_input_weights = model->addOperand(&type1);
30 auto input_to_forget_weights = model->addOperand(&type1);
31 auto input_to_cell_weights = model->addOperand(&type1);
32 auto input_to_output_weights = model->addOperand(&type1);
33 auto recurrent_to_input_weights = model->addOperand(&type2);
34 auto recurrent_to_forget_weights = model->addOperand(&type2);
35 auto recurrent_to_cell_weights = model->addOperand(&type2);
[all …]
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| /packages/modules/Bluetooth/tools/rootcanal/ |
| D | Android.bp | 53 "model/controller/acl_connection.cc",
54 "model/controller/acl_connection_handler.cc",
55 "model/controller/controller_properties.cc",
56 "model/controller/dual_mode_controller.cc",
57 "model/controller/isochronous_connection_handler.cc",
58 "model/controller/le_advertiser.cc",
59 "model/controller/link_layer_controller.cc",
60 "model/controller/sco_connection.cc",
61 "model/controller/security_manager.cc",
62 "model/devices/baseband_sniffer.cc",
[all …]
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| /packages/apps/DocumentsUI/tests/functional/com/android/documentsui/dirlist/ |
| D | DirectoryAddonsAdapterTest.java | 62 mEnv.model.addUpdateListener(mAdapter.getModelUpdateListener()); in setUp()
69 assertEquals(mEnv.model.getItemCount() + 1, mAdapter.getItemCount()); in testItemCount_mixed()
73 mEnv.model.createFolder("a"); // id will be "1"...derived from insert position. in testGetPosition()
74 mEnv.model.createFile("b"); // id will be "2" in testGetPosition()
75 mEnv.model.update(); in testGetPosition()
77 assertEquals(0, mAdapter.getPosition(ModelId.build(mEnv.model.mUserId, AUTHORITY, "1"))); in testGetPosition()
80 assertEquals(2, mAdapter.getPosition(ModelId.build(mEnv.model.mUserId, AUTHORITY, "2"))); in testGetPosition()
87 mEnv.model.createFolder(name); in testItemCount_allDirs()
89 mEnv.model.update(); in testItemCount_allDirs()
90 assertEquals(mEnv.model.getItemCount(), mAdapter.getItemCount()); in testItemCount_allDirs()
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