| /packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | BidirectionalSequenceLSTM.cpp | 80 BidirectionalSequenceLSTM::BidirectionalSequenceLSTM(const Operation& operation, in BidirectionalSequenceLSTM() argument
82 input_ = GetInput(operation, operands, kInputTensor); in BidirectionalSequenceLSTM()
85 GetInput(operation, operands, kFwInputToInputWeightsTensor); // optional in BidirectionalSequenceLSTM()
86 fw_input_to_forget_weights_ = GetInput(operation, operands, kFwInputToForgetWeightsTensor); in BidirectionalSequenceLSTM()
87 fw_input_to_cell_weights_ = GetInput(operation, operands, kFwInputToCellWeightsTensor); in BidirectionalSequenceLSTM()
88 fw_input_to_output_weights_ = GetInput(operation, operands, kFwInputToOutputWeightsTensor); in BidirectionalSequenceLSTM()
91 GetInput(operation, operands, kFwRecurrentToInputWeightsTensor); // optional in BidirectionalSequenceLSTM()
93 GetInput(operation, operands, kFwRecurrentToForgetWeightsTensor); in BidirectionalSequenceLSTM()
94 fw_recurrent_to_cell_weights_ = GetInput(operation, operands, kFwRecurrentToCellWeightsTensor); in BidirectionalSequenceLSTM()
96 GetInput(operation, operands, kFwRecurrentToOutputWeightsTensor); in BidirectionalSequenceLSTM()
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| D | QuantizedLSTM.cpp | 224 QuantizedLSTMCell::QuantizedLSTMCell(const Operation& operation, RunTimeOperandInfo* operands) { in QuantizedLSTMCell() argument
225 input_ = GetInput(operation, operands, kInputTensor); in QuantizedLSTMCell()
227 inputToInputWeights_ = GetInput(operation, operands, kInputToInputWeightsTensor); in QuantizedLSTMCell()
228 inputToForgetWeights_ = GetInput(operation, operands, kInputToForgetWeightsTensor); in QuantizedLSTMCell()
229 inputToCellWeights_ = GetInput(operation, operands, kInputToCellWeightsTensor); in QuantizedLSTMCell()
230 inputToOutputWeights_ = GetInput(operation, operands, kInputToOutputWeightsTensor); in QuantizedLSTMCell()
232 recurrentToInputWeights_ = GetInput(operation, operands, kRecurrentToInputWeightsTensor); in QuantizedLSTMCell()
233 recurrentToForgetWeights_ = GetInput(operation, operands, kRecurrentToForgetWeightsTensor); in QuantizedLSTMCell()
234 recurrentToCellWeights_ = GetInput(operation, operands, kRecurrentToCellWeightsTensor); in QuantizedLSTMCell()
235 recurrentToOutputWeights_ = GetInput(operation, operands, kRecurrentToOutputWeightsTensor); in QuantizedLSTMCell()
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| D | SVDF.cpp | 33 SVDF::SVDF(const Operation& operation, RunTimeOperandInfo* operands) { in SVDF() argument
35 input_ = GetInput(operation, operands, kInputTensor); in SVDF()
36 weights_feature_ = GetInput(operation, operands, kWeightsFeatureTensor); in SVDF()
37 weights_time_ = GetInput(operation, operands, kWeightsTimeTensor); in SVDF()
38 bias_ = GetInput(operation, operands, kBiasTensor); in SVDF()
39 state_in_ = GetInput(operation, operands, kStateInTensor); in SVDF()
41 const auto& rankOperand = *GetInput(operation, operands, kRankParam); in SVDF()
43 const auto& activationOperand = *GetInput(operation, operands, kActivationParam); in SVDF()
47 state_out_ = GetOutput(operation, operands, kStateOutTensor); in SVDF()
48 output_ = GetOutput(operation, operands, kOutputTensor); in SVDF()
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| D | LSHProjection.cpp | 33 LSHProjection::LSHProjection(const Operation& operation, RunTimeOperandInfo* operands) { in LSHProjection() argument
34 input_ = GetInput(operation, operands, kInputTensor); in LSHProjection()
35 weight_ = GetInput(operation, operands, kWeightTensor); in LSHProjection()
36 hash_ = GetInput(operation, operands, kHashTensor); in LSHProjection()
39 getScalarData<int32_t>(*GetInput(operation, operands, kTypeParam))); in LSHProjection()
41 output_ = GetOutput(operation, operands, kOutputTensor); in LSHProjection()
44 bool LSHProjection::Prepare(const Operation& operation, RunTimeOperandInfo* operands, in Prepare() argument
49 NN_RET_CHECK(!IsNullInput(GetInput(operation, operands, requiredInput))) in Prepare()
52 NN_CHECK_EQ(NumOutputs(operation), 1); in Prepare()
54 const RunTimeOperandInfo* hash = GetInput(operation, operands, kHashTensor); in Prepare()
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| D | RNN.cpp | 30 RNN::RNN(const Operation& operation, RunTimeOperandInfo* operands) { in RNN() argument
32 input_ = GetInput(operation, operands, kInputTensor); in RNN()
33 weights_ = GetInput(operation, operands, kWeightsTensor); in RNN()
34 recurrent_weights_ = GetInput(operation, operands, kRecurrentWeightsTensor); in RNN()
35 hidden_state_in_ = GetInput(operation, operands, kHiddenStateInTensor); in RNN()
36 bias_ = GetInput(operation, operands, kBiasTensor); in RNN()
39 getScalarData<int32_t>(operands[operation.inputs[kActivationParam]])); in RNN()
41 hidden_state_out_ = GetOutput(operation, operands, kHiddenStateOutTensor); in RNN()
42 output_ = GetOutput(operation, operands, kOutputTensor); in RNN()
45 bool RNN::Prepare(const Operation& operation, RunTimeOperandInfo* operands, Shape* hiddenStateShape, in Prepare() argument
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| D | Multinomial.cpp | 60 Multinomial::Multinomial(const Operation& operation, RunTimeOperandInfo* operands) { in Multinomial() argument
62 input_ = GetInput(operation, operands, kInputTensor); in Multinomial()
63 sample_count_ = getScalarData<int>(*GetInput(operation, operands, kSampleCountParam)); in Multinomial()
64 random_seeds_ = GetInput(operation, operands, kRandomSeedsTensor); in Multinomial()
66 output_ = GetOutput(operation, operands, kOutputTensor); in Multinomial()
69 bool Multinomial::Prepare(const Operation& operation, RunTimeOperandInfo* operands, in Prepare() argument
72 NN_CHECK_EQ(NumInputsWithValues(operation, operands), 3); in Prepare()
73 NN_CHECK_EQ(NumOutputs(operation), 1); in Prepare()
75 const RunTimeOperandInfo* input = GetInput(operation, operands, Multinomial::kInputTensor); in Prepare()
80 getScalarData<int>(*GetInput(operation, operands, kSampleCountParam)); in Prepare()
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| D | LSTM.cpp | 54 LSTMCell::LSTMCell(const Operation& operation, RunTimeOperandInfo* operands) { in LSTMCell() argument
55 input_ = GetInput(operation, operands, kInputTensor); in LSTMCell()
58 GetInput(operation, operands, kInputToInputWeightsTensor); // optional in LSTMCell()
59 input_to_forget_weights_ = GetInput(operation, operands, kInputToForgetWeightsTensor); in LSTMCell()
60 input_to_cell_weights_ = GetInput(operation, operands, kInputToCellWeightsTensor); in LSTMCell()
61 input_to_output_weights_ = GetInput(operation, operands, kInputToOutputWeightsTensor); in LSTMCell()
64 GetInput(operation, operands, kRecurrentToInputWeightsTensor); // optional in LSTMCell()
65 recurrent_to_forget_weights_ = GetInput(operation, operands, kRecurrentToForgetWeightsTensor); in LSTMCell()
66 recurrent_to_cell_weights_ = GetInput(operation, operands, kRecurrentToCellWeightsTensor); in LSTMCell()
67 recurrent_to_output_weights_ = GetInput(operation, operands, kRecurrentToOutputWeightsTensor); in LSTMCell()
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| /packages/modules/NeuralNetworks/runtime/operation_converters/ |
| D | Conv2DOperationConverter.cpp | 28 const Operation& operation, SubGraphContext* context) const { in getConv2DInputs() argument
30 context->getSubgraph()->operands[operation.inputs[kFilterTensorIdx]])); in getConv2DInputs()
32 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kInputTensorIdx])); in getConv2DInputs()
34 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kFilterTensorIdx], in getConv2DInputs()
36 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kBiasTensorIdx])); in getConv2DInputs()
38 context->getTensorIdxFromOperandIdx(operation.inputs[kInputTensorIdx]), in getConv2DInputs()
39 context->getTensorIdxFromOperandIdx(operation.inputs[kFilterTensorIdx]), in getConv2DInputs()
40 context->getTensorIdxFromOperandIdx(operation.inputs[kBiasTensorIdx])}; in getConv2DInputs()
45 const Operation& operation, SubGraphContext* context) const { in getConv2DOutputs() argument
46 NN_TRY(context->createTensorFlatbufferFromOperand(operation.outputs[kOutputTensorIdx])); in getConv2DOutputs()
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| D | DepthwiseConv2DOperationConverter.cpp | 27 Result<void> DepthwiseConv2DOperationConverter::convert(const Operation& operation, in convert() argument
37 (operation.inputs.size() < 9 || in convert()
38 subgraph->operands[operation.inputs[8]].type == OperandType::BOOL); in convert()
40 std::vector<int32_t> inputs = NN_TRY(getConv2DInputs(operation, context)); in convert()
41 std::vector<int32_t> outputs = NN_TRY(getConv2DOutputs(operation, context)); in convert()
46 auto padOpIdx = NN_TRY(decomposeExplicitPadding(operation, context)); in convert()
53 const Operand& paddingTypeOperand = subgraph->operands[operation.inputs[3]]; in convert()
65 subgraph->operands[operation.inputs[baseOptionsIdx + kStrideWOffset]]; in convert()
67 subgraph->operands[operation.inputs[baseOptionsIdx + kStrideHOffset]]; in convert()
69 subgraph->operands[operation.inputs[baseOptionsIdx + kActivationOffset]]; in convert()
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| D | LogisticOperationConverter.cpp | 28 const Operation& operation, SubGraphContext* context) const { in getLogisticInputs() argument
29 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kInputTensorIdx])); in getLogisticInputs()
31 context->getTensorIdxFromOperandIdx(operation.inputs[kInputTensorIdx])}; in getLogisticInputs()
36 const Operation& operation, SubGraphContext* context) const { in getLogisticOutputs() argument
37 NN_TRY(context->createTensorFlatbufferFromOperand(operation.outputs[kOutputTensorIdx])); in getLogisticOutputs()
39 context->getTensorIdxFromOperandIdx(operation.outputs[kOutputTensorIdx])}; in getLogisticOutputs()
43 Result<void> LogisticOperationConverter::convert(const Operation& operation, in convert() argument
48 std::vector<int32_t> inputs = NN_TRY(getLogisticInputs(operation, context)); in convert()
49 std::vector<int32_t> outputs = NN_TRY(getLogisticOutputs(operation, context)); in convert()
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| D | ArithmeticOperationConverter.cpp | 28 const Operation& operation, SubGraphContext* context) const { in getArithmeticInputs() argument
29 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kInput1TensorIdx])); in getArithmeticInputs()
30 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kInput2TensorIdx])); in getArithmeticInputs()
32 context->getTensorIdxFromOperandIdx(operation.inputs[kInput1TensorIdx]), in getArithmeticInputs()
33 context->getTensorIdxFromOperandIdx(operation.inputs[kInput2TensorIdx])}; in getArithmeticInputs()
38 const Operation& operation, SubGraphContext* context) const { in getArithmeticOutputs() argument
39 NN_TRY(context->createTensorFlatbufferFromOperand(operation.outputs[kOutputTensorIdx])); in getArithmeticOutputs()
41 context->getTensorIdxFromOperandIdx(operation.outputs[kOutputTensorIdx])}; in getArithmeticOutputs()
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| /packages/modules/Bluetooth/android/app/tests/unit/src/com/android/bluetooth/pbap/ |
| D | BluetoothPbapObexServerTest.java | 233 Operation operation = mock(Operation.class); in testOnPut_notSupported() local
234 assertThat(mServer.onPut(operation)).isEqualTo(ResponseCodes.OBEX_HTTP_BAD_REQUEST); in testOnPut_notSupported()
254 Operation operation = mock(Operation.class); in testCloseStream_success() local
256 assertThat(BluetoothPbapObexServer.closeStream(outputStream, operation)).isTrue(); in testCloseStream_success()
258 verify(operation).close(); in testCloseStream_success()
265 Operation operation = mock(Operation.class); in testCloseStream_failOnClosingOutputStream() local
267 assertThat(BluetoothPbapObexServer.closeStream(outputStream, operation)).isFalse(); in testCloseStream_failOnClosingOutputStream()
273 Operation operation = mock(Operation.class); in testCloseStream_failOnClosingOperation() local
274 doThrow(IOException.class).when(operation).close(); in testCloseStream_failOnClosingOperation()
276 assertThat(BluetoothPbapObexServer.closeStream(outputStream, operation)).isFalse(); in testCloseStream_failOnClosingOperation()
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| /packages/modules/StatsD/statsd/tests/condition/ |
| D | CombinationConditionTracker_test.cpp | 29 LogicalOperation operation = LogicalOperation::AND; in TEST() local
41 EXPECT_EQ(evaluateCombinationCondition(children, operation, conditionResults), in TEST()
47 LogicalOperation operation = LogicalOperation::AND; in TEST() local
59 EXPECT_FALSE(evaluateCombinationCondition(children, operation, conditionResults)); in TEST()
66 EXPECT_TRUE(evaluateCombinationCondition(children, operation, conditionResults)); in TEST()
71 LogicalOperation operation = LogicalOperation::OR; in TEST() local
83 EXPECT_TRUE(evaluateCombinationCondition(children, operation, conditionResults)); in TEST()
90 EXPECT_FALSE(evaluateCombinationCondition(children, operation, conditionResults)); in TEST()
95 LogicalOperation operation = LogicalOperation::NOT; in TEST() local
103 EXPECT_FALSE(evaluateCombinationCondition(children, operation, conditionResults)); in TEST()
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| /packages/modules/Bluetooth/android/app/src/com/android/bluetooth/avrcpcontroller/bip/ |
| D | BipRequest.java | 76 ClientOperation operation = (ClientOperation) session.get(mHeaderSet); in executeGet() local
77 setOperation(operation); in executeGet()
78 operation.setGetFinalFlag(true); in executeGet()
79 operation.continueOperation(true, false); in executeGet()
80 readResponseHeaders(operation.getReceivedHeader()); in executeGet()
81 InputStream inputStream = operation.openInputStream(); in executeGet()
84 operation.close(); in executeGet()
85 mResponseCode = operation.getResponseCode(); in executeGet()
102 ClientOperation operation = (ClientOperation) session.put(mHeaderSet); in executePut() local
103 setOperation(operation); in executePut()
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| /packages/modules/NeuralNetworks/runtime/test/fuzzing/ |
| D | RandomGraphGenerator.cpp | 82 RandomOperation::RandomOperation(const OperationSignature& operation) in RandomOperation() argument
83 : opType(operation.opType), finalizer(operation.finalizer) { in RandomOperation()
87 TestOperandType dataType = getRandomChoice(operation.supportedDataTypes); in RandomOperation()
88 uint32_t rank = getRandomChoice(operation.supportedRanks); in RandomOperation()
91 for (const auto& op : operation.inputs) { in RandomOperation()
94 for (const auto& op : operation.outputs) { in RandomOperation()
97 if (operation.constructor) operation.constructor(dataType, rank, this); in RandomOperation()
179 for (const auto& operation : mOperations) { in generateValue() local
180 fillOperands(operation.inputs); in generateValue()
181 fillOperands(operation.outputs); in generateValue()
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| /packages/modules/Bluetooth/system/bta/has/ |
| D | has_client.cc | 449 void CpReadAllPresetsOperation(HasCtpOp operation) { in CpReadAllPresetsOperation() argument
450 DLOG(INFO) << __func__ << " Operation: " << operation; in CpReadAllPresetsOperation()
452 if (std::holds_alternative<int>(operation.addr_or_group)) { in CpReadAllPresetsOperation()
455 callbacks_->OnPresetInfoError(operation.addr_or_group, operation.index, in CpReadAllPresetsOperation()
462 HasDevice::MatchAddress(std::get<RawAddress>(operation.addr_or_group))); in CpReadAllPresetsOperation()
465 << ADDRESS_TO_LOGGABLE_STR(std::get<RawAddress>(operation.addr_or_group)); in CpReadAllPresetsOperation()
466 callbacks_->OnPresetInfoError(device->addr, operation.index, in CpReadAllPresetsOperation()
472 callbacks_->OnPresetInfoError(device->addr, operation.index, in CpReadAllPresetsOperation()
476 auto context = HasGattOpContext(operation); in CpReadAllPresetsOperation()
479 device->has_journal_.Append(HasJournalRecord(operation, context)); in CpReadAllPresetsOperation()
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| /packages/modules/NeuralNetworks/driver/sample_hidl/ |
| D | SampleDriverFloatXNNPACK.cpp | 182 for (const auto& operation : operations) { in Create() local
183 const std::vector<uint32_t>& ins = operation.inputs; in Create()
184 const std::vector<uint32_t>& outs = operation.outputs; in Create()
185 switch (operation.type) { in Create()
254 for (const auto& operation : operations) { in Create() local
255 if (VisitNode(subgraph.get(), operation, operands.data(), xnnpackTensors) != in Create()
409 static V1_3::ErrorStatus CheckNumInputsAndOutputs(const V1_3::Operation& operation, in CheckNumInputsAndOutputs() argument
412 if (operation.inputs.size() != expected_num_inputs) { in CheckNumInputsAndOutputs()
415 if (operation.outputs.size() != expected_num_outputs) { in CheckNumInputsAndOutputs()
496 static V1_3::ErrorStatus VisitNode(xnn_subgraph_t subgraph, const V1_3::Operation& operation, in VisitNode() argument
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| /packages/providers/MediaProvider/tests/src/com/android/providers/media/photopicker/data/ |
| D | PickerDbFacadeTest.java | 342 try (PickerDbFacade.DbWriteOperation operation = in testRemoveCloud_promote() argument
344 assertWriteOperation(operation, cloudCursor1, 1); in testRemoveCloud_promote()
345 assertWriteOperation(operation, cloudCursor2, 1); in testRemoveCloud_promote()
346 operation.setSuccess(); in testRemoveCloud_promote()
393 try (PickerDbFacade.DbWriteOperation operation = in testLocalUpdate() argument
395 assertWriteOperation(operation, localCursor1, 1); in testLocalUpdate()
396 assertWriteOperation(operation, localCursor2, 1); in testLocalUpdate()
397 operation.setSuccess(); in testLocalUpdate()
550 try (PickerDbFacade.DbWriteOperation operation = in testQueryWithIdFilter() argument
552 assertWriteOperation(operation, cursor1, 1); in testQueryWithIdFilter()
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| /packages/modules/Permission/framework-s/java/android/app/role/ |
| D | RoleControllerManager.java | 141 AndroidFuture<Bundle> operation = mRemoteService.postAsync(service -> { in grantDefaultRoles() local
146 propagateCallback(operation, "grantDefaultRoles", executor, callback); in grantDefaultRoles()
156 AndroidFuture<Bundle> operation = mRemoteService.postAsync(service -> { in onAddRoleHolder() local
162 propagateCallback(operation, "onAddRoleHolder", callback); in onAddRoleHolder()
172 AndroidFuture<Bundle> operation = mRemoteService.postAsync(service -> { in onRemoveRoleHolder() local
178 propagateCallback(operation, "onRemoveRoleHolder", callback); in onRemoveRoleHolder()
188 AndroidFuture<Bundle> operation = mRemoteService.postAsync(service -> { in onClearRoleHolders() local
194 propagateCallback(operation, "onClearRoleHolders", callback); in onClearRoleHolders()
205 AndroidFuture<Bundle> operation = mRemoteService.postAsync(service -> { in isApplicationVisibleForRole() local
211 propagateCallback(operation, "isApplicationVisibleForRole", executor, callback); in isApplicationVisibleForRole()
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| /packages/apps/WallpaperPicker2/src/com/android/wallpaper/module/ |
| D | DefaultAlarmManagerWrapper.java | 34 public void set(int type, long triggerAtMillis, PendingIntent operation) { in set() argument
35 mAlarmManager.set(type, triggerAtMillis, operation); in set()
40 PendingIntent operation) { in setWindow() argument
41 mAlarmManager.setWindow(type, windowStartMillis, windowLengthMillis, operation); in setWindow()
46 PendingIntent operation) { in setInexactRepeating() argument
47 mAlarmManager.setInexactRepeating(type, triggerAtMillis, intervalMillis, operation); in setInexactRepeating()
51 public void cancel(PendingIntent operation) { in cancel() argument
52 mAlarmManager.cancel(operation); in cancel()
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| /packages/modules/NeuralNetworks/common/ |
| D | LegacyHalUtils.cpp | 719 static V1_0::Operation uncheckedConvertToV1_0(const V1_1::Operation& operation) { in uncheckedConvertToV1_0() argument
720 return {.type = uncheckedConvertToV1_0(operation.type), in uncheckedConvertToV1_0()
721 .inputs = operation.inputs, in uncheckedConvertToV1_0()
722 .outputs = operation.outputs}; in uncheckedConvertToV1_0()
725 static V1_1::Operation convertToV1_1(const V1_0::Operation& operation) { in convertToV1_1() argument
726 return {.type = convertToV1_1(operation.type), in convertToV1_1()
727 .inputs = operation.inputs, in convertToV1_1()
728 .outputs = operation.outputs}; in convertToV1_1()
736 [](const V1_1::Operation& operation) { return uncheckedConvertToV1_0(operation); }); in uncheckedConvertToV1_0() argument
744 [](const V1_0::Operation& operation) { return convertToV1_1(operation); }); in convertToV1_1() argument
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| D | CpuExecutor.cpp | 69 OperationExecutionContext(const Operation* operation, RunTimeOperandInfo* operands) in OperationExecutionContext() argument
70 : operation(operation), operands(operands) {} in OperationExecutionContext()
101 const Operation* operation; member in android::nn::__anonaad75dad0111::OperationExecutionContext
108 CHECK(index < operation->inputs.size()); in getInputInfo()
109 return &operands[operation->inputs[index]]; in getInputInfo()
113 CHECK(index < operation->outputs.size()); in getOutputInfo()
114 return &operands[operation->outputs[index]]; in getOutputInfo()
118 CHECK(index < operation->outputs.size()); in getOutputInfo()
119 return &operands[operation->outputs[index]]; in getOutputInfo()
151 return operation->inputs.size(); in getNumInputs()
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| /packages/modules/NeuralNetworks/runtime/ |
| D | ModelArchHasher.cpp | 49 for (auto& operation : subgraph.operations) { in updateSubgraph() local
51 update(hasher, static_cast<const void*>(&operation.type), sizeof(operation.type)); in updateSubgraph()
52 success &= update(hasher, static_cast<const void*>(operation.inputs.data()), in updateSubgraph()
53 sizeof(decltype(operation.inputs)::value_type) * operation.inputs.size()); in updateSubgraph()
55 update(hasher, static_cast<const void*>(operation.outputs.data()), in updateSubgraph()
56 sizeof(decltype(operation.outputs)::value_type) * operation.outputs.size()); in updateSubgraph()
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| D | ModelBuilder.cpp | 403 Operation operation = { in addOperation() local
408 if (auto result = validateOperationButNotOperands(operation, mOperands, in addOperation()
421 mOperations.push_back(std::move(operation)); in addOperation()
569 static void logRemoval(const Operation& operation, uint32_t count, in logRemoval() argument
572 message << "Operation " << operation.type << " with inputs {"; in logRemoval()
573 for (uint32_t i = 0; i < operation.inputs.size(); ++i) { in logRemoval()
577 message << operands[operation.inputs[i]].type; in logRemoval()
585 for (Operation& operation : mOperations) { in removeTrailingArgumentsWithDefaultValues()
586 const uint32_t count = getNumTrailingArgumentsToRemove(operation); in removeTrailingArgumentsWithDefaultValues()
591 logRemoval(operation, count, mOperands); in removeTrailingArgumentsWithDefaultValues()
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| /packages/services/Car/car-lib/src/android/car/vms/ |
| D | VmsOperationRecorder.java | 207 private void recordOp(String operation) { in recordOp() argument
210 write(new JSONObject().put(operation, new JSONObject())); in recordOp()
217 private void recordOp(String operation, VmsLayer layer) { in recordOp() argument
220 recordOp(operation, new JSONObject().put("layer", toJson(layer))); in recordOp()
227 private void recordOp(String operation, VmsLayersOffering layersOffering) { in recordOp() argument
236 recordOp(operation, args); in recordOp()
243 private void recordOp(String operation, String intArgName, int arg) { in recordOp() argument
246 recordOp(operation, new JSONObject().put(intArgName, arg)); in recordOp()
253 private void recordOp(String operation, String intArgName, int arg, VmsLayer layer) { in recordOp() argument
256 recordOp(operation, in recordOp()
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