/packages/modules/NeuralNetworks/runtime/test/fuzzing/operation_signatures/ |
D | Convolutions.cpp | 30 int32_t paddingLeft = op->inputs[3]->value<int32_t>(); in conv2DExplicitConstructor() 31 int32_t paddingRight = op->inputs[4]->value<int32_t>(); in conv2DExplicitConstructor() 32 int32_t paddingTop = op->inputs[5]->value<int32_t>(); in conv2DExplicitConstructor() 33 int32_t paddingBottom = op->inputs[6]->value<int32_t>(); in conv2DExplicitConstructor() 34 int32_t strideWidth = op->inputs[7]->value<int32_t>(); in conv2DExplicitConstructor() 35 int32_t strideHeight = op->inputs[8]->value<int32_t>(); in conv2DExplicitConstructor() 38 if (op->inputs.size() > 10) { in conv2DExplicitConstructor() 39 useNchw = op->inputs[10]->value<bool8>(); in conv2DExplicitConstructor() 40 if (op->inputs.size() > 11) { in conv2DExplicitConstructor() 41 dilationWidth = op->inputs[11]->value<int32_t>(); in conv2DExplicitConstructor() [all …]
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D | Reshape.cpp | 30 if (op->inputs.size() > 2) useNchw = op->inputs[2]->value<bool8>(); in spaceToDepthConstructor() 35 op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE, in spaceToDepthConstructor() 37 int32_t blockSize = op->inputs[1]->value<int32_t>(); in spaceToDepthConstructor() 38 auto outHeight = op->inputs[0]->dimensions[heightIndex].exactDiv(blockSize); in spaceToDepthConstructor() 39 auto outWidth = op->inputs[0]->dimensions[widthIndex].exactDiv(blockSize); in spaceToDepthConstructor() 40 auto outDepth = op->inputs[0]->dimensions[depthIndex] * (blockSize * blockSize); in spaceToDepthConstructor() 43 op->outputs[0]->dimensions = {op->inputs[0]->dimensions[0], outDepth, outHeight, outWidth}; in spaceToDepthConstructor() 45 op->outputs[0]->dimensions = {op->inputs[0]->dimensions[0], outHeight, outWidth, outDepth}; in spaceToDepthConstructor() 47 setSameQuantization(op->outputs[0], op->inputs[0]); in spaceToDepthConstructor() 56 .inputs = {INPUT_DEFAULT, PARAMETER_RANGE(TestOperandType::INT32, 1, 5)}, \ [all …]
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D | Selection.cpp | 28 setFreeDimensions(op->inputs[0], /*rank=*/1); in embeddingLookupConstructor() 29 setFreeDimensions(op->inputs[1], rank); in embeddingLookupConstructor() 31 op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0]; in embeddingLookupConstructor() 33 op->outputs[0]->dimensions[i] = op->inputs[1]->dimensions[i]; in embeddingLookupConstructor() 35 setSameQuantization(op->outputs[0], op->inputs[1]); in embeddingLookupConstructor() 39 uint32_t dimValue = op->inputs[1]->dimensions[0].getValue(); in embeddingLookupFinalizer() 40 uint32_t numElements = op->inputs[0]->getNumberOfElements(); in embeddingLookupFinalizer() 43 op->inputs[0]->value<int32_t>(i) = getUniform<int32_t>(0, dimValue - 1); in embeddingLookupFinalizer() 53 .inputs = {PARAMETER_NONE(TestOperandType::TENSOR_INT32), INPUT_DEFAULT}, \ 65 op->inputs[0]->dimensions = {RandomVariableType::FREE}; in hashtableLookupConstructor() [all …]
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D | BoundingBox.cpp | 46 useNchw = op->inputs[9]->value<bool8>(); in roiConstructor() 48 useNchw = op->inputs[7]->value<bool8>(); in roiConstructor() 51 op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE, in roiConstructor() 53 op->inputs[1]->dimensions = {RandomVariableType::FREE, 4}; in roiConstructor() 54 op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]}; in roiConstructor() 55 auto outBatch = op->inputs[1]->dimensions[0]; in roiConstructor() 56 auto outDepth = op->inputs[0]->dimensions[useNchw ? 1 : 3]; in roiConstructor() 57 auto outHeight = op->inputs[3]->value<RandomVariable>(); in roiConstructor() 58 auto outWidth = op->inputs[4]->value<RandomVariable>(); in roiConstructor() 66 setSameQuantization(op->outputs[0], op->inputs[0]); in roiConstructor() [all …]
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D | Resize.cpp | 25 setFreeDimensions(op->inputs[0], rank); in resizeOpConstructor() 27 bool useNchw = op->inputs.size() > 3 ? static_cast<bool>(op->inputs[3]->value<bool8>()) : false; in resizeOpConstructor() 33 switch (op->inputs[1]->dataType) { in resizeOpConstructor() 36 outWidth = op->inputs[1]->value<RandomVariable>(); in resizeOpConstructor() 37 outHeight = op->inputs[2]->value<RandomVariable>(); in resizeOpConstructor() 41 outWidth = op->inputs[0]->dimensions[widthIndex] * op->inputs[1]->value<float>(); in resizeOpConstructor() 42 outHeight = op->inputs[0]->dimensions[heightIndex] * op->inputs[2]->value<float>(); in resizeOpConstructor() 45 outWidth = op->inputs[0]->dimensions[widthIndex] * in resizeOpConstructor() 46 static_cast<float>(op->inputs[1]->value<_Float16>()); in resizeOpConstructor() 47 outHeight = op->inputs[0]->dimensions[heightIndex] * in resizeOpConstructor() [all …]
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D | Poolings.cpp | 28 int32_t paddingLeft = op->inputs[1]->value<int32_t>(); in poolingExplicitOpConstructor() 29 int32_t paddingRight = op->inputs[2]->value<int32_t>(); in poolingExplicitOpConstructor() 30 int32_t paddingTop = op->inputs[3]->value<int32_t>(); in poolingExplicitOpConstructor() 31 int32_t paddingBottom = op->inputs[4]->value<int32_t>(); in poolingExplicitOpConstructor() 32 int32_t strideWidth = op->inputs[5]->value<int32_t>(); in poolingExplicitOpConstructor() 33 int32_t strideHeight = op->inputs[6]->value<int32_t>(); in poolingExplicitOpConstructor() 34 auto filterWidth = op->inputs[7]->value<RandomVariable>(); in poolingExplicitOpConstructor() 35 auto filterHeight = op->inputs[8]->value<RandomVariable>(); in poolingExplicitOpConstructor() 37 if (op->inputs.size() > 10) useNchw = op->inputs[10]->value<bool8>(); in poolingExplicitOpConstructor() 43 op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE, in poolingExplicitOpConstructor() [all …]
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D | Normalization.cpp | 26 if (op->inputs.size() > 2) { in softmaxConstructor() 27 op->inputs[2]->setScalarValue<int32_t>(getRandomAxis(rank)); in softmaxConstructor() 37 .inputs = {INPUT_DEFAULT, PARAMETER_FLOAT_RANGE(0.1, 10.0)}, in DEFINE_OPERATION_SIGNATURE() 47 .inputs = {INPUT_DEFAULT, PARAMETER_FLOAT_RANGE(0.1, 10.0)}, in DEFINE_OPERATION_SIGNATURE() 56 .inputs = {INPUT_DEFAULT, PARAMETER_FLOAT_RANGE(0.1, 10.0)}, in DEFINE_OPERATION_SIGNATURE() 67 .inputs = {INPUT_DEFAULT, PARAMETER_FLOAT_RANGE(0.1, 10.0), in DEFINE_OPERATION_SIGNATURE() 77 .inputs = {INPUT_DEFAULT, PARAMETER_FLOAT_RANGE(0.1, 10.0)}, in DEFINE_OPERATION_SIGNATURE() 86 .inputs = {INPUT_DEFAULT, PARAMETER_FLOAT_RANGE(0.1, 10.0), in DEFINE_OPERATION_SIGNATURE() 94 if (op->inputs.size() > 1) { in l2normConstructor() 95 op->inputs[1]->setScalarValue<int32_t>(getRandomAxis(rank)); in l2normConstructor() [all …]
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D | ConcatSplit.cpp | 26 op->inputs[i]->dimensions.resize(rank); in concatConstructor() 27 if (isV1_0) setSameQuantization(op->inputs[i], op->inputs[0]); in concatConstructor() 32 op->inputs[numInputs]->setScalarValue<int32_t>(axis); in concatConstructor() 34 op->inputs[0]->dimensions[i] = RandomVariableType::FREE; in concatConstructor() 35 op->outputs[0]->dimensions[i] = op->inputs[0]->dimensions[i]; in concatConstructor() 38 op->inputs[j]->dimensions[i] = RandomVariableType::FREE; in concatConstructor() 40 op->outputs[0]->dimensions[i] + op->inputs[j]->dimensions[i]; in concatConstructor() 42 op->inputs[j]->dimensions[i] = op->inputs[0]->dimensions[i]; in concatConstructor() 54 .inputs = {INPUT_DEFAULT, INPUT_DEFAULT, PARAMETER_NONE(TestOperandType::INT32)}, in DEFINE_OPERATION_SIGNATURE() 66 .inputs = {INPUT_DEFAULT, INPUT_DEFAULT, INPUT_DEFAULT, in DEFINE_OPERATION_SIGNATURE() [all …]
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D | Reduce.cpp | 24 setFreeDimensions(op->inputs[0], rank); in reduceOpConstructor() 31 op->inputs[1]->dimensions = {numAxis}; in reduceOpConstructor() 32 op->inputs[1]->resizeBuffer<int32_t>(numAxis); in reduceOpConstructor() 35 op->inputs[1]->value<int32_t>(i) = dim; in reduceOpConstructor() 41 if (op->inputs[2]->dataType == TestOperandType::BOOL) { in reduceOpConstructor() 42 keepDims = op->inputs[2]->value<bool8>(); in reduceOpConstructor() 44 keepDims = op->inputs[2]->value<int32_t>() > 0; in reduceOpConstructor() 49 op->outputs[0]->dimensions.emplace_back(op->inputs[0]->dimensions[i]); in reduceOpConstructor() 54 setSameQuantization(op->outputs[0], op->inputs[0]); in reduceOpConstructor() 69 .inputs = {INPUT_DEFAULT, PARAMETER_NONE(TestOperandType::TENSOR_INT32), \ [all …]
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D | Broadcast.cpp | 27 op->inputs[0]->dimensions.resize(rank); in broadcastOpConstructor() 28 op->inputs[1]->dimensions.resize(rank2); in broadcastOpConstructor() 33 op->inputs[0]->dimensions[i] = op->outputs[0]->dimensions[i]; in broadcastOpConstructor() 37 op->inputs[0]->dimensions[i] = op->outputs[0]->dimensions[i]; in broadcastOpConstructor() 38 op->inputs[1]->dimensions[i - rankDiff] = op->outputs[0]->dimensions[i]; in broadcastOpConstructor() 41 op->inputs[0]->dimensions[i] = 1; in broadcastOpConstructor() 42 op->inputs[1]->dimensions[i - rankDiff] = op->outputs[0]->dimensions[i]; in broadcastOpConstructor() 45 op->inputs[0]->dimensions[i] = op->outputs[0]->dimensions[i]; in broadcastOpConstructor() 46 op->inputs[1]->dimensions[i - rankDiff] = 1; in broadcastOpConstructor() 52 op->inputs[0]->dimensions.swap(op->inputs[1]->dimensions); in broadcastOpConstructor() [all …]
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D | FullyConnected.cpp | 28 op->inputs[0]->dimensions.resize(rank); in fullyConnectedConstructor() 31 op->inputs[0]->dimensions[i] = RandomVariableType::FREE; in fullyConnectedConstructor() 32 numElements = numElements * op->inputs[0]->dimensions[i]; in fullyConnectedConstructor() 36 op->inputs[1]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE}; in fullyConnectedConstructor() 39 op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]}; in fullyConnectedConstructor() 42 op->outputs[0]->dimensions = {numElements.exactDiv(op->inputs[1]->dimensions[1]), in fullyConnectedConstructor() 43 op->inputs[1]->dimensions[0]}; in fullyConnectedConstructor() 54 .inputs = {INPUT_DEFAULT, INPUT_DEFAULT, INPUT_BIAS, in DEFINE_OPERATION_SIGNATURE() 65 .inputs = {INPUT_DEFAULT, INPUT_DEFAULT, INPUT_BIAS, in DEFINE_OPERATION_SIGNATURE() 75 .inputs = {INPUT_DEFAULT, INPUT_DEFAULT, INPUT_BIAS, in DEFINE_OPERATION_SIGNATURE()
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/packages/modules/NeuralNetworks/runtime/operation_converters/ |
D | Conv2DOperationConverter.cpp | 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() 37 std::vector<int32_t> inputs{ in getConv2DInputs() local 38 context->getTensorIdxFromOperandIdx(operation.inputs[kInputTensorIdx]), in getConv2DInputs() 39 context->getTensorIdxFromOperandIdx(operation.inputs[kFilterTensorIdx]), in getConv2DInputs() 40 context->getTensorIdxFromOperandIdx(operation.inputs[kBiasTensorIdx])}; in getConv2DInputs() 41 return inputs; in getConv2DInputs() 55 const Operand& inputOperand = subgraph->operands[operation.inputs[0]]; in decomposeExplicitPadding() [all …]
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D | DepthwiseConv2DOperationConverter.cpp | 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() local 47 inputs[0] = padOpIdx; 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() 71 subgraph->operands[operation.inputs[baseOptionsIdx + kDepthwiseMultiplier]]; in convert() 86 if (operation.inputs.size() > static_cast<uint32_t>(isNchwIdx)) { in convert() [all …]
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D | ArithmeticOperationConverter.cpp | 29 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kInput1TensorIdx])); in getArithmeticInputs() 30 NN_TRY(context->createTensorFlatbufferFromOperand(operation.inputs[kInput2TensorIdx])); in getArithmeticInputs() 31 std::vector<int32_t> inputs{ in getArithmeticInputs() local 32 context->getTensorIdxFromOperandIdx(operation.inputs[kInput1TensorIdx]), in getArithmeticInputs() 33 context->getTensorIdxFromOperandIdx(operation.inputs[kInput2TensorIdx])}; in getArithmeticInputs() 34 return inputs; in getArithmeticInputs()
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/packages/modules/Bluetooth/android/app/tests/unit/src/com/android/bluetooth/avrcpcontroller/bip/ |
D | BipEncodingTest.java | 43 String[] inputs, in testParseMany() argument 48 for (String input : inputs) { in testParseMany() 55 String[] inputs = new String[] {"JPEG", "jpeg", "Jpeg", "JpEg"}; in testParseJpeg() local 56 testParseMany(inputs, BipEncoding.JPEG, "JPEG", null, true); in testParseJpeg() 61 String[] inputs = new String[] {"GIF", "gif", "Gif", "gIf"}; in testParseGif() local 62 testParseMany(inputs, BipEncoding.GIF, "GIF", null, true); in testParseGif() 67 String[] inputs = new String[] {"WBMP", "wbmp", "Wbmp", "WbMp"}; in testParseWbmp() local 68 testParseMany(inputs, BipEncoding.WBMP, "WBMP", null, false); in testParseWbmp() 73 String[] inputs = new String[] {"PNG", "png", "Png", "PnG"}; in testParsePng() local 74 testParseMany(inputs, BipEncoding.PNG, "PNG", null, true); in testParsePng() [all …]
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/packages/modules/AppSearch/testing/coretests/src/android/app/appsearch/external/util/ |
D | BundleUtilTest.java | 70 Bundle[] inputs = new Bundle[2]; in testDeepEquals_thorough_equal() local 72 inputs[i] = createThoroughBundle(); in testDeepEquals_thorough_equal() 74 assertThat(inputs[0]).isNotEqualTo(inputs[1]); in testDeepEquals_thorough_equal() 75 assertThat(BundleUtil.deepEquals(inputs[0], inputs[1])).isTrue(); in testDeepEquals_thorough_equal() 80 Bundle[] inputs = new Bundle[2]; in testDeepEquals_thorough_notEqual() local 86 inputs[i] = b; in testDeepEquals_thorough_notEqual() 88 assertThat(inputs[0]).isNotEqualTo(inputs[1]); in testDeepEquals_thorough_notEqual() 89 assertThat(BundleUtil.deepEquals(inputs[0], inputs[1])).isFalse(); in testDeepEquals_thorough_notEqual() 152 Bundle[] inputs = new Bundle[2]; in testDeepHashCode_same() local 154 inputs[i] = createThoroughBundle(); in testDeepHashCode_same() [all …]
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/packages/modules/Virtualization/pvmfw/src/ |
D | dice.rs | 225 let inputs = PartialInputs::new(&vb_data).unwrap(); in base_data_conversion() localVariable 227 assert_eq!(inputs.mode, DiceMode::kDiceModeNormal); in base_data_conversion() 228 assert_eq!(inputs.security_version, 42); in base_data_conversion() 229 assert!(!inputs.rkp_vm_marker); in base_data_conversion() 237 let inputs = PartialInputs::new(&vb_data).unwrap(); in debuggable_conversion() localVariable 239 assert_eq!(inputs.mode, DiceMode::kDiceModeDebug); in debuggable_conversion() 246 let inputs = PartialInputs::new(&vb_data).unwrap(); in rkp_vm_conversion() localVariable 248 assert!(inputs.rkp_vm_marker); in rkp_vm_conversion() 254 let inputs = PartialInputs::new(&vb_data).unwrap(); in base_config_descriptor() localVariable 255 let config_map = decode_config_descriptor(&inputs, None); in base_config_descriptor() [all …]
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/packages/modules/NeuralNetworks/runtime/test/generated/spec_V1_2/ |
D | l2_normalization_v1_2.example.cpp | 35 .inputs = {0}, in get_test_model_dim4_axis3() 112 .inputs = {2, 3, 4}, in get_test_model_dim4_axis3_all_inputs_as_internal() 116 .inputs = {0}, in get_test_model_dim4_axis3_all_inputs_as_internal() 163 .inputs = {0}, in get_test_model_dim4_axis3_relaxed() 240 .inputs = {2, 3, 4}, in get_test_model_dim4_axis3_relaxed_all_inputs_as_internal() 244 .inputs = {0}, in get_test_model_dim4_axis3_relaxed_all_inputs_as_internal() 291 .inputs = {0}, in get_test_model_dim4_axis3_float16() 368 .inputs = {2, 3, 4}, in get_test_model_dim4_axis3_float16_all_inputs_as_internal() 372 .inputs = {0}, in get_test_model_dim4_axis3_float16_all_inputs_as_internal() 419 .inputs = {0}, in get_test_model_dim4_axis3_quant8() [all …]
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D | cast.example.cpp | 35 .inputs = {0}, in get_test_model_float16_to_float16() 112 .inputs = {2, 3, 4}, in get_test_model_float16_to_float16_all_inputs_as_internal() 116 .inputs = {0}, in get_test_model_float16_to_float16_all_inputs_as_internal() 163 .inputs = {0}, in get_test_model_float16_to_float32() 240 .inputs = {2, 3, 4}, in get_test_model_float16_to_float32_all_inputs_as_internal() 244 .inputs = {0}, in get_test_model_float16_to_float32_all_inputs_as_internal() 291 .inputs = {0}, in get_test_model_float16_to_float32_relaxed() 368 .inputs = {2, 3, 4}, in get_test_model_float16_to_float32_relaxed_all_inputs_as_internal() 372 .inputs = {0}, in get_test_model_float16_to_float32_relaxed_all_inputs_as_internal() 419 .inputs = {0}, in get_test_model_float16_to_int32() [all …]
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D | l2_normalization_axis.example.cpp | 45 .inputs = {0, 1}, in get_test_model_dim4_axis0() 132 .inputs = {3, 4, 5}, in get_test_model_dim4_axis0_all_inputs_as_internal() 136 .inputs = {0, 1}, in get_test_model_dim4_axis0_all_inputs_as_internal() 193 .inputs = {0, 1}, in get_test_model_dim4_axis0_relaxed() 280 .inputs = {3, 4, 5}, in get_test_model_dim4_axis0_relaxed_all_inputs_as_internal() 284 .inputs = {0, 1}, in get_test_model_dim4_axis0_relaxed_all_inputs_as_internal() 341 .inputs = {0, 1}, in get_test_model_dim4_axis0_float16() 428 .inputs = {3, 4, 5}, in get_test_model_dim4_axis0_float16_all_inputs_as_internal() 432 .inputs = {0, 1}, in get_test_model_dim4_axis0_float16_all_inputs_as_internal() 489 .inputs = {0, 1}, in get_test_model_dim4_axis0_quant8() [all …]
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D | pow.example.cpp | 45 .inputs = {0, 1}, in get_test_model() 162 .inputs = {3, 4, 5}, in get_test_model_all_inputs_as_internal() 166 .inputs = {6, 7, 8}, in get_test_model_all_inputs_as_internal() 170 .inputs = {0, 1}, in get_test_model_all_inputs_as_internal() 227 .inputs = {0, 1}, in get_test_model_relaxed() 344 .inputs = {3, 4, 5}, in get_test_model_relaxed_all_inputs_as_internal() 348 .inputs = {6, 7, 8}, in get_test_model_relaxed_all_inputs_as_internal() 352 .inputs = {0, 1}, in get_test_model_relaxed_all_inputs_as_internal() 409 .inputs = {0, 1}, in get_test_model_float16() 526 .inputs = {3, 4, 5}, in get_test_model_float16_all_inputs_as_internal() [all …]
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D | not_equal.example.cpp | 45 .inputs = {0, 1}, in get_test_model_simple() 162 .inputs = {3, 4, 5}, in get_test_model_simple_all_inputs_as_internal() 166 .inputs = {6, 7, 8}, in get_test_model_simple_all_inputs_as_internal() 170 .inputs = {0, 1}, in get_test_model_simple_all_inputs_as_internal() 227 .inputs = {0, 1}, in get_test_model_simple_int32() 284 .inputs = {0, 1}, in get_test_model_simple_float16() 401 .inputs = {3, 4, 5}, in get_test_model_simple_float16_all_inputs_as_internal() 405 .inputs = {6, 7, 8}, in get_test_model_simple_float16_all_inputs_as_internal() 409 .inputs = {0, 1}, in get_test_model_simple_float16_all_inputs_as_internal() 466 .inputs = {0, 1}, in get_test_model_simple_relaxed() [all …]
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/packages/apps/Camera2/src/com/android/camera/async/ |
D | ObservableCombiner.java | 45 private ObservableCombiner(List<? extends Observable<?>> inputs, in ObservableCombiner() argument 47 mInputs = ImmutableList.copyOf(inputs); in ObservableCombiner() 62 static <I, O> Observable<O> transform(final List<? extends Observable<I>> inputs, in transform() argument 64 return new ObservableCombiner<>(inputs, new Supplier<O>() { in transform() 68 for (Observable<? extends I> dependency : inputs) { in transform() 76 static <O> Observable<O> transform(final List<? extends Observable<?>> inputs, 78 return new ObservableCombiner<>(inputs, output);
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/packages/modules/NeuralNetworks/runtime/test/generated/spec_V1_3/ |
D | rank.example.cpp | 35 .inputs = {0}, in get_test_model_1d() 112 .inputs = {2, 3, 4}, in get_test_model_1d_all_inputs_as_internal() 116 .inputs = {0}, in get_test_model_1d_all_inputs_as_internal() 163 .inputs = {0}, in get_test_model_1d_int32() 210 .inputs = {0}, in get_test_model_1d_float16() 287 .inputs = {2, 3, 4}, in get_test_model_1d_float16_all_inputs_as_internal() 291 .inputs = {0}, in get_test_model_1d_float16_all_inputs_as_internal() 338 .inputs = {0}, in get_test_model_1d_quant8() 415 .inputs = {2, 3, 4}, in get_test_model_1d_quant8_all_inputs_as_internal() 419 .inputs = {0}, in get_test_model_1d_quant8_all_inputs_as_internal() [all …]
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D | hard_swish.example.cpp | 35 .inputs = {0}, in get_test_model_simple() 112 .inputs = {2, 3, 4}, in get_test_model_simple_all_inputs_as_internal() 116 .inputs = {0}, in get_test_model_simple_all_inputs_as_internal() 163 .inputs = {0}, in get_test_model_simple_float16() 240 .inputs = {2, 3, 4}, in get_test_model_simple_float16_all_inputs_as_internal() 244 .inputs = {0}, in get_test_model_simple_float16_all_inputs_as_internal() 291 .inputs = {0}, in get_test_model_simple_relaxed() 368 .inputs = {2, 3, 4}, in get_test_model_simple_relaxed_all_inputs_as_internal() 372 .inputs = {0}, in get_test_model_simple_relaxed_all_inputs_as_internal() 419 .inputs = {0}, in get_test_model_simple_quant8() [all …]
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