/packages/modules/NeuralNetworks/common/ |
D | AidlValidateHal.cpp | 45 NN_RET_CHECK(preparedModels.size() != 0); in validateMemoryDesc() 46 NN_RET_CHECK(inputRoles.size() != 0 || outputRoles.size() != 0); in validateMemoryDesc() 54 NN_RET_CHECK(preparedModel != nullptr); in validateMemoryDesc() 56 NN_RET_CHECK(model != nullptr); in validateMemoryDesc() 62 NN_RET_CHECK(success); in validateMemoryDesc() 68 NN_RET_CHECK(preparedModel != nullptr); in validateMemoryDesc() 70 NN_RET_CHECK(model != nullptr); in validateMemoryDesc() 76 NN_RET_CHECK(success); in validateMemoryDesc() 83 NN_RET_CHECK(canonicalOperandType.has_value()) << canonicalOperandType.error().message; in validateMemoryDesc() 87 NN_RET_CHECK(maybeDimensions.has_value()) << maybeDimensions.error().message; in validateMemoryDesc() [all …]
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D | LegacyUtils.cpp | 403 NN_RET_CHECK(type.dimensions == nullptr) << tag << " invalid dimensions for scalar type"; in validateScalarDimensions() 408 NN_RET_CHECK(0 <= type.zeroPoint && type.zeroPoint <= 255) in validateQuant8AsymmParams() 416 NN_RET_CHECK(-128 <= type.zeroPoint && type.zeroPoint <= 127) in validateQuant8AsymmSignedParams() 429 NN_RET_CHECK(0 <= type.zeroPoint && type.zeroPoint <= 65535) in validateQuant16AsymmParams() 477 NN_RET_CHECK(extensionOperandTypeInfo != nullptr); in validateOperandTypeHelper() 479 NN_RET_CHECK( in validateOperandTypeHelper() 482 NN_RET_CHECK(validateScalarDimensions(type, tag)); in validateOperandTypeHelper() 487 NN_RET_CHECK(extensionOperandTypeInfo == nullptr); in validateOperandTypeHelper() 488 NN_RET_CHECK(validCode(kNumberOfDataTypes, kNumberOfDataTypesOEM, type.type)) in validateOperandTypeHelper() 493 NN_RET_CHECK(validateScalarDimensions(type, tag)); in validateOperandTypeHelper() [all …]
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/packages/modules/NeuralNetworks/common/operations/ |
D | QLSTM.cpp | 144 NN_RET_CHECK(validateInputTypes(context, inExpectedTypes)); in validate() 153 NN_RET_CHECK(validateOutputTypes(context, outExpectedTypes)); in validate() 175 NN_RET_CHECK(!context->isOmittedInput(tensor)) in prepare() 234 NN_RET_CHECK(cifgWeightsAllOrNone); in prepare() 263 NN_RET_CHECK(peepholeWeightsAllOrNone); in prepare() 266 NN_RET_CHECK(hasTensor(context, kInputGateBiasTensor)); in prepare() 271 NN_RET_CHECK(!hasTensor(context, kInputGateBiasTensor)) in prepare() 332 NN_RET_CHECK(!hasTensor(context, kInputLayerNormTensor)) in prepare() 340 NN_RET_CHECK(layerNormWeightsAllOrNoneCifg); in prepare() 350 NN_RET_CHECK(layerNormWeightsAllOrNone); in prepare() [all …]
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D | RoiPooling.cpp | 85 NN_RET_CHECK(roiInfo[0] >= 0); in roiPoolingNhwc() 86 NN_RET_CHECK(roiInfo[1] >= 0); in roiPoolingNhwc() 87 NN_RET_CHECK(roiInfo[2] >= 0); in roiPoolingNhwc() 88 NN_RET_CHECK(roiInfo[3] >= 0); in roiPoolingNhwc() 89 NN_RET_CHECK(roiInfo[0] * widthScale <= inWidth); in roiPoolingNhwc() 90 NN_RET_CHECK(roiInfo[1] * heightScale <= inHeight); in roiPoolingNhwc() 91 NN_RET_CHECK(roiInfo[2] * widthScale <= inWidth); in roiPoolingNhwc() 92 NN_RET_CHECK(roiInfo[3] * heightScale <= inHeight); in roiPoolingNhwc() 93 NN_RET_CHECK(roiInfo[0] <= roiInfo[2]); in roiPoolingNhwc() 94 NN_RET_CHECK(roiInfo[1] <= roiInfo[3]); in roiPoolingNhwc() [all …]
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D | Pooling.cpp | 259 NN_RET_CHECK(input.initialize(inputData, inputShape)); in averagePool() 260 NN_RET_CHECK(output.initialize(outputData, outputShape)); in averagePool() 261 NN_RET_CHECK(averagePoolNhwc(input.getNhwcBuffer(), input.getNhwcShape(), param, in averagePool() 263 NN_RET_CHECK(output.commit()); in averagePool() 272 NN_RET_CHECK(input.initialize(inputData, inputShape)); in l2Pool() 273 NN_RET_CHECK(output.initialize(outputData, outputShape)); in l2Pool() 274 NN_RET_CHECK(l2PoolNhwc(input.getNhwcBuffer(), input.getNhwcShape(), param, in l2Pool() 276 NN_RET_CHECK(output.commit()); in l2Pool() 285 NN_RET_CHECK(input.initialize(inputData, inputShape)); in maxPool() 286 NN_RET_CHECK(output.initialize(outputData, outputShape)); in maxPool() [all …]
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D | Elementwise.cpp | 89 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validate() 92 NN_RET_CHECK(validateInputTypes(context, {inputType})); in validate() 93 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 101 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validateAbs() 104 NN_RET_CHECK(validateInputTypes(context, {inputType})); in validateAbs() 105 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validateAbs() 114 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validateFloor() 117 NN_RET_CHECK(validateInputTypes(context, {inputType})); in validateFloor() 118 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validateFloor() 131 NN_RET_CHECK(SetShape(input, &output)); in prepare() [all …]
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D | RoiAlign.cpp | 90 NN_RET_CHECK(roiInfo[0] >= 0); in roiAlignNhwc() 91 NN_RET_CHECK(roiInfo[1] >= 0); in roiAlignNhwc() 92 NN_RET_CHECK(roiInfo[2] >= 0); in roiAlignNhwc() 93 NN_RET_CHECK(roiInfo[3] >= 0); in roiAlignNhwc() 94 NN_RET_CHECK(roiInfo[0] * widthScale <= inWidth); in roiAlignNhwc() 95 NN_RET_CHECK(roiInfo[1] * heightScale <= inHeight); in roiAlignNhwc() 96 NN_RET_CHECK(roiInfo[2] * widthScale <= inWidth); in roiAlignNhwc() 97 NN_RET_CHECK(roiInfo[3] * heightScale <= inHeight); in roiAlignNhwc() 98 NN_RET_CHECK(roiInfo[0] <= roiInfo[2]); in roiAlignNhwc() 99 NN_RET_CHECK(roiInfo[1] <= roiInfo[3]); in roiAlignNhwc() [all …]
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D | LogicalAndOr.cpp | 48 NN_RET_CHECK(outputShapeIndexed.indexToFlatIndex(curIndex, &outputFlatIndex)); in compute() 50 NN_RET_CHECK(aShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &aFlatIndex)); in compute() 52 NN_RET_CHECK(bShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &bFlatIndex)); in compute() 56 NN_RET_CHECK(outputShapeIndexed.nextIndexInplace(&curIndex, &lastIndex)); in compute() 67 NN_RET_CHECK(inputType == OperandType::TENSOR_BOOL8) in validate() 69 NN_RET_CHECK(validateInputTypes(context, {inputType, inputType})); in validate() 70 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 78 NN_RET_CHECK(calculateBroadcastedShape(input1, input2, &output)); in prepare()
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D | ResizeImageOps.cpp | 145 NN_RET_CHECK(resizeImageOpNhwc(opType, inputData_float32.data(), inputShape, alignCorners, in resizeImageOpNhwc() 157 NN_RET_CHECK(input.initialize(inputData, inputShape)); in resizeImageOp() 158 NN_RET_CHECK(output.initialize(outputData, outputShape)); in resizeImageOp() 159 NN_RET_CHECK(resizeImageOpNhwc(opType, input.getNhwcBuffer(), input.getNhwcShape(), in resizeImageOp() 162 NN_RET_CHECK(output.commit()); in resizeImageOp() 180 NN_RET_CHECK(numInputs >= kNumInputs - 1 && numInputs <= kNumInputs + kNumOptionalInputs); in validate() 182 NN_RET_CHECK(numInputs >= kNumInputs && numInputs <= kNumInputs + kNumOptionalInputs); in validate() 191 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validate() 205 NN_RET_CHECK(scalarType == OperandType::FLOAT32); in validate() 207 NN_RET_CHECK(scalarType == OperandType::FLOAT16); in validate() [all …]
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D | TransposeConv2D.cpp | 210 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape, in transposeConvNhwc() 213 NN_RET_CHECK(QuantizeMultiplier(realMultiplier, &outputMultiplier, &exponent)); in transposeConvNhwc() 307 NN_RET_CHECK(input.initialize(inputData, inputShape)); in transposeConv() 308 NN_RET_CHECK(output.initialize(outputData, outputShape)); in transposeConv() 309 NN_RET_CHECK(transposeConvNhwc(input.getNhwcBuffer(), input.getNhwcShape(), filterData, in transposeConv() 312 NN_RET_CHECK(output.commit()); in transposeConv() 351 NN_RET_CHECK(GetQuantizedConvolutionMultipler( in transposeConvQuant8PerChannelNhwc() 354 NN_RET_CHECK(QuantizeMultiplier(realMultiplier[i], &outputMultiplier[i], &exponent)); in transposeConvQuant8PerChannelNhwc() 427 NN_RET_CHECK(input.initialize(inputData, inputShape)); in transposeConvQuant8PerChannel() 428 NN_RET_CHECK(output.initialize(outputData, outputShape)); in transposeConvQuant8PerChannel() [all …]
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D | GenerateProposals.cpp | 122 NN_RET_CHECK(bboxTransformFloat32(roi_float32.data(), roiShape, delta_float32.data(), in bboxTransformFloat16() 144 NN_RET_CHECK(bboxTransformFloat32(roi_float32.data(), roiShape, delta_float32.data(), in bboxTransformQuant() 166 NN_RET_CHECK(bboxTransformFloat32(roi_float32.data(), roiShape, delta_float32.data(), in bboxTransformQuant() 224 NN_RET_CHECK(validateInputTypes(context, inExpectedTypes)); in validate() 225 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 269 NN_RET_CHECK(context->setOutputShape(kOutputTensor, outputShape)); in prepare() 581 NN_RET_CHECK(context->setOutputShape(kOutputScoreTensor, scoresOutShape)); in boxWithNmsLimitWriteOutput() 585 NN_RET_CHECK(context->setOutputShape(kOutputRoiTensor, roiOutShape)); in boxWithNmsLimitWriteOutput() 589 NN_RET_CHECK(context->setOutputShape(kOutputClassTensor, classesOutShape)); in boxWithNmsLimitWriteOutput() 593 NN_RET_CHECK(context->setOutputShape(kOutputBatchesTensor, batchesOutShape)); in boxWithNmsLimitWriteOutput() [all …]
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D | PRelu.cpp | 56 NN_RET_CHECK(outputShapeIndexed.indexToFlatIndex(curIndex, &outputFlatIndex)); in eval() 58 NN_RET_CHECK(aShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &aFlatIndex)); in eval() 60 NN_RET_CHECK(bShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &bFlatIndex)); in eval() 64 NN_RET_CHECK(outputShapeIndexed.nextIndexInplace(&curIndex, &lastIndex)); in eval() 106 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validate() 111 NN_RET_CHECK(validateInputTypes(context, {inputType, inputType})); in validate() 112 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 124 NN_RET_CHECK(input.type == alpha.type); in prepare() 126 NN_RET_CHECK(calculateBroadcastedShape(input, alpha, &output)); in prepare()
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D | DepthwiseConv2D.cpp | 210 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape, in depthwiseConvNhwc() 213 NN_RET_CHECK(QuantizeMultiplier(real_multiplier, &output_multiplier, &exponent)); in depthwiseConvNhwc() 264 NN_RET_CHECK(depthwiseConvNhwc(unsignedInput.data(), inputShape, unsignedFilter.data(), in depthwiseConvNhwc() 312 NN_RET_CHECK(GetQuantizedConvolutionMultipler( in depthwiseConvQuant8PerChannelNhwc() 315 NN_RET_CHECK(QuantizeMultiplier(realMultiplier[i], &outputMultiplier[i], &exponent)); in depthwiseConvQuant8PerChannelNhwc() 382 NN_RET_CHECK(input.initialize(inputData, inputShape)); in depthwiseConv() 383 NN_RET_CHECK(output.initialize(outputData, outputShape)); in depthwiseConv() 384 NN_RET_CHECK(depthwiseConvNhwc(input.getNhwcBuffer(), input.getNhwcShape(), filterData, in depthwiseConv() 389 NN_RET_CHECK(output.commit()); in depthwiseConv() 405 NN_RET_CHECK(input.initialize(inputData, inputShape)); in depthwiseConvQuant8PerChannel() [all …]
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D | Conv2D.cpp | 243 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape, in convNhwc() 246 NN_RET_CHECK(QuantizeMultiplier(real_multiplier, &output_multiplier, &exponent)); in convNhwc() 296 NN_RET_CHECK(convNhwc(unsignedInput.data(), inputShape, unsignedFilter.data(), filterShape, in convNhwc() 341 NN_RET_CHECK(input.initialize(inputData, inputShape)); in conv() 342 NN_RET_CHECK(output.initialize(outputData, outputShape)); in conv() 343 NN_RET_CHECK(convNhwc(input.getNhwcBuffer(), input.getNhwcShape(), filterData, filterShape, in conv() 348 NN_RET_CHECK(output.commit()); in conv() 385 NN_RET_CHECK(GetQuantizedConvolutionMultipler( in convQuant8PerChannelNhwc() 388 NN_RET_CHECK(QuantizeMultiplier(realMultiplier[i], &outputMultiplier[i], &exponent)); in convQuant8PerChannelNhwc() 478 NN_RET_CHECK(GetQuantizedConvolutionMultipler( in convQuant8PerChannelNhwc() [all …]
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D | QuantizedLSTM.cpp | 263 NN_RET_CHECK(weightsScale != 0); in prepare() 278 NN_RET_CHECK(checkWeightsShape(inputToInputWeights, inputSize)); in prepare() 279 NN_RET_CHECK(checkWeightsShape(inputToForgetWeights, inputSize)); in prepare() 280 NN_RET_CHECK(checkWeightsShape(inputToCellWeights, inputSize)); in prepare() 281 NN_RET_CHECK(checkWeightsShape(inputToOutputWeights, inputSize)); in prepare() 287 NN_RET_CHECK(checkWeightsShape(recurrentToInputWeights, outputSize)); in prepare() 288 NN_RET_CHECK(checkWeightsShape(recurrentToForgetWeights, outputSize)); in prepare() 289 NN_RET_CHECK(checkWeightsShape(recurrentToCellWeights, outputSize)); in prepare() 290 NN_RET_CHECK(checkWeightsShape(recurrentToOutputWeights, outputSize)); in prepare() 309 NN_RET_CHECK(checkBiasShape(inputGateBias)); in prepare() [all …]
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D | Reduce.cpp | 77 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validateProdSum() 80 NN_RET_CHECK( in validateProdSum() 82 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validateProdSum() 94 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validateMaxMin() 99 NN_RET_CHECK( in validateMaxMin() 101 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validateMaxMin() 117 NN_RET_CHECK(inputType == OperandType::TENSOR_BOOL8) in validateLogical() 119 NN_RET_CHECK( in validateLogical() 121 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validateLogical() 142 NN_RET_CHECK(handleNegativeAxis(inputRank, &axis)); in prepare()
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D | UnidirectionalSequenceLSTM.cpp | 123 NN_RET_CHECK(numOutputs == kNumOutputs || numOutputs == kNumOutputsWithState); in validate() 169 NN_RET_CHECK(validateInputTypes(context, inExpectedTypes)); in validate() 170 NN_RET_CHECK(validateOutputTypes(context, outExpectedTypes)); in validate() 196 NN_RET_CHECK(!context->isOmittedInput(requiredInput)) in prepare() 256 NN_RET_CHECK(cifgWeightsAllOrNone); in prepare() 285 NN_RET_CHECK(peepholeWeightsAllOrNone); in prepare() 288 NN_RET_CHECK(hasTensor(context, kInputGateBiasTensor)); in prepare() 293 NN_RET_CHECK(!hasTensor(context, kInputGateBiasTensor)) in prepare() 354 NN_RET_CHECK(!hasTensor(context, kInputLayerNormWeightsTensor)) in prepare() 363 NN_RET_CHECK(layerNormWeightsAllOrNoneCifg); in prepare() [all …]
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D | FullyConnected.cpp | 122 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, weightsShape, biasShape, outputShape, in fullyConnectedQuant8() 125 NN_RET_CHECK(QuantizeMultiplier(realMultiplier, &outputMultiplier, &exponent)); in fullyConnectedQuant8() 160 NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, weightsShape, biasShape, outputShape, in fullyConnectedQuant8() 162 NN_RET_CHECK(QuantizeMultiplier(realMultiplier, &outputMultiplier, &outputShift)); in fullyConnectedQuant8() 189 NN_RET_CHECK(weights.type == input.type); in validateShapes() 192 NN_RET_CHECK(bias.type == OperandType::TENSOR_INT32); in validateShapes() 194 NN_RET_CHECK(bias.type == input.type); in validateShapes() 281 NN_RET_CHECK(validateInputTypes(context, inExpectedTypes)); in validate() 282 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 288 NN_RET_CHECK(validateShapes(input, weights, bias)); in validate() [all …]
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D | ChannelShuffle.cpp | 64 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validate() 73 NN_RET_CHECK(validateInputTypes(context, {inputType, OperandType::INT32, OperandType::INT32})); in validate() 74 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 86 NN_RET_CHECK(handleNegativeAxis(input, &axis)); in prepare() 87 NN_RET_CHECK(numGroups > 0); in prepare() 88 NN_RET_CHECK(getSizeOfDimension(input, axis) % numGroups == 0); in prepare() 95 NN_RET_CHECK(handleNegativeAxis(context->getInputShape(kInputTensor), &axis)); in execute()
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D | BidirectionalSequenceRNN.cpp | 143 NN_RET_CHECK(getLinkingMode(context, &linkingMode)); in executeTyped() 323 NN_RET_CHECK(numOutputs == kNumOutputs || numOutputs == kNumOutputsMerged || in validate() 331 NN_RET_CHECK(validateInputTypes( in validate() 337 NN_RET_CHECK(validateOutputTypes(context, outExpectedTypes)); in validate() 351 NN_RET_CHECK(numOutputs == kNumOutputsMerged || numOutputs == kNumOutputsMergedWithState); in prepare() 353 NN_RET_CHECK(numOutputs == kNumOutputs || numOutputs == kNumOutputsWithState); in prepare() 363 NN_RET_CHECK(!context->isOmittedInput(requiredInput)) in prepare() 382 NN_RET_CHECK(getLinkingMode(context, &linkingMode)); in prepare() 443 NN_RET_CHECK(context->setOutputShape(kFwOutputTensor, fwOutput)); in prepare() 450 NN_RET_CHECK(context->setOutputShape(kBwOutputTensor, bwOutput)); in prepare() [all …]
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D | Slice.cpp | 74 NN_RET_CHECK(indexedOutput.indexToFlatIndex(outputIndex, &outputOffset)); in evalGeneric() 75 NN_RET_CHECK(indexedInput.indexToFlatIndex(inputIndex, &inputOffset)); in evalGeneric() 78 NN_RET_CHECK(indexedOutput.nextIndexInplace(&outputIndex, &lastIndex)); in evalGeneric() 91 NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 || in validate() 103 NN_RET_CHECK(validateInputTypes( in validate() 105 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 113 NN_RET_CHECK(n_dims > 0); in prepare()
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D | InstanceNormalization.cpp | 96 NN_RET_CHECK(input.initialize(inputData, inputShape)); in instanceNorm() 97 NN_RET_CHECK(output.initialize(outputData, outputShape)); in instanceNorm() 98 NN_RET_CHECK(instanceNormNhwc(input.getNhwcBuffer(), input.getNhwcShape(), gamma, beta, epsilon, in instanceNorm() 100 NN_RET_CHECK(output.commit()); in instanceNorm() 121 NN_RET_CHECK(validateInputTypes(context, inExpectedTypes)); in validate() 122 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate()
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D | Comparisons.cpp | 50 NN_RET_CHECK(outputShapeIndexed.indexToFlatIndex(curIndex, &outputFlatIndex)); in compute() 52 NN_RET_CHECK(aShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &aFlatIndex)); in compute() 54 NN_RET_CHECK(bShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &bFlatIndex)); in compute() 65 NN_RET_CHECK(outputShapeIndexed.nextIndexInplace(&curIndex, &lastIndex)); in compute() 130 NN_RET_CHECK( in validate() 136 NN_RET_CHECK(validateInputTypes(context, {inputType, inputType})); in validate() 137 NN_RET_CHECK(validateOutputTypes(context, {OperandType::TENSOR_BOOL8})); in validate() 149 NN_RET_CHECK(calculateBroadcastedShape(input1, input2, &output)); in prepare()
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D | Transpose.cpp | 96 NN_RET_CHECK(validateInputTypes(context, {inputType, OperandType::TENSOR_INT32})); in validate() 97 NN_RET_CHECK(validateOutputTypes(context, {inputType})); in validate() 104 NN_RET_CHECK(!context->isOmittedInput(kInputTensor)); in prepare() 105 NN_RET_CHECK(!context->isOmittedOutput(kOutputTensor)); in prepare() 126 NN_RET_CHECK(permShape.type == OperandType::TENSOR_INT32); in prepare() 132 NN_RET_CHECK(permData[idx] >= 0 && permData[idx] < static_cast<int32_t>(numInputDims)); in prepare()
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/packages/modules/NeuralNetworks/runtime/ |
D | Memory.cpp | 53 NN_RET_CHECK(offset + length <= kSize) << "request size larger than the memory size."; in validate() 54 NN_RET_CHECK(offset != 0 || length != 0) << "memory size cannot be implied."; in validate() 77 NN_RET_CHECK(compilation != nullptr) in validate() 79 NN_RET_CHECK(offset == 0 && length == 0) in validate() 104 NN_RET_CHECK(kCompilationRoles.count({compilation, ioType, index}) > 0) in validate() 106 NN_RET_CHECK(offset == 0 && length == 0) in validate() 110 NN_RET_CHECK(isTensor || type->dimensionCount == 0) in validate() 118 NN_RET_CHECK(combined.has_value()) in validate() 126 NN_RET_CHECK(mInitialized) << "using an uninitialized memory as input"; in validateInputDimensions() 127 NN_RET_CHECK(dimensions == mUpdatedDimensions) in validateInputDimensions() [all …]
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