| /frameworks/ml/nn/common/operations/ |
| D | QuantizedLSTMTest.cpp | 59 const uint32_t numBatches = inputOperandTypeParams[0].shape[0]; in QuantizedLSTMOpModel() local
66 OperandType cellStateOutOperandType(Type::TENSOR_QUANT16_SYMM, {numBatches, outputSize}, in QuantizedLSTMOpModel()
69 OperandType outputOperandType(Type::TENSOR_QUANT8_ASYMM, {numBatches, outputSize}, in QuantizedLSTMOpModel()
82 cellStateOut_.resize(numBatches * outputSize, 0); in QuantizedLSTMOpModel()
83 output_.resize(numBatches * outputSize, 0); in QuantizedLSTMOpModel()
239 const int numBatches = input.size(); in VerifyGoldens() local
240 EXPECT_GT(numBatches, 0); in VerifyGoldens()
247 for (int b = 0; b < numBatches; ++b) { in VerifyGoldens()
257 for (int b = 0; b < numBatches; ++b) { in VerifyGoldens()
271 const int numBatches = 2; in TEST_F() local
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| D | RoiAlign.cpp | 68 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in roiAlignNhwc() local
87 NN_RET_CHECK_LT(batchId, numBatches); in roiAlignNhwc()
195 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in roiAlignQuantNhwc() local
219 NN_RET_CHECK_LT(batchId, numBatches); in roiAlignQuantNhwc()
392 uint32_t numBatches = getSizeOfDimension(input, 0); in prepare() local
398 NN_RET_CHECK_GT(numBatches, 0); in prepare()
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| D | TransposeConv2D.cpp | 111 uint32_t numBatches = getSizeOfDimension(inputShape, 0); \
139 for (uint32_t b = 0; b < numBatches; b++) { in transposeConvNhwc()
169 const uint32_t outerSize = numBatches * outputHeight * outputWidth; in transposeConvNhwc()
225 for (uint32_t b = 0; b < numBatches; b++) { in transposeConvNhwc()
260 const uint32_t outerSize = numBatches * outputHeight * outputWidth; in transposeConvNhwc()
367 for (uint32_t b = 0; b < numBatches; b++) { in transposeConvQuant8PerChannelNhwc()
401 const uint32_t outerSize = numBatches * outputHeight * outputWidth; in transposeConvQuant8PerChannelNhwc()
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| D | InstanceNormalization.cpp | 51 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in instanceNormNhwc() local
55 for (uint32_t b = 0; b < numBatches; b++) { in instanceNormNhwc()
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| D | GroupedConv2D.cpp | 34 uint32_t numBatches = getSizeOfDimension(inputShape, 0); \
60 for (uint32_t b = 0; b < numBatches; b++) { in groupedConvFloat32()
132 for (uint32_t b = 0; b < numBatches; b++) { in groupedConvQuant8()
236 for (uint32_t b = 0; b < numBatches; b++) { in groupedConvQuant8PerChannel()
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| D | GenerateProposals.cpp | 68 uint32_t numBatches = getSizeOfDimension(imageInfoDataShape, 0); in bboxTransformFloat32() local
80 NN_RET_CHECK_LT(batchIndex, numBatches); in bboxTransformFloat32()
245 uint32_t numBatches = getSizeOfDimension(imageInfoShape, 0); in prepare() local
247 NN_RET_CHECK_GT(numBatches, 0); in prepare()
962 uint32_t numBatches = getSizeOfDimension(scoresShape, 0); in generateProposalsNhwcFloat32Compute() local
1005 for (uint32_t b = 0; b < numBatches; b++) { in generateProposalsNhwcFloat32Compute()
1296 uint32_t numBatches = getSizeOfDimension(scoreShape, 0); in prepare() local
1301 NN_RET_CHECK_EQ(getSizeOfDimension(bboxDeltasShape, 0), numBatches); in prepare()
1305 NN_RET_CHECK_EQ(getSizeOfDimension(imageInfoDataShape, 0), numBatches); in prepare()
1449 uint32_t numBatches = getSizeOfDimension(scoreShape, 0); in detectionPostprocessFloat32() local
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| D | RoiPooling.cpp | 64 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in roiPoolingNhwc() local
83 NN_RET_CHECK_LT(batchId, numBatches); in roiPoolingNhwc()
237 uint32_t numBatches = getSizeOfDimension(input, 0); in prepare() local
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| D | QuantizedLSTM.cpp | 254 const uint32_t numBatches = SizeOfDimension(input, 0); in prepare() local
259 NN_RET_CHECK_EQ(SizeOfDimension(prevOutput, 0), numBatches); in prepare()
319 NN_CHECK_EQ(SizeOfDimension(prevCellState, 0), numBatches); in prepare()
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| D | Conv2D.cpp | 361 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in convQuant8PerChannelNhwc() local
396 for (uint32_t b = 0; b < numBatches; b++) { in convQuant8PerChannelNhwc()
454 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in convQuant8PerChannelNhwc() local
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| D | DepthwiseConv2D.cpp | 287 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in depthwiseConvQuant8PerChannelNhwc() local
323 for (uint32_t b = 0; b < numBatches; b++) { in depthwiseConvQuant8PerChannelNhwc()
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| /frameworks/ml/nn/runtime/test/ |
| D | TestValidateOperations.cpp | 3491 const int numBatches = 2; in detectionPostprocessingOpTest() local
3496 uint32_t inputDims[3] = {numBatches, numAnchors, numClasses}; in detectionPostprocessingOpTest()
3498 uint32_t deltasDims[3] = {numBatches, numAnchors, lengthBoxEncoding}; in detectionPostprocessingOpTest()
3515 uint32_t outputScoreDims[2] = {numBatches, maxNumDetectionsValue}; in detectionPostprocessingOpTest()
3517 uint32_t boundingBoxesDims[3] = {numBatches, maxNumDetectionsValue, 4}; in detectionPostprocessingOpTest()
3521 uint32_t numValidDims[1] = {numBatches}; in detectionPostprocessingOpTest()
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| /frameworks/base/services/core/java/com/android/server/ |
| D | AlarmManagerService.java | 1028 final int numBatches = batches.size(); in haveBatchesTimeTickAlarm() local
1029 for (int i = 0; i < numBatches; i++) { in haveBatchesTimeTickAlarm()
3757 final int numBatches = batches.size(); in recordWakeupAlarms() local
3758 for (int nextBatch = 0; nextBatch < numBatches; nextBatch++) { in recordWakeupAlarms()
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| /frameworks/ml/nn/tools/api/ |
| D | types.spec | 4871 * and shape [numBatches, inputSize] specifying the input to the LSTM
4943 * and shape [numBatches, outputSize] specifying the cell state from the
4956 * and shape [numBatches, outputSize] which contains a cell state from
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