/aosp12/packages/modules/NeuralNetworks/common/operations/ |
H A D | BidirectionalSequenceRNN.cpp | 222 auxInputSize = getSizeOfDimension(auxInputShape, 2); in executeTyped() 386 timeMajor ? getSizeOfDimension(input, 1) : getSizeOfDimension(input, 0); in prepare() 388 timeMajor ? getSizeOfDimension(input, 0) : getSizeOfDimension(input, 1); in prepare() 391 const uint32_t inputSize = getSizeOfDimension(input, 2); in prepare() 424 NN_RET_CHECK_EQ(getSizeOfDimension(auxInput, 0), getSizeOfDimension(input, 0)); in prepare() 425 NN_RET_CHECK_EQ(getSizeOfDimension(auxInput, 1), getSizeOfDimension(input, 1)); in prepare() 427 NN_RET_CHECK_EQ(getSizeOfDimension(fwAuxWeights, 1), getSizeOfDimension(auxInput, 2)); in prepare() 429 NN_RET_CHECK_EQ(getSizeOfDimension(bwAuxWeights, 1), getSizeOfDimension(auxInput, 2)); in prepare() 433 NN_RET_CHECK_EQ(getSizeOfDimension(auxInput, 0), getSizeOfDimension(input, 0)); in prepare() 434 NN_RET_CHECK_EQ(getSizeOfDimension(auxInput, 1), getSizeOfDimension(input, 1)); in prepare() [all …]
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H A D | UnidirectionalSequenceLSTM.cpp | 210 NN_RET_CHECK_EQ(getSizeOfDimension(inputToOutputShape, 1), inputSize); in prepare() 211 const uint32_t numCells = getSizeOfDimension(inputToOutputShape, 0); in prepare() 227 NN_RET_CHECK_EQ(getSizeOfDimension(inputToForgetShape, 0), numCells); in prepare() 228 NN_RET_CHECK_EQ(getSizeOfDimension(inputToForgetShape, 1), inputSize); in prepare() 231 NN_RET_CHECK_EQ(getSizeOfDimension(inputToCellShape, 0), numCells); in prepare() 232 NN_RET_CHECK_EQ(getSizeOfDimension(inputToCellShape, 1), inputSize); in prepare() 302 NN_RET_CHECK_EQ(getSizeOfDimension(cellGateBiasShape, 0), numCells); in prepare() 322 NN_RET_CHECK_EQ(getSizeOfDimension(outputStateShape, 0), batchSize); in prepare() 323 NN_RET_CHECK_EQ(getSizeOfDimension(outputStateShape, 1), outputSize); in prepare() 326 NN_RET_CHECK_EQ(getSizeOfDimension(cellStateShape, 0), batchSize); in prepare() [all …]
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H A D | UnidirectionalSequenceRNN.cpp | 50 const uint32_t firstDimSize = getSizeOfDimension(inputShape, 0); in transposeFirstTwoDims() 52 const uint32_t inputSize = getSizeOfDimension(inputShape, 2); in transposeFirstTwoDims() 96 const uint32_t maxTime = getSizeOfDimension(inputShape, 0); in executeTyped() 97 const uint32_t batchSize = getSizeOfDimension(inputShape, 1); in executeTyped() 98 const uint32_t inputSize = getSizeOfDimension(inputShape, 2); in executeTyped() 163 timeMajor ? getSizeOfDimension(input, 1) : getSizeOfDimension(input, 0); in prepare() 165 timeMajor ? getSizeOfDimension(input, 0) : getSizeOfDimension(input, 1); in prepare() 166 const uint32_t numUnits = getSizeOfDimension(weights, 0); in prepare() 167 const uint32_t inputSize = getSizeOfDimension(input, 2); in prepare() 175 NN_RET_CHECK_EQ(inputSize, getSizeOfDimension(weights, 1)); in prepare() [all …]
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H A D | Conv2D.cpp | 362 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in convQuant8PerChannelNhwc() 363 uint32_t inputHeight = getSizeOfDimension(inputShape, 1); in convQuant8PerChannelNhwc() 364 uint32_t inputWidth = getSizeOfDimension(inputShape, 2); in convQuant8PerChannelNhwc() 365 uint32_t inputDepth = getSizeOfDimension(inputShape, 3); in convQuant8PerChannelNhwc() 455 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in convQuant8PerChannelNhwc() 457 uint32_t inputWidth = getSizeOfDimension(inputShape, 2); in convQuant8PerChannelNhwc() 458 uint32_t inputDepth = getSizeOfDimension(inputShape, 3); in convQuant8PerChannelNhwc() 660 uint32_t batches = getSizeOfDimension(input, 0); in prepare() 664 uint32_t channels_out = getSizeOfDimension(filter, 0); in prepare() 665 uint32_t filterHeight = getSizeOfDimension(filter, 1); in prepare() [all …]
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H A D | QLSTM.cpp | 183 const uint32_t batchSize = getSizeOfDimension(inputShape, 0); in prepare() 184 const uint32_t inputSize = getSizeOfDimension(inputShape, 1); in prepare() 188 NN_RET_CHECK_EQ(getSizeOfDimension(inputToOutputShape, 1), inputSize); in prepare() 189 const uint32_t numUnits = getSizeOfDimension(inputToOutputShape, 0); in prepare() 205 NN_RET_CHECK_EQ(getSizeOfDimension(inputToForgetShape, 0), numUnits); in prepare() 209 NN_RET_CHECK_EQ(getSizeOfDimension(inputToCellShape, 0), numUnits); in prepare() 210 NN_RET_CHECK_EQ(getSizeOfDimension(inputToCellShape, 1), inputSize); in prepare() 280 NN_RET_CHECK_EQ(getSizeOfDimension(cellGateBiasShape, 0), numUnits); in prepare() 300 NN_RET_CHECK_EQ(getSizeOfDimension(outputStateShape, 0), batchSize); in prepare() 304 NN_RET_CHECK_EQ(getSizeOfDimension(cellStateShape, 0), batchSize); in prepare() [all …]
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H A D | RoiAlign.cpp | 70 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in roiAlignNhwc() 71 uint32_t inHeight = getSizeOfDimension(inputShape, 1); in roiAlignNhwc() 72 uint32_t inWidth = getSizeOfDimension(inputShape, 2); in roiAlignNhwc() 73 uint32_t inDepth = getSizeOfDimension(inputShape, 3); in roiAlignNhwc() 75 uint32_t outWidth = getSizeOfDimension(outputShape, 2); in roiAlignNhwc() 76 uint32_t numRois = getSizeOfDimension(roiShape, 0); in roiAlignNhwc() 199 uint32_t inWidth = getSizeOfDimension(inputShape, 2); in roiAlignQuantNhwc() 200 uint32_t inDepth = getSizeOfDimension(inputShape, 3); in roiAlignQuantNhwc() 203 uint32_t numRois = getSizeOfDimension(roiShape, 0); in roiAlignQuantNhwc() 395 uint32_t numBatches = getSizeOfDimension(input, 0); in prepare() [all …]
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H A D | DepthwiseConv2D.cpp | 289 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in depthwiseConvQuant8PerChannelNhwc() 290 uint32_t inputHeight = getSizeOfDimension(inputShape, 1); in depthwiseConvQuant8PerChannelNhwc() 291 uint32_t inputWidth = getSizeOfDimension(inputShape, 2); in depthwiseConvQuant8PerChannelNhwc() 292 uint32_t inputDepth = getSizeOfDimension(inputShape, 3); in depthwiseConvQuant8PerChannelNhwc() 294 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); in depthwiseConvQuant8PerChannelNhwc() 539 NN_RET_CHECK_EQ(getSizeOfDimension(filter, 0), 1); in prepare() 540 NN_RET_CHECK_EQ(getSizeOfDimension(filter, 3), getSizeOfDimension(bias, 0)); in prepare() 545 uint32_t batches = getSizeOfDimension(input, 0); in prepare() 549 uint32_t channels_out = getSizeOfDimension(filter, 3); in prepare() 550 uint32_t filterHeight = getSizeOfDimension(filter, 1); in prepare() [all …]
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H A D | RoiPooling.cpp | 65 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in roiPoolingNhwc() 66 uint32_t inHeight = getSizeOfDimension(inputShape, 1); in roiPoolingNhwc() 67 uint32_t inWidth = getSizeOfDimension(inputShape, 2); in roiPoolingNhwc() 68 uint32_t inDepth = getSizeOfDimension(inputShape, 3); in roiPoolingNhwc() 69 uint32_t outHeight = getSizeOfDimension(outputShape, 1); in roiPoolingNhwc() 70 uint32_t outWidth = getSizeOfDimension(outputShape, 2); in roiPoolingNhwc() 71 uint32_t numRois = getSizeOfDimension(roiShape, 0); in roiPoolingNhwc() 72 uint32_t roiInfoLength = getSizeOfDimension(roiShape, 1); in roiPoolingNhwc() 238 uint32_t numBatches = getSizeOfDimension(input, 0); in prepare() 242 uint32_t numRois = getSizeOfDimension(roiShape, 0); in prepare() [all …]
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H A D | TransposeConv2D.cpp | 76 int32_t filterWidth = getSizeOfDimension(filterShape, 2); in initialize() 77 int32_t filterHeight = getSizeOfDimension(filterShape, 1); in initialize() 79 NN_RET_CHECK_EQ(getSizeOfDimension(context->getInputShape(3), 0), 4); in initialize() 512 uint32_t batches = getSizeOfDimension(input, 0); in prepare() 513 uint32_t height = getSizeOfDimension(input, param.useNchw ? 2 : 1); in prepare() 514 uint32_t width = getSizeOfDimension(input, param.useNchw ? 3 : 2); in prepare() 516 uint32_t channels_out = getSizeOfDimension(filter, 0); in prepare() 517 uint32_t filterHeight = getSizeOfDimension(filter, 1); in prepare() 518 uint32_t filterWidth = getSizeOfDimension(filter, 2); in prepare() 520 NN_RET_CHECK_EQ(channels_in, getSizeOfDimension(filter, 3)); in prepare() [all …]
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H A D | ResizeImageOps.cpp | 70 const int batchSize = getSizeOfDimension(inputShape, 0); in resizeNearestNeighbor() 71 const int inHeight = getSizeOfDimension(inputShape, 1); in resizeNearestNeighbor() 72 const int inWidth = getSizeOfDimension(inputShape, 2); in resizeNearestNeighbor() 73 const int channels = getSizeOfDimension(inputShape, 3); in resizeNearestNeighbor() 74 const int outHeight = getSizeOfDimension(outputShape, 1); in resizeNearestNeighbor() 75 const int outWidth = getSizeOfDimension(outputShape, 2); in resizeNearestNeighbor() 116 int32_t width = static_cast<int32_t>(getSizeOfDimension(outputShape, 2)); in resizeImageOpNhwc() 241 uint32_t batches = getSizeOfDimension(input, 0); in prepare() 242 uint32_t inHeight = getSizeOfDimension(input, useNchw ? 2 : 1); in prepare() 243 uint32_t inWidth = getSizeOfDimension(input, useNchw ? 3 : 2); in prepare() [all …]
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H A D | GenerateProposals.cpp | 244 uint32_t numRois = getSizeOfDimension(roiShape, 0); in prepare() 249 NN_RET_CHECK_EQ(getSizeOfDimension(roiShape, 1), kRoiDim); in prepare() 253 NN_RET_CHECK_EQ(getSizeOfDimension(imageInfoShape, 1), 2); in prepare() 508 uint32_t numRois = getSizeOfDimension(scoresShape, 0); in boxWithNmsLimitFloat32Compute() 509 uint32_t numClasses = getSizeOfDimension(scoresShape, 1); in boxWithNmsLimitFloat32Compute() 574 uint32_t numClasses = getSizeOfDimension(scoresShape, 1); in boxWithNmsLimitWriteOutput() 774 uint32_t numRois = getSizeOfDimension(scoreShape, 0); in prepare() 775 uint32_t numClasses = getSizeOfDimension(scoreShape, 1); in prepare() 970 uint32_t height = getSizeOfDimension(scoresShape, 1); in generateProposalsNhwcFloat32Compute() 971 uint32_t width = getSizeOfDimension(scoresShape, 2); in generateProposalsNhwcFloat32Compute() [all …]
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H A D | GroupedConv2D.cpp | 34 uint32_t numBatches = getSizeOfDimension(inputShape, 0); \ 35 uint32_t inputHeight = getSizeOfDimension(inputShape, 1); \ 36 uint32_t inputWidth = getSizeOfDimension(inputShape, 2); \ 37 uint32_t inputDepth = getSizeOfDimension(inputShape, 3); \ 38 uint32_t filterHeight = getSizeOfDimension(filterShape, 1); \ 39 uint32_t filterWidth = getSizeOfDimension(filterShape, 2); \ 40 uint32_t filterDepth = getSizeOfDimension(filterShape, 3); \ 41 uint32_t outputHeight = getSizeOfDimension(outputShape, 1); \ 42 uint32_t outputWidth = getSizeOfDimension(outputShape, 2); \ 43 uint32_t outputDepth = getSizeOfDimension(outputShape, 3); \
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H A D | HeatmapMaxKeypoint.cpp | 97 uint32_t numBoxes = getSizeOfDimension(heatmapShape, 0); in heatmapMaxKeypointFloat32Nhwc() 98 uint32_t heatmapSize = getSizeOfDimension(heatmapShape, 1); in heatmapMaxKeypointFloat32Nhwc() 99 uint32_t numKeypoints = getSizeOfDimension(heatmapShape, 3); in heatmapMaxKeypointFloat32Nhwc() 100 uint32_t boxInfoLength = getSizeOfDimension(boxesShape, 1); in heatmapMaxKeypointFloat32Nhwc() 268 uint32_t numBoxes = getSizeOfDimension(heatmapShape, 0); in prepare() 269 uint32_t heatmapSize = getSizeOfDimension(heatmapShape, 2); in prepare() 270 uint32_t numKeypoints = getSizeOfDimension(heatmapShape, layout ? 1 : 3); in prepare() 271 uint32_t boxInfoLength = getSizeOfDimension(boxesShape, 1); in prepare() 272 NN_RET_CHECK_EQ(getSizeOfDimension(heatmapShape, layout ? 3 : 1), heatmapSize); in prepare() 274 NN_RET_CHECK_EQ(getSizeOfDimension(boxesShape, 0), numBoxes); in prepare()
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H A D | Slice.cpp | 60 std::vector<uint32_t> beginIndex(getSizeOfDimension(beginShape, 0)); in evalGeneric() 117 NN_RET_CHECK_EQ(getSizeOfDimension(beginShape, 0), n_dims); in prepare() 121 NN_RET_CHECK_EQ(getSizeOfDimension(sizeShape, 0), n_dims); in prepare() 132 sliceSize = getSizeOfDimension(inputShape, i) - sliceBegin; in prepare() 134 NN_RET_CHECK_LE(beginData[i], getSizeOfDimension(inputShape, i)); in prepare() 136 NN_RET_CHECK_LE(sliceBegin + sliceSize, getSizeOfDimension(inputShape, i)); in prepare()
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H A D | Transpose.cpp | 56 int32_t permSize = perm == nullptr ? 2 : static_cast<int32_t>(getSizeOfDimension(permShape, 0)); in transposeGeneric() 117 output.dimensions = {getSizeOfDimension(input, 1), getSizeOfDimension(input, 0)}; in prepare() 128 NN_RET_CHECK_EQ(numInputDims, getSizeOfDimension(permShape, 0)); in prepare() 133 outDims[idx] = getSizeOfDimension(input, permData[idx]); in prepare()
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H A D | Squeeze.cpp | 92 if (getSizeOfDimension(inputShape, idx) == 1) { in prepare() 98 int32_t squeezeDimsSize = static_cast<int32_t>(getSizeOfDimension(squeezeDimsShape, 0)); in prepare() 103 getSizeOfDimension(inputShape, current) == 1); in prepare() 117 outDims[outIdx++] = getSizeOfDimension(inputShape, inIdx); in prepare()
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H A D | InstanceNormalization.cpp | 52 uint32_t numBatches = getSizeOfDimension(inputShape, 0); in instanceNormNhwc() 53 uint32_t height = getSizeOfDimension(inputShape, 1); in instanceNormNhwc() 54 uint32_t width = getSizeOfDimension(inputShape, 2); in instanceNormNhwc() 55 uint32_t depth = getSizeOfDimension(inputShape, 3); in instanceNormNhwc()
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H A D | StridedSlice.cpp | 155 NN_OPS_CHECK(getSizeOfDimension(beginShape, 0) == numInputDims); in prepare() 156 NN_OPS_CHECK(getSizeOfDimension(endShape, 0) == numInputDims); in prepare() 157 NN_OPS_CHECK(getSizeOfDimension(stridesShape, 0) == numInputDims); in prepare() 174 int32_t dim = static_cast<int32_t>(getSizeOfDimension(inputShape, idx)); in prepare()
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H A D | Concatenation.cpp | 192 uint32_t sumAxis = getSizeOfDimension(input0, axis); in prepare() 199 sumAxis += getSizeOfDimension(input, axis); in prepare() 201 NN_RET_CHECK_EQ(getSizeOfDimension(input0, d), getSizeOfDimension(input, d)); in prepare()
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H A D | LSTM.cpp | 433 (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 0 : 1) : 1; in LSTMEvalFloat32() 434 const uint32_t batchSize = (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 1 : 0) in LSTMEvalFloat32() 435 : getSizeOfDimension(input_shape, 0); in LSTMEvalFloat32() 436 const uint32_t inputSize = getSizeOfDimension(input_shape, inputRank - 1); in LSTMEvalFloat32() 437 const uint32_t numCells = getSizeOfDimension(input_to_output_weights_shape, 0); in LSTMEvalFloat32() 438 const uint32_t outputSize = getSizeOfDimension(recurrent_to_output_weights_shape, 1); in LSTMEvalFloat32() 553 (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 0 : 1) : 1; in LSTMEvalFloat16() 555 : getSizeOfDimension(input_shape, 0); in LSTMEvalFloat16() 556 const uint32_t inputSize = getSizeOfDimension(input_shape, inputRank - 1); in LSTMEvalFloat16() 557 const uint32_t numCells = getSizeOfDimension(input_to_output_weights_shape, 0); in LSTMEvalFloat16() [all …]
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H A D | Pooling.cpp | 82 int32_t input_height = getSizeOfDimension(inputShape, useNchw ? 2 : 1); in initialize() 83 int32_t input_width = getSizeOfDimension(inputShape, useNchw ? 3 : 2); in initialize() 369 uint32_t batches = getSizeOfDimension(input, 0); in prepare() 370 uint32_t height = getSizeOfDimension(input, param.useNchw ? 2 : 1); in prepare() 371 uint32_t width = getSizeOfDimension(input, param.useNchw ? 3 : 2); in prepare() 372 uint32_t channels = getSizeOfDimension(input, param.useNchw ? 1 : 3); in prepare()
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H A D | FullyConnected.cpp | 66 uint32_t batch_size = getSizeOfDimension(outputShape, 0); in fullyConnectedFloat32() 203 uint32_t num_units = getSizeOfDimension(weights, 0); in validateShapes() 204 uint32_t input_size = getSizeOfDimension(weights, 1); in validateShapes() 205 uint32_t bias_len = getSizeOfDimension(bias, 0); in validateShapes()
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H A D | L2Normalization.cpp | 53 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in l2normFloat32Impl() 80 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in l2normQuant8Impl() 112 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in l2normQuant8SignedImpl() 192 const int32_t axisSize = getSizeOfDimension(inputShape, axis); in l2normQuant8Signed()
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H A D | ChannelShuffle.cpp | 41 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in eval() 88 NN_RET_CHECK(getSizeOfDimension(input, axis) % numGroups == 0); in prepare()
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/aosp12/packages/modules/NeuralNetworks/common/ |
H A D | OperationsUtils.cpp | 425 uint32_t height = getSizeOfDimension(input, 1); in depthToSpacePrepare() 426 uint32_t width = getSizeOfDimension(input, 2); in depthToSpacePrepare() 444 uint32_t height = getSizeOfDimension(input, 1); in spaceToDepthPrepare() 445 uint32_t width = getSizeOfDimension(input, 2); in spaceToDepthPrepare() 539 uint32_t height = getSizeOfDimension(input, 1); in batchToSpacePrepare() 540 uint32_t width = getSizeOfDimension(input, 2); in batchToSpacePrepare() 572 uint32_t height = getSizeOfDimension(input, 1); in spaceToBatchPrepare() 573 uint32_t width = getSizeOfDimension(input, 2); in spaceToBatchPrepare() 727 NN_OPS_CHECK(getSizeOfDimension(filter, 0) == getSizeOfDimension(bias, 0)); in groupedConvPrepare() 729 NN_OPS_CHECK(getSizeOfDimension(filter, 3) * numGroups == getSizeOfDimension(input, 3)); in groupedConvPrepare() [all …]
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