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Searched refs:numInputDims (Results 1 – 5 of 5) sorted by relevance

/packages/modules/NeuralNetworks/common/operations/
DStridedSlice.cpp65 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(inputShape)); in compute() local
66 for (int32_t idx = numInputDims - 1; idx >= 0; --idx) { in compute()
72 for (int i = numInputDims; i < kMaxDim; i++) { in compute()
78 beginMask = ReverseMaskBits(beginMask, numInputDims); in compute()
79 endMask = ReverseMaskBits(endMask, numInputDims); in compute()
80 shrinkAxisMask = ReverseMaskBits(shrinkAxisMask, numInputDims); in compute()
144 uint32_t numInputDims = getNumberOfDimensions(inputShape); in prepare() local
145 NN_OPS_CHECK(numInputDims <= 4); in prepare()
155 NN_OPS_CHECK(getSizeOfDimension(beginShape, 0) == numInputDims); in prepare()
156 NN_OPS_CHECK(getSizeOfDimension(endShape, 0) == numInputDims); in prepare()
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DSqueeze.cpp78 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(inputShape)); in prepare() local
86 std::vector<bool> shouldSqueeze(numInputDims, false); in prepare()
91 for (int32_t idx = 0; idx < numInputDims; ++idx) { in prepare()
101 squeezeDims[idx] < 0 ? squeezeDims[idx] + numInputDims : squeezeDims[idx]; in prepare()
102 NN_OPS_CHECK(current >= 0 && current < numInputDims && in prepare()
110 std::vector<uint32_t> outDims(numInputDims - numDimsSqueezed); in prepare()
111 if (numInputDims == numDimsSqueezed) { in prepare()
115 for (int32_t inIdx = 0, outIdx = 0; inIdx < numInputDims; ++inIdx) { in prepare()
DTranspose.cpp108 uint32_t numInputDims = getNumberOfDimensions(input); in prepare() local
116 NN_RET_CHECK_EQ(numInputDims, 2); in prepare()
123 NN_RET_CHECK_LE(numInputDims, 4); in prepare()
128 NN_RET_CHECK_EQ(numInputDims, getSizeOfDimension(permShape, 0)); in prepare()
130 std::vector<uint32_t> outDims(numInputDims); in prepare()
131 for (int32_t idx = 0; idx < static_cast<int32_t>(numInputDims); ++idx) { in prepare()
132 NN_RET_CHECK(permData[idx] >= 0 && permData[idx] < static_cast<int32_t>(numInputDims)); in prepare()
DReshape.cpp94 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(inputShape)); in padGeneric() local
95 NN_OPS_CHECK(numInputDims <= 4); in padGeneric()
96 std::vector<int> leftPaddings(4 - numInputDims, 0); in padGeneric()
97 std::vector<int> rightPaddings(4 - numInputDims, 0); in padGeneric()
98 for (int32_t i = 0; i < numInputDims; ++i) { in padGeneric()
/packages/modules/NeuralNetworks/common/
DOperationsUtils.cpp503 uint32_t numInputDims = getNumberOfDimensions(input); in padPrepare() local
508 NN_OPS_CHECK(getSizeOfDimension(paddingsShape, 0) == numInputDims); in padPrepare()
511 std::vector<uint32_t> outDims(numInputDims); in padPrepare()
512 for (uint32_t i = 0; i < numInputDims; ++i) { in padPrepare()
598 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(input)); in meanPrepare() local
603 std::vector<uint32_t> outDims(numInputDims); in meanPrepare()
604 for (int32_t idx = 0; idx < numInputDims; ++idx) { in meanPrepare()
607 if (axisData[axisIdx] == idx || axisData[axisIdx] + numInputDims == idx) { in meanPrepare()
625 current += numInputDims; in meanPrepare()
627 NN_OPS_CHECK(current >= 0 && current < numInputDims); in meanPrepare()
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