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

/packages/modules/NeuralNetworks/common/cpu_operations/
DStridedSlice.cpp59 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(inputShape)); in compute() local
60 for (int32_t idx = numInputDims - 1; idx >= 0; --idx) { in compute()
66 for (int i = numInputDims; i < kMaxDim; i++) { in compute()
72 beginMask = ReverseMaskBits(beginMask, numInputDims); in compute()
73 endMask = ReverseMaskBits(endMask, numInputDims); in compute()
74 shrinkAxisMask = ReverseMaskBits(shrinkAxisMask, numInputDims); in compute()
100 uint32_t numInputDims = getNumberOfDimensions(inputShape); in prepare() local
101 NN_OPS_CHECK(numInputDims <= 4); in prepare()
111 NN_OPS_CHECK(getSizeOfDimension(beginShape, 0) == numInputDims); in prepare()
112 NN_OPS_CHECK(getSizeOfDimension(endShape, 0) == numInputDims); in prepare()
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DSqueeze.cpp42 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(inputShape)); in prepare() local
50 std::vector<bool> shouldSqueeze(numInputDims, false); in prepare()
55 for (int32_t idx = 0; idx < numInputDims; ++idx) { in prepare()
65 squeezeDims[idx] < 0 ? squeezeDims[idx] + numInputDims : squeezeDims[idx]; in prepare()
66 NN_OPS_CHECK(current >= 0 && current < numInputDims && in prepare()
74 std::vector<uint32_t> outDims(numInputDims - numDimsSqueezed); in prepare()
75 if (numInputDims == numDimsSqueezed) { in prepare()
79 for (int32_t inIdx = 0, outIdx = 0; inIdx < numInputDims; ++inIdx) { in prepare()
DTranspose.cpp80 uint32_t numInputDims = getNumberOfDimensions(input); in prepare() local
88 NN_RET_CHECK_EQ(numInputDims, 2u); in prepare()
95 NN_RET_CHECK_LE(numInputDims, 4u); in prepare()
100 NN_RET_CHECK_EQ(numInputDims, getSizeOfDimension(permShape, 0)); in prepare()
102 std::vector<uint32_t> outDims(numInputDims); in prepare()
103 for (int32_t idx = 0; idx < static_cast<int32_t>(numInputDims); ++idx) { in prepare()
104 NN_RET_CHECK(permData[idx] >= 0 && permData[idx] < static_cast<int32_t>(numInputDims)); in prepare()
DReshape.cpp100 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(inputShape)); in padGeneric() local
101 NN_OPS_CHECK(numInputDims <= 4); in padGeneric()
102 std::vector<int> leftPaddings(4 - numInputDims, 0); in padGeneric()
103 std::vector<int> rightPaddings(4 - numInputDims, 0); in padGeneric()
104 for (int32_t i = 0; i < numInputDims; ++i) { in padGeneric()
/packages/modules/NeuralNetworks/common/
DOperationsExecutionUtils.cpp412 uint32_t numInputDims = getNumberOfDimensions(input); in padPrepare() local
417 NN_OPS_CHECK(getSizeOfDimension(paddingsShape, 0) == numInputDims); in padPrepare()
420 std::vector<uint32_t> outDims(numInputDims); in padPrepare()
421 for (uint32_t i = 0; i < numInputDims; ++i) { in padPrepare()
507 int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(input)); in meanPrepare() local
512 std::vector<uint32_t> outDims(numInputDims); in meanPrepare()
513 for (int32_t idx = 0; idx < numInputDims; ++idx) { in meanPrepare()
516 if (axisData[axisIdx] == idx || axisData[axisIdx] + numInputDims == idx) { in meanPrepare()
534 current += numInputDims; in meanPrepare()
536 NN_OPS_CHECK(current >= 0 && current < numInputDims); in meanPrepare()
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