| /packages/modules/NeuralNetworks/common/types/operations/src/ |
| D | Reshape.cpp | 28 NN_RET_CHECK((context->getNumInputs() == 3 || context->getNumInputs() == 2) && in validateDepthToSpace()
30 << "Invalid number of input operands (" << context->getNumInputs() in validateDepthToSpace()
57 if (context->getNumInputs() == 3) { in validateDepthToSpace()
68 NN_RET_CHECK((context->getNumInputs() == 3 || context->getNumInputs() == 2) && in validateSpaceToDepth()
70 << "Invalid number of input operands (" << context->getNumInputs() in validateSpaceToDepth()
97 if (context->getNumInputs() == 3) { in validateSpaceToDepth()
108 NN_RET_CHECK(context->getNumInputs() == 2 && context->getNumOutputs() == 1) in validatePad()
156 NN_RET_CHECK(context->getNumInputs() == 3 && context->getNumOutputs() == 1) in validatePadV2()
203 NN_RET_CHECK((context->getNumInputs() == 3 || context->getNumInputs() == 2) && in validateBatchToSpaceND()
205 << "Invalid number of input operands (" << context->getNumInputs() in validateBatchToSpaceND()
[all …]
|
| D | LSTM.cpp | 28 NN_RET_CHECK((context->getNumInputs() == 23 || context->getNumInputs() == 27) && in validate()
30 << "Invalid number of input operands (" << context->getNumInputs() in validate()
55 if (context->getNumInputs() == 23) { in validate()
|
| D | GroupedConv2D.cpp | 27 NN_RET_CHECK((context->getNumInputs() == 12 || context->getNumInputs() == 9) && in validate()
29 << "Invalid number of input operands (" << context->getNumInputs() in validate()
69 if (context->getNumInputs() == 12) { in validate()
|
| D | Elementwise.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
37 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validateAbs()
49 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validateFloor()
68 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validateRsqrt()
|
| D | L2Normalization.cpp | 27 NN_RET_CHECK(context->getNumInputs() == kNumInputs || in validate()
28 context->getNumInputs() == kNumInputs - 1); in validate()
43 if (context->getNumInputs() == kNumInputs) { in validate()
|
| D | Softmax.cpp | 28 NN_RET_CHECK(context->getNumInputs() == kNumInputs || in validate()
29 context->getNumInputs() == kNumInputs - 1); in validate()
50 if (context->getNumInputs() == kNumInputs) { in validate()
|
| D | LocalResponseNormalization.cpp | 27 NN_RET_CHECK(context->getNumInputs() == kNumInputs || in validate()
28 context->getNumInputs() == kNumInputs - 1); in validate()
53 if (context->getNumInputs() == kNumInputs) { in validate()
|
| D | Reduce.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validateProdSum()
42 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validateMaxMin()
65 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validateLogical()
|
| D | Split.cpp | 27 NN_RET_CHECK_EQ(context->getNumInputs(), 3u) in validate()
28 << "Invalid number of input operands (" << context->getNumInputs() << ", expected 3)" in validate()
|
| D | GenerateProposals.cpp | 29 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
57 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
106 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
171 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| D | Pack.cpp | 25 NN_RET_CHECK_GE(context->getNumInputs(), kMinNumInputs); in validate()
48 for (uint32_t inputTensorNum = 0, inputTensorCount = context->getNumInputs() - 1; in validate()
|
| D | BidirectionalSequenceLSTM.cpp | 31 NN_RET_CHECK(context->getNumInputs() == 61 && in validate()
36 << "Invalid number of input operands (" << context->getNumInputs() in validate()
|
| D | Activation.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
54 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validateHardSwish()
|
| D | Conv2D.cpp | 27 const uint32_t numInputs = context->getNumInputs(); in validate()
39 auto inputCount = context->getNumInputs(); in validate()
|
| D | LogicalNot.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| D | LogicalAndOr.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| D | Neg.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| D | Quantize.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| D | Elu.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| D | PRelu.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| D | Select.cpp | 25 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); in validate()
|
| /packages/modules/NeuralNetworks/common/types/src/ |
| D | OperationsValidationUtils.cpp | 49 os << "Invalid number of input operands (" << getNumInputs() << ", expected " << expIn in invalidInOutNumberMessage()
58 NN_RET_CHECK_EQ(getNumInputs(), inExpectedTypes.size()) in validateOperationOperandTypes()
60 << getNumInputs() << " inputs"; in validateOperationOperandTypes()
64 for (size_t i = 0; i < getNumInputs(); i++) { in validateOperationOperandTypes()
80 return validateOperandTypes(expectedTypes, "input", context->getNumInputs(), in validateInputTypes()
96 for (uint32_t i = 0, n = context->getNumInputs(); i < n; ++i) { in validateVersion()
|
| /packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | Pack.cpp | 47 for (uint32_t inputTensorNum = 1, inputTensorCount = context->getNumInputs() - 1; in prepare()
75 outputShape.dimensions[axisDimension] = context->getNumInputs() - 1; in prepare()
88 const uint32_t inputTensorCount = context->getNumInputs() - 1; in packParams()
112 const uint32_t inputTensorCount = context->getNumInputs() - 1; in pack()
|
| D | Concatenation.cpp | 99 uint32_t inputCount = context->getNumInputs() - 1; in concatenation()
115 uint32_t inputCount = context->getNumInputs() - 1; in concatenation()
146 uint32_t numInputs = context->getNumInputs(); in prepare()
|
| D | LocalResponseNormalization.cpp | 119 int32_t axis = context->getNumInputs() == kNumInputs in executeTyped()
135 int32_t axis = context->getNumInputs() == kNumInputs in prepare()
|