| /packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | Split.cpp | 31 bool splitGeneric(const Scalar* inputData, const Shape& inputShape, int32_t axis, in splitGeneric()
57 bool splitFloat16(const _Float16* inputData, const Shape& inputShape, int32_t axis, in splitFloat16()
64 bool splitFloat32(const float* inputData, const Shape& inputShape, int32_t axis, in splitFloat32()
71 bool splitQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t axis, in splitQuant8()
78 bool splitQuant8Signed(const int8_t* inputData, const Shape& inputShape, int32_t axis, in splitQuant8Signed()
85 bool splitInt32(const int32_t* inputData, const Shape& inputShape, int32_t axis, in splitInt32()
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| D | L2Normalization.cpp | 46 inline bool l2normFloat32Impl(const float* inputData, const Shape& inputShape, int32_t axis, in l2normFloat32Impl()
74 inline bool l2normQuant8Impl(const uint8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8Impl()
106 inline bool l2normQuant8SignedImpl(const int8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8SignedImpl()
137 bool l2normFloat32(const float* inputData, const Shape& inputShape, int32_t axis, float* outputData, in l2normFloat32()
153 bool l2normFloat16(const _Float16* inputData, const Shape& inputShape, int32_t axis, in l2normFloat16()
166 bool l2normQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8()
182 bool l2normQuant8Signed(const int8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8Signed()
204 int32_t axis = context->getNumInputs() == kNumInputs in prepare() local
227 int32_t axis = context->getNumInputs() == kNumInputs in execute() local
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| D | LocalResponseNormalization.cpp | 47 int32_t axis, float* outputData, in localResponseNormFloat32Impl()
81 float bias, float alpha, float beta, int32_t axis, float* outputData, in localResponseNorm()
103 _Float16 bias, _Float16 alpha, _Float16 beta, int32_t axis, in localResponseNorm()
119 int32_t axis = context->getNumInputs() == kNumInputs in executeTyped() local
135 int32_t axis = context->getNumInputs() == kNumInputs in prepare() local
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| D | Gather.cpp | 31 inline bool eval(const T* inputData, const Shape& inputShape, int32_t axis, in eval()
55 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in prepare() local
73 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in execute() local
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| D | ChannelShuffle.cpp | 30 inline bool eval(const T* inputData, const Shape& inputShape, int32_t numGroups, int32_t axis, in eval()
55 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in prepare() local
64 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in execute() local
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| D | Softmax.cpp | 51 int32_t axis, float* outputData, const Shape& /*outputShape*/) { in softmaxSlowFloat32()
82 bool softmaxFloat32(const float* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxFloat32()
99 int32_t axis, _Float16* outputData, const Shape& outputShape) { in softmaxFloat16()
114 int32_t axis, int32_t inputMultiplier, int32_t inputLeftShift, float diffMin, in softmaxQuant8Impl()
200 bool softmaxQuant8(const T* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxQuant8()
246 int32_t axis = (context->getNumInputs() == kNumInputs) in execute() local
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| D | LogSoftmax.cpp | 34 inline bool compute(const T* input, const Shape& shape, T beta, uint32_t axis, T* output) { in compute()
70 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in execute() local
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| D | SimpleMath.cpp | 39 bool meanFloat16(_Float16* inputData, const Shape& inputShape, const int32_t* axis, in meanFloat16()
54 bool meanGeneric(T* inputData, const Shape& inputShape, const int32_t* axis, const Shape& axisShape, in meanGeneric()
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| D | Concatenation.cpp | 53 const std::vector<Shape>& inputShapes, int32_t axis, T* outputData, in concatenation()
73 const std::vector<Shape>& inputShapes, int32_t axis, in concatenation()
150 int32_t axis = context->getInputValue<int32_t>(numInputs - 1); in prepare() local
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| D | ArgMinMax.cpp | 31 static void argMinMaxImpl(const In* inputData, const Shape& inputShape, int32_t axis, bool isArgMin, in argMinMaxImpl()
53 bool argMinMaxGeneric(const uint8_t* inputData, const Shape& inputShape, int32 axis, bool isArgMin, in argMinMaxGeneric()
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
| D | argmax_quant8_signed.mod.py | 18 axis = Int32Scalar("axis", 1) variable
36 axis = Int32Scalar("axis", 0) variable
56 axis = Int32Scalar("axis", -1) variable
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| D | argmin_quant8_signed.mod.py | 19 axis = Int32Scalar("axis", -1) variable
37 axis = Int32Scalar("axis", 0) variable
55 axis = Int32Scalar("axis", 1) variable
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| D | split_quant8_signed.mod.py | 18 axis = Int32Scalar("axis", 0) variable
41 axis = Int32Scalar("axis", 0) variable
62 axis = Int32Scalar("axis", 1) variable
85 axis = Int32Scalar("axis", 1) variable
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| D | l2_normalization_quant8_signed.mod.py | 19 axis = Int32Scalar("axis", -1) # last axis variable
53 axis = Int32Scalar("axis", -1) # last axis variable
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| D | gather_quant8_signed.mod.py | 18 axis = 1 variable
46 def test(input0, axis, indices, output0, input_data, output_data): argument
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| D | mean_quant8_signed.mod.py | 18 axis = Parameter("axis", "TENSOR_INT32", "{4}", [1, 0, -3, -3]) variable
42 axis = Parameter("axis", "TENSOR_INT32", "{2}", [0, 2]) variable
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| D | channel_shuffle_quant8_signed.mod.py | 19 axis = Int32Scalar("axis", -1) # last axis variable
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
| D | l2_normalization_axis.mod.py | 20 axis = Int32Scalar("axis", -1) # last axis variable
54 axis = Int32Scalar("axis", -1) # last axis variable
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| D | channel_shuffle.mod.py | 19 axis = Int32Scalar("axis", -1) # last axis variable
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| D | local_response_normalization_v1_2.mod.py | 19 axis = Int32Scalar("axis", -1) # last axis variable
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| D | l2_normalization_v1_2.mod.py | 19 axis = Int32Scalar("axis", -1) # last axis variable
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| D | argmin_2.mod.py | 18 axis = Int32Scalar("axis", 0) variable
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| D | argmax_1.mod.py | 18 axis = Int32Scalar("axis", 1) variable
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| /packages/apps/Car/Notification/src/com/android/car/notification/ |
| D | HeadsUpNotificationOnTouchListener.java | 299 private boolean isFlingEnoughForDismiss(VelocityTracker velocityTracker, Axis axis) { in isFlingEnoughForDismiss()
309 private float getVelocityInAxis(VelocityTracker velocityTracker, Axis axis) { in getVelocityInAxis()
319 Axis axis) { in isFlingInSameDirectionAsDelta()
326 private void animateDismissInAxis(View view, Axis axis, boolean dismissInPositiveDirection) { in animateDismissInAxis()
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_3_cts_only/ |
| D | concat_invalid_rank.mod.py | 19 axis = 4 variable
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