| /frameworks/native/services/inputflinger/reader/mapper/ |
| D | JoystickInputMapper.cpp | 35 const Axis& axis = mAxes.valueAt(i); in populateDeviceInfo() local
36 addMotionRange(axis.axisInfo.axis, axis, info); in populateDeviceInfo()
38 if (axis.axisInfo.mode == AxisInfo::MODE_SPLIT) { in populateDeviceInfo()
39 addMotionRange(axis.axisInfo.highAxis, axis, info); in populateDeviceInfo()
44 void JoystickInputMapper::addMotionRange(int32_t axisId, const Axis& axis, InputDeviceInfo* info) { in addMotionRange() argument
45 info->addMotionRange(axisId, AINPUT_SOURCE_JOYSTICK, axis.min, axis.max, axis.flat, axis.fuzz, in addMotionRange()
46 axis.resolution); in addMotionRange()
52 info->addMotionRange(compatAxis, AINPUT_SOURCE_JOYSTICK, axis.min, axis.max, axis.flat, in addMotionRange()
53 axis.fuzz, axis.resolution); in addMotionRange()
60 int32_t JoystickInputMapper::getCompatAxis(int32_t axis) { in getCompatAxis() argument
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| D | InputMapper.cpp | 76 status_t InputMapper::getAbsoluteAxisInfo(int32_t axis, RawAbsoluteAxisInfo* axisInfo) { in getAbsoluteAxisInfo() argument
77 return getEventHub()->getAbsoluteAxisInfo(getDeviceId(), axis, axisInfo); in getAbsoluteAxisInfo()
84 void InputMapper::dumpRawAbsoluteAxisInfo(std::string& dump, const RawAbsoluteAxisInfo& axis, in dumpRawAbsoluteAxisInfo() argument
86 if (axis.valid) { in dumpRawAbsoluteAxisInfo()
88 axis.minValue, axis.maxValue, axis.flat, axis.fuzz, axis.resolution); in dumpRawAbsoluteAxisInfo()
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| /frameworks/ml/nn/common/operations/ |
| D | L2Normalization.cpp | 47 inline bool l2normFloat32Impl(const float* inputData, const Shape& inputShape, int32_t axis, in l2normFloat32Impl() argument
51 const uint32_t outerSize = getNumberOfElements(inputShape, 0, axis); in l2normFloat32Impl()
52 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in l2normFloat32Impl()
54 getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape)); in l2normFloat32Impl()
75 inline bool l2normQuant8Impl(const uint8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8Impl() argument
78 const uint32_t outerSize = getNumberOfElements(inputShape, 0, axis); in l2normQuant8Impl()
79 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in l2normQuant8Impl()
81 getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape)); in l2normQuant8Impl()
107 inline bool l2normQuant8SignedImpl(const int8_t* inputData, const Shape& inputShape, int32_t axis, in l2normQuant8SignedImpl() argument
110 const uint32_t outerSize = getNumberOfElements(inputShape, 0, axis); in l2normQuant8SignedImpl()
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| D | Split.cpp | 30 bool splitGeneric(const Scalar* inputData, const Shape& inputShape, int32_t axis, in splitGeneric() argument
33 NN_CHECK(handleNegativeAxis(inputShape, &axis)); in splitGeneric()
35 for (int i = 0; i < axis; ++i) { in splitGeneric()
40 for (int i = axis + 1; i < concatDimensions; ++i) { in splitGeneric()
47 const int copySize = outputShapes[i].dimensions[axis] * baseInnerSize; in splitGeneric()
56 bool splitFloat16(const _Float16* inputData, const Shape& inputShape, int32_t axis, in splitFloat16() argument
60 return splitGeneric<_Float16>(inputData, inputShape, axis, outputDataPtrs, outputShapes); in splitFloat16()
63 bool splitFloat32(const float* inputData, const Shape& inputShape, int32_t axis, in splitFloat32() argument
67 return splitGeneric<float>(inputData, inputShape, axis, outputDataPtrs, outputShapes); in splitFloat32()
70 bool splitQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t axis, in splitQuant8() argument
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| D | Gather.cpp | 43 inline bool eval(const T* inputData, const Shape& inputShape, int32_t axis, in eval() argument
45 const auto outerSize = getNumberOfElements(inputShape, 0, axis); in eval()
46 const auto axisSize = getSizeOfDimension(inputShape, axis); in eval()
48 getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape)); in eval()
87 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in prepare() local
88 NN_RET_CHECK(handleNegativeAxis(input, &axis)); in prepare()
95 input.dimensions.begin() + axis); in prepare()
98 output.dimensions.insert(output.dimensions.end(), input.dimensions.begin() + axis + 1, in prepare()
105 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in execute() local
106 NN_RET_CHECK(handleNegativeAxis(context->getInputShape(kInputTensor), &axis)); in execute()
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| D | ChannelShuffle.cpp | 41 inline bool eval(const T* inputData, const Shape& inputShape, int32_t numGroups, int32_t axis, in eval() argument
43 const uint32_t outerSize = getNumberOfElements(inputShape, 0, axis); in eval()
44 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in eval()
46 getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape)); in eval()
88 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in prepare() local
89 NN_RET_CHECK(handleNegativeAxis(input, &axis)); in prepare()
91 NN_RET_CHECK(getSizeOfDimension(input, axis) % numGroups == 0); in prepare()
97 int32_t axis = context->getInputValue<int32_t>(kInputAxis); in execute() local
98 NN_RET_CHECK(handleNegativeAxis(context->getInputShape(kInputTensor), &axis)); in execute()
102 context->getInputShape(kInputTensor), numGroups, axis, in execute()
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| D | LocalResponseNormalization.cpp | 52 int32_t axis, float* outputData, in localResponseNormFloat32Impl() argument
55 const uint32_t outerSize = getNumberOfElements(inputShape, 0, axis); in localResponseNormFloat32Impl()
56 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in localResponseNormFloat32Impl()
58 getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape)); in localResponseNormFloat32Impl()
82 T beta, int32_t axis, T* outputData, const Shape& outputShape);
86 float bias, float alpha, float beta, int32_t axis, float* outputData, in localResponseNorm() argument
89 NN_CHECK(handleNegativeAxis(inputShape, &axis)); in localResponseNorm()
91 if (axis == ndim - 1) { in localResponseNorm()
100 return localResponseNormFloat32Impl(inputData, inputShape, radius, bias, alpha, beta, axis, in localResponseNorm()
107 _Float16 bias, _Float16 alpha, _Float16 beta, int32_t axis, in localResponseNorm() argument
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| D | Softmax.cpp | 52 int32_t axis, float* outputData, const Shape& outputShape) { in softmaxSlowFloat32() argument
54 const uint32_t outerSize = getNumberOfElements(inputShape, 0, axis); in softmaxSlowFloat32()
55 const uint32_t axisSize = getSizeOfDimension(inputShape, axis); in softmaxSlowFloat32()
57 getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape)); in softmaxSlowFloat32()
83 bool softmaxFloat32(const float* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxFloat32() argument
86 NN_CHECK(handleNegativeAxis(inputShape, &axis)); in softmaxFloat32()
88 if (axis == ndim - 1) { in softmaxFloat32()
95 return softmaxSlowFloat32(inputData, inputShape, beta, axis, outputData, outputShape); in softmaxFloat32()
100 int32_t axis, _Float16* outputData, const Shape& outputShape) { in softmaxFloat16() argument
106 softmaxFloat32(inputData_float32.data(), inputShape, beta, axis, outputData_float32.data(), in softmaxFloat16()
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| /frameworks/base/data/keyboards/ |
| D | Vendor_054c_Product_0268.kl | 36 axis 0x00 X
37 axis 0x01 Y
40 axis 0x02 Z
41 axis 0x05 RZ
44 # axis 0x2c -HAT_Y
45 # axis 0x2d +HAT_X
46 # axis 0x2e +HAT_Y
47 # axis 0x2f -HAT_X
50 axis 0x30 LTRIGGER
53 axis 0x31 RTRIGGER
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| D | Vendor_045e_Product_02e0.kl | 30 # LT axis
31 axis 0x02 LTRIGGER
32 # RT axis
33 axis 0x05 RTRIGGER
37 axis 0x00 X
38 axis 0x01 Y
40 axis 0x03 Z
41 axis 0x04 RZ
49 axis 0x10 HAT_X
50 axis 0x11 HAT_Y
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| D | Vendor_2e95_Product_7725.kl | 35 # L2 Trigger axis
36 axis 0x03 LTRIGGER
37 # R2 Trigger axis
38 axis 0x04 RTRIGGER
41 axis 0x00 X
42 axis 0x01 Y
44 axis 0x02 Z
45 axis 0x05 RZ
53 axis 0x10 HAT_X
54 axis 0x11 HAT_Y
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| D | Vendor_2378_Product_100a.kl | 28 axis 0x00 X
29 axis 0x01 Y
30 axis 0x03 Z
31 axis 0x04 RZ
32 axis 0x05 RTRIGGER
33 axis 0x02 LTRIGGER
34 axis 0x10 HAT_X
35 axis 0x11 HAT_Y
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| D | Vendor_046d_Product_c21f.kl | 29 axis 0x00 X
30 axis 0x01 Y
31 axis 0x03 Z
32 axis 0x04 RZ
33 axis 0x05 RTRIGGER
34 axis 0x02 LTRIGGER
35 axis 0x10 HAT_X
36 axis 0x11 HAT_Y
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| D | Vendor_046d_Product_c21d.kl | 29 axis 0x00 X
30 axis 0x01 Y
31 axis 0x03 Z
32 axis 0x04 RZ
33 axis 0x05 GAS
34 axis 0x02 BRAKE
35 axis 0x10 HAT_X
36 axis 0x11 HAT_Y
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| D | Vendor_2378_Product_1008.kl | 28 axis 0x00 X
29 axis 0x01 Y
30 axis 0x03 Z
31 axis 0x04 RZ
32 axis 0x05 RTRIGGER
33 axis 0x02 LTRIGGER
34 axis 0x10 HAT_X
35 axis 0x11 HAT_Y
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| D | Vendor_1689_Product_fd01.kl | 29 axis 0x00 X
30 axis 0x01 Y
31 axis 0x03 Z
32 axis 0x04 RZ
33 axis 0x05 RTRIGGER
34 axis 0x02 LTRIGGER
35 axis 0x10 HAT_X
36 axis 0x11 HAT_Y
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| D | Vendor_0a5c_Product_8502.kl | 30 axis 0x00 X
31 axis 0x01 Y
32 axis 0x02 Z
33 axis 0x03 RX
34 axis 0x04 RY
35 axis 0x05 RZ
36 axis 0x10 HAT_X
37 axis 0x11 HAT_Y
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| D | Vendor_1bad_Product_f036.kl | 29 axis 0x00 X
30 axis 0x01 Y
31 axis 0x03 Z
32 axis 0x04 RZ
33 axis 0x05 RTRIGGER
34 axis 0x02 LTRIGGER
35 axis 0x10 HAT_X
36 axis 0x11 HAT_Y
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| D | Vendor_1689_Product_fe00.kl | 29 axis 0x00 X
30 axis 0x01 Y
31 axis 0x03 Z
32 axis 0x04 RZ
33 axis 0x05 RTRIGGER
34 axis 0x02 LTRIGGER
35 axis 0x10 HAT_X
36 axis 0x11 HAT_Y
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| /frameworks/base/startop/scripts/app_startup/ |
| D | analyze_metrics.py | 209 print("Mean: ", np_data_2d.mean(axis=0))
210 print("Std: ", np_data_2d.std(axis=0))
212 print("SEM: ", stats_standard_error_one(np_data_2d, axis=0))
215 sem = stats_standard_error_one(np_data_2d, axis=0)[_PLOT_DATA_INDEX]
216 mean = np_data_2d.mean(axis=0)[_PLOT_DATA_INDEX]
220 … csv_writer.writerow(label_list + [mean, np_data_2d.std(axis=0)[_PLOT_DATA_INDEX], ci[0], ci[1]])
281 def stats_standard_error_one(a, axis): argument
282 a_std = a.std(axis=axis, ddof=0)
283 a_len = a.shape[axis]
287 def stats_standard_error(a, b, axis): argument
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| /frameworks/ml/nn/runtime/test/specs/V1_3/ |
| D | gather_quant8_signed.mod.py | 18 axis = 1 variable
22 model = Model().Operation("GATHER", input0, axis, indices).To(output0)
46 def test(input0, axis, indices, output0, input_data, output_data): argument
47 model = Model().Operation("GATHER", input0, axis, indices).To(output0)
61 axis=0,
72 axis=0,
82 axis=0,
91 axis=0,
100 axis=0,
113 axis=0,
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| D | split_quant8_signed.mod.py | 18 axis = Int32Scalar("axis", 0) variable
24 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
41 axis = Int32Scalar("axis", 0) variable
46 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
62 axis = Int32Scalar("axis", 1) variable
68 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
85 axis = Int32Scalar("axis", 1) variable
92 model = Model().Operation("SPLIT", input0, axis, num_splits).To(
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| /frameworks/ml/nn/runtime/test/specs/V1_2/ |
| D | gather.mod.py | 17 def test(input0, axis, indices, output0, input_data, output_data): argument
18 model = Model().Operation("GATHER", input0, axis, indices).To(output0)
42 axis=0,
53 axis=0,
63 axis=0,
72 axis=0,
81 axis=0,
94 axis=0,
103 axis=1,
114 axis=-1,
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| D | l2_normalization_axis.mod.py | 20 axis = Int32Scalar("axis", -1) # last axis variable
47 Model().Operation("L2_NORMALIZATION", i1, axis).To(o1)
48 Example(example0).AddAllDimsAndAxis(i1, o1, axis).AddVariations("relaxed", "float16", quant8)
54 axis = Int32Scalar("axis", -1) # last axis variable
56 Model("corner_case").Operation("L2_NORMALIZATION", i2, axis).To(o2)
60 }).AddAllDimsAndAxis(i2, o2, axis)
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| /frameworks/native/libs/vr/libdvrcommon/tests/ |
| D | pose_test.cpp | 56 for (int axis = 0; axis < 3; ++axis) { in TYPED_TEST() local
58 start_position[axis] = FT(1.0); in TYPED_TEST()
81 for (int axis = 0; axis < 3; ++axis) { in TYPED_TEST() local
83 start_position[axis] = FT(1.0); in TYPED_TEST()
110 for (int axis = 0; axis < 3; ++axis) { in TYPED_TEST() local
112 start_position[axis] = FT(1.0); in TYPED_TEST()
136 for (int axis = 0; axis < 3; ++axis) { in TYPED_TEST() local
138 start_position[axis] = FT(1.0); in TYPED_TEST()
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