| /hardware/interfaces/wifi/1.4/default/tests/ |
| D | ringbuffer_unit_tests.cpp | 41 const std::vector<uint8_t> input(maxBufferSize_ / 2, '0'); in TEST_F() local
43 buffer_.append(input); in TEST_F()
46 EXPECT_EQ(input, buffer_.getData().front()); in TEST_F()
51 const std::vector<uint8_t> input(maxBufferSize_ / 2, '0'); in TEST_F() local
54 buffer_.append(input); in TEST_F()
63 const std::vector<uint8_t> input(maxBufferSize_ / 2, '0'); in TEST_F() local
66 buffer_.append(input); in TEST_F()
74 const std::vector<uint8_t> input = {}; in TEST_F() local
75 buffer_.append(input); in TEST_F()
80 const std::vector<uint8_t> input(maxBufferSize_ + 1, '0'); in TEST_F() local
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| /hardware/interfaces/wifi/1.4/default/ |
| D | ringbuffer.cpp | 29 void Ringbuffer::append(const std::vector<uint8_t>& input) { in append() argument
30 if (input.size() == 0) { in append()
33 if (input.size() > maxSize_) { in append()
34 LOG(INFO) << "Oversized message of " << input.size() in append()
38 data_.push_back(input); in append()
39 size_ += input.size() * sizeof(input[0]); in append()
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| /hardware/libhardware/modules/sensors/dynamic_sensor/HidUtils/ |
| D | HidParser.h | 121 uint32_t mask(int64_t input) const { in mask()
122 return static_cast<uint32_t>(input & rawMask()); in mask()
125 bool decode(uint32_t input, double *output) const { in decode()
129 int64_t s = signExtendIfNeeded(input); in decode()
137 bool encode(double input, uint32_t *output) const { in encode()
141 input = input / a - b; in encode()
142 if (input < minRaw || input > maxRaw) { in encode()
145 *output = static_cast<uint32_t>(static_cast<int64_t>(input) & rawMask()); in encode()
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| /hardware/libhardware/modules/camera/3_4/metadata/ |
| D | v4l2_control_delegate_test.cpp | 80 uint8_t input = 10; in TEST_F() local
82 EXPECT_CALL(*mock_converter_, MetadataToV4L2(input, _)) in TEST_F()
87 ASSERT_EQ(dut_->SetValue(input), 0); in TEST_F()
91 uint8_t input = 10; in TEST_F() local
93 EXPECT_CALL(*mock_converter_, MetadataToV4L2(input, _)).WillOnce(Return(err)); in TEST_F()
94 ASSERT_EQ(dut_->SetValue(input), err); in TEST_F()
98 uint8_t input = 10; in TEST_F() local
100 EXPECT_CALL(*mock_converter_, MetadataToV4L2(input, _)) in TEST_F()
106 ASSERT_EQ(dut_->SetValue(input), err); in TEST_F()
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| /hardware/interfaces/input/classifier/1.0/vts/functional/ |
| D | VtsHalInputClassifierV1_0TargetTest.cpp | 31 using ::android::hardware::input::classifier::V1_0::IInputClassifier;
32 using ::android::hardware::input::common::V1_0::Action;
33 using ::android::hardware::input::common::V1_0::Axis;
34 using ::android::hardware::input::common::V1_0::Button;
35 using ::android::hardware::input::common::V1_0::EdgeFlag;
36 using ::android::hardware::input::common::V1_0::MotionEvent;
37 using ::android::hardware::input::common::V1_0::PointerCoords;
38 using ::android::hardware::input::common::V1_0::PointerProperties;
39 using ::android::hardware::input::common::V1_0::Source;
40 using ::android::hardware::input::common::V1_0::ToolType;
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| /hardware/interfaces/tv/input/1.0/default/ |
| D | Android.bp | 2 name: "android.hardware.tv.input@1.0-impl",
15 "android.hardware.tv.input@1.0",
21 name: "android.hardware.tv.input@1.0-service",
25 init_rc: ["android.hardware.tv.input@1.0-service.rc"],
38 "android.hardware.tv.input@1.0",
|
| D | TvInput.h | 28 namespace input {
33 using ::android::hardware::tv::input::V1_0::ITvInput;
34 using ::android::hardware::tv::input::V1_0::ITvInputCallback;
35 using ::android::hardware::tv::input::V1_0::Result;
36 using ::android::hardware::tv::input::V1_0::TvInputEvent;
37 using ::android::hardware::tv::input::V1_0::TvStreamConfig;
|
| D | [email protected] | 1 service vendor.tv-input-1-0 /vendor/bin/hw/android.hardware.tv.input@1.0-service
2 interface android.hardware.tv.input@1.0::ITvInput default
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| /hardware/interfaces/neuralnetworks/1.1/vts/functional/ |
| D | ValidateRequest.cpp | 57 for (size_t input = 0; input < request.inputs.size(); ++input) { in removeInputTest() local
58 const std::string message = "removeInput: removed input " + std::to_string(input); in removeInputTest()
60 [input](Request* request) { hidl_vec_removeAt(&request->inputs, input); }); in removeInputTest()
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| /hardware/interfaces/neuralnetworks/1.0/ |
| D | types.hal | 83 * Takes two input tensors of identical {@link OperandType} and compatible
84 * dimensions. The output is the sum of both input tensors, optionally
92 * input operands. It starts with the trailing dimensions, and works its
134 * input[b, strides[1] * i + di, strides[2] * j + dj, channel]
148 * the input.
158 * walking through input in the ‘width’ dimension.
160 * walking through input in the ‘height’ dimension.
171 * the input.
176 * walking through input in the ‘width’ dimension.
178 * walking through input in the ‘height’ dimension.
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| /hardware/interfaces/neuralnetworks/1.0/vts/functional/ |
| D | ValidateRequest.cpp | 73 for (size_t input = 0; input < request.inputs.size(); ++input) { in removeInputTest() local
74 const std::string message = "removeInput: removed input " + std::to_string(input); in removeInputTest()
76 [input](Request* request) { hidl_vec_removeAt(&request->inputs, input); }); in removeInputTest()
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| /hardware/qcom/neuralnetworks/hvxservice/1.0/ |
| D | HexagonOperationsPrepare.cpp | 56 const hexagon_nn_input& input = model->getTensor(ins[0]); in average_pool_2d() local
96 return model->addFloatOperationWithActivation(OP_AvgPool_f, pad, act, {input, window, stride}, in average_pool_2d()
129 const hexagon_nn_input& input = model->getTensor(ins[0]); in conv_2d() local
165 return model->addFusedFloatOperation(OP_Conv2d_f, pad, bias, act, {input, filter, stride}, in conv_2d()
176 const hexagon_nn_input& input = model->getTensor(ins[0]); in depthwise_conv_2d() local
218 {input, filter, stride}, outs); in depthwise_conv_2d()
227 const hexagon_nn_input& input = model->getTensor(ins[0]); in fully_connected() local
234 return model->addFusedFloatOperation(OP_MatMul_f, NN_PAD_NA, bias, act, {input, weights}, outs); in fully_connected()
244 const hexagon_nn_input& input = model->getTensor(ins[0]); in l2_pool_2d() local
284 return model->addFloatOperationWithActivation(OP_L2Pool_f, pad, act, {input, window, stride}, in l2_pool_2d()
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| /hardware/invensense/65xx/libsensors_iio/software/core/mllite/ |
| D | ml_math_func.h | 30 float input; member
94 void inv_convert_to_body(unsigned short orientation, const long *input, long *output);
95 void inv_convert_to_chip(unsigned short orientation, const long *input, long *output);
96 …_to_body_with_scale(unsigned short orientation, long sensitivity, const long *input, long *output);
113 float inv_biquad_filter_process(inv_biquad_filter_t *pFilter, float input);
114 void inv_calc_state_to_match_output(inv_biquad_filter_t *pFilter, float input);
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| /hardware/invensense/6515/libsensors_iio/software/core/mllite/ |
| D | ml_math_func.h | 30 float input; member
94 void inv_convert_to_body(unsigned short orientation, const long *input, long *output);
95 void inv_convert_to_chip(unsigned short orientation, const long *input, long *output);
96 …_to_body_with_scale(unsigned short orientation, long sensitivity, const long *input, long *output);
113 float inv_biquad_filter_process(inv_biquad_filter_t *pFilter, float input);
114 void inv_calc_state_to_match_output(inv_biquad_filter_t *pFilter, float input);
|
| /hardware/qcom/data/ipacfg-mgr/msm8998/ipacm/src/ |
| D | IPACM_ConntrackListener.cpp | 782 void IPACM_ConntrackListener::AddORDeleteNatEntry(const nat_entry_bundle *input) in AddORDeleteNatEntry() argument
794 input->rule->target_ip); in AddORDeleteNatEntry()
796 input->rule->target_port, input->rule->target_port); in AddORDeleteNatEntry()
798 input->rule->private_ip); in AddORDeleteNatEntry()
800 input->rule->private_port, input->rule->private_port); in AddORDeleteNatEntry()
802 input->rule->public_port, input->rule->public_port); in AddORDeleteNatEntry()
804 input->rule->protocol, input->rule->dst_nat); in AddORDeleteNatEntry()
806 if (IPPROTO_TCP == input->rule->protocol) in AddORDeleteNatEntry()
808 tcp_state = nfct_get_attr_u8(input->ct, ATTR_TCP_STATE); in AddORDeleteNatEntry()
815 nat_inst->CacheEntry(input->rule); in AddORDeleteNatEntry()
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| /hardware/qcom/sdm845/data/ipacfg-mgr/ipacm/src/ |
| D | IPACM_ConntrackListener.cpp | 773 void IPACM_ConntrackListener::AddORDeleteNatEntry(const nat_entry_bundle *input) in AddORDeleteNatEntry() argument
785 input->rule->target_ip); in AddORDeleteNatEntry()
787 input->rule->target_port, input->rule->target_port); in AddORDeleteNatEntry()
789 input->rule->private_ip); in AddORDeleteNatEntry()
791 input->rule->private_port, input->rule->private_port); in AddORDeleteNatEntry()
793 input->rule->public_port, input->rule->public_port); in AddORDeleteNatEntry()
795 input->rule->protocol, input->rule->dst_nat); in AddORDeleteNatEntry()
797 if (IPPROTO_TCP == input->rule->protocol) in AddORDeleteNatEntry()
799 tcp_state = nfct_get_attr_u8(input->ct, ATTR_TCP_STATE); in AddORDeleteNatEntry()
806 nat_inst->CacheEntry(input->rule); in AddORDeleteNatEntry()
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| /hardware/qcom/sm8150/data/ipacfg-mgr/ipacm/src/ |
| D | IPACM_ConntrackListener.cpp | 780 void IPACM_ConntrackListener::AddORDeleteNatEntry(const nat_entry_bundle *input) in AddORDeleteNatEntry() argument
792 input->rule->target_ip); in AddORDeleteNatEntry()
794 input->rule->target_port, input->rule->target_port); in AddORDeleteNatEntry()
796 input->rule->private_ip); in AddORDeleteNatEntry()
798 input->rule->private_port, input->rule->private_port); in AddORDeleteNatEntry()
800 input->rule->public_port, input->rule->public_port); in AddORDeleteNatEntry()
802 input->rule->protocol, input->rule->dst_nat); in AddORDeleteNatEntry()
804 if (IPPROTO_TCP == input->rule->protocol) in AddORDeleteNatEntry()
806 tcp_state = nfct_get_attr_u8(input->ct, ATTR_TCP_STATE); in AddORDeleteNatEntry()
813 nat_inst->CacheEntry(input->rule); in AddORDeleteNatEntry()
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| /hardware/interfaces/neuralnetworks/1.3/ |
| D | types.hal | 96 * Takes two input tensors of identical {@link OperandType} and compatible
97 * dimensions. The output is the sum of both input tensors, optionally
105 * input operands. It starts with the trailing dimensions, and works its
114 * Since HAL version 1.2, generic zero-sized input tensor is supported. Zero
116 * dimension is zero if either of corresponding input dimension is zero.
158 * input[b, strides[1] * i + di, strides[2] * j + dj, channel]
177 * the input.
188 * walking through input in the ‘width’ dimension.
190 * walking through input in the ‘height’ dimension.
204 * the input.
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| /hardware/interfaces/input/classifier/1.0/default/ |
| D | Android.bp | 2 name: "android.hardware.input[email protected]",
3 init_rc: ["android.hardware.input[email protected]"],
12 "android.hardware.input[email protected]",
|
| D | InputClassifier.h | 25 namespace input {
35 Return<android::hardware::input::common::V1_0::Classification> classify(
36 const android::hardware::input::common::V1_0::MotionEvent& event) override;
|
| D | [email protected] | 1 service vendor.input.classifier-1-0 /vendor/bin/hw/android.hardware.input[email protected]…
3 interface android.hardware.input[email protected]::IInputClassifier default
|
| /hardware/interfaces/neuralnetworks/1.2/ |
| D | types.hal | 159 * Takes two input tensors of identical {@link OperandType} and compatible
160 * dimensions. The output is the sum of both input tensors, optionally
168 * input operands. It starts with the trailing dimensions, and works its
177 * Since HAL version 1.2, generic zero-sized input tensor is supported. Zero
179 * dimension is zero if either of corresponding input dimension is zero.
215 * input[b, strides[1] * i + di, strides[2] * j + dj, channel]
233 * the input.
244 * walking through input in the ‘width’ dimension.
246 * walking through input in the ‘height’ dimension.
260 * the input.
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| /hardware/google/camera/devices/EmulatedCamera/hwl/ |
| D | JpegCompressor.cpp | 67 if ((job->input.get() == nullptr) || (job->output.get() == nullptr) || in QueueYUV420()
137 job->input->yuv_planes.img_y, job->input->yuv_planes.y_stride, in CompressYUV420()
138 job->input->yuv_planes.img_cb, job->input->yuv_planes.cbcr_stride, in CompressYUV420()
139 job->input->yuv_planes.img_cr, job->input->yuv_planes.cbcr_stride, in CompressYUV420()
140 job->input->width, job->input->height, thumb_planes.img_y, in CompressYUV420()
153 *job->result_metadata, job->input->width, job->input->height)) { in CompressYUV420()
194 .yuv_planes = job->input->yuv_planes, in CompressYUV420()
195 .width = job->input->width, in CompressYUV420()
196 .height = job->input->height, in CompressYUV420()
|
| /hardware/interfaces/media/c2/1.0/ |
| D | IComponentListener.hal | 27 * All the input buffers in the returned `Work` objects must not be used by
89 * Identifying information for an input buffer previously queued to the
94 * This value comes from `Work::input.ordinal.frameIndex` in a `Work`
99 * This value is an index into `Work::input.buffers` (which is an array)
106 * Notify the listener that some input buffers are no longer needed by the
112 * onInputBuffersReleased() must only report input buffers that are released
114 * possible for an input buffer to be returned by onWorkDone() after it has
118 * that input buffers are no longer needed. However, in order to minimize
120 * onWorkDone() cannot be called, e.g., the component needs more input
123 * @param inputBuffers List of `InputBuffer` objects, identifying input
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| /hardware/interfaces/neuralnetworks/1.1/ |
| D | types.hal | 35 * result with the same rank as the input.
49 * sizes for each spatial dimension of the input tensor. All values
62 * Takes two input tensors of identical {@link OperandType} and compatible
63 * dimensions. The output is the result of dividing the first input tensor
71 * input operands. It starts with the trailing dimensions, and works its way
85 * * 0: An n-D tensor, specifying the first input.
100 * Reduces the input tensor along the given dimensions to reduce. Unless
112 * * 0: A tensor, specifying the input.
149 * for each spatial dimension of the input tensor. The shape of the
160 * corresponding dimension of the input tensor plus the size
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