| /frameworks/native/services/sensorservice/ |
| D | CorrectedGyroSensor.cpp | 59 const vec3_t bias(mSensorFusion.getGyroBias()); in process() local
61 outEvent->data[0] -= bias.x; in process()
62 outEvent->data[1] -= bias.y; in process()
63 outEvent->data[2] -= bias.z; in process()
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| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| D | fully_connected_float_large_weights_as_inputs.mod.py | 20 bias = Input("b0", "TENSOR_FLOAT32", "{1}") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
30 bias:
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| D | fully_connected_float_weights_as_inputs.mod.py | 20 bias = Input("b0", "TENSOR_FLOAT32", "{1}") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
29 bias: [4]}
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| D | fully_connected_quant8_large_weights_as_inputs.mod.py | 20 bias = Input("b0", "TENSOR_INT32", "{1}, 0.04, 0") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
30 bias:
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| D | fully_connected_quant8_weights_as_inputs.mod.py | 20 bias = Input("b0", "TENSOR_INT32", "{1}, 0.25f, 0") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
29 bias: [4]}
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| D | rnn_state.mod.py | 26 bias = Input("bias", "TENSOR_FLOAT32", "{%d}" % (units)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
80 bias: [
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| D | svdf_state.mod.py | 27 bias = Input("bias", "TENSOR_FLOAT32", "{%d}" % (units)) variable
34 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
56 bias: [],
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| D | svdf2.mod.py | 29 bias = Input("bias", "TENSOR_FLOAT32", "{%d}" % (units)) variable
36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
74 bias: [],
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| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| D | fully_connected_float_large_weights_as_inputs_relaxed.mod.py | 20 bias = Input("b0", "TENSOR_FLOAT32", "{1}") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
31 bias:
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| D | fully_connected_float_weights_as_inputs_relaxed.mod.py | 20 bias = Input("b0", "TENSOR_FLOAT32", "{1}") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
30 bias: [4]}
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| D | rnn_state_relaxed.mod.py | 26 bias = Input("bias", "TENSOR_FLOAT32", "{%d}" % (units)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
81 bias: [
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| D | svdf_state_relaxed.mod.py | 27 bias = Input("bias", "TENSOR_FLOAT32", "{%d}" % (units)) variable
34 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
57 bias: [],
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| D | rnn_relaxed.mod.py | 26 bias = Input("bias", "TENSOR_FLOAT32", "{%d}" % (units)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
81 bias: [
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| /frameworks/ml/nn/runtime/test/generated/models/ |
| D | local_response_norm_float_3.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | local_response_norm_float_4.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | local_response_norm_float_2.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | local_response_norm_float_1.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | local_response_norm_float_1_relaxed.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | local_response_norm_float_4_relaxed.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | local_response_norm_float_3_relaxed.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | local_response_norm_float_2_relaxed.model.cpp | 9 auto bias = model->addOperand(&type2); in CreateModel() local
17 model->setOperandValue(bias, bias_init, sizeof(float) * 1); in CreateModel()
22 …model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, bet… in CreateModel()
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| D | rnn_state.model.cpp | 13 auto bias = model->addOperand(&type3); in CreateModel() local
21 …model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in… in CreateModel()
24 {input, weights, recurrent_weights, bias, hidden_state_in}, in CreateModel()
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| D | rnn_state_relaxed.model.cpp | 13 auto bias = model->addOperand(&type3); in CreateModel() local
21 …model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in… in CreateModel()
24 {input, weights, recurrent_weights, bias, hidden_state_in}, in CreateModel()
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| D | rnn.model.cpp | 13 auto bias = model->addOperand(&type3); in CreateModel() local
21 …model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in… in CreateModel()
24 {input, weights, recurrent_weights, bias, hidden_state_in}, in CreateModel()
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| D | rnn_relaxed.model.cpp | 13 auto bias = model->addOperand(&type3); in CreateModel() local
21 …model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in… in CreateModel()
24 {input, weights, recurrent_weights, bias, hidden_state_in}, in CreateModel()
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