| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| svdf_state.mod.py | 29 rank_param = Int32Scalar("rank_param", 1) variable
35 rank_param, activation_param).To([state_out, output])
|
| svdf.mod.py | 31 rank_param = Int32Scalar("rank_param", rank) variable
37 rank_param, activation_param).To([state_out, output])
|
| svdf2.mod.py | 31 rank_param = Int32Scalar("rank_param", rank) variable
37 rank_param, activation_param).To([state_out, output])
|
| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| svdf_state_relaxed.mod.py | 29 rank_param = Int32Scalar("rank_param", 1) variable
35 rank_param, activation_param).To([state_out, output])
|
| svdf2_relaxed.mod.py | 31 rank_param = Int32Scalar("rank_param", rank) variable
37 rank_param, activation_param).To([state_out, output])
|
| svdf_relaxed.mod.py | 31 rank_param = Int32Scalar("rank_param", rank) variable
37 rank_param, activation_param).To([state_out, output])
|
| /frameworks/ml/nn/runtime/test/generated/models/ |
| svdf.model.cpp | 16 auto rank_param = model->addOperand(&type5); local
22 model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
|
| svdf2.model.cpp | 16 auto rank_param = model->addOperand(&type5); local
22 model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
|
| svdf2_relaxed.model.cpp | 16 auto rank_param = model->addOperand(&type5); local
22 model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
|
| svdf_relaxed.model.cpp | 16 auto rank_param = model->addOperand(&type5); local
22 model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
|
| svdf_state.model.cpp | 16 auto rank_param = model->addOperand(&type5); local
22 model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
|
| svdf_state_relaxed.model.cpp | 16 auto rank_param = model->addOperand(&type5); local
22 model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
|
