| /frameworks/ml/nn/runtime/test/specs/ |
| concat_float_1.mod.py | 21 axis0 = Int32Scalar("axis0", 0) variable
23 model = model.Operation("CONCATENATION", i1, i2, axis0).To(r)
|
| concat_float_2.mod.py | 27 axis0 = Int32Scalar("axis0", 0) variable
29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output)
|
| concat_quant8_2.mod.py | 27 axis0 = Int32Scalar("axis0", 0) variable
29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output)
|
| /frameworks/ml/nn/runtime/test/generated/models/ |
| concat_float_1.model.cpp | 9 auto axis0 = model->addOperand(&type1); local
13 model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
14 model->addOperation(ANEURALNETWORKS_CONCATENATION, {op1, op2, axis0}, {result});
|
| concat_float_2.model.cpp | 10 auto axis0 = model->addOperand(&type2); local
14 model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
15 model->addOperation(ANEURALNETWORKS_CONCATENATION, {input1, input2, axis0}, {output});
|
| concat_quant8_2.model.cpp | 10 auto axis0 = model->addOperand(&type2); local
14 model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
15 model->addOperation(ANEURALNETWORKS_CONCATENATION, {input1, input2, axis0}, {output});
|
