| /frameworks/ml/nn/tools/test_generator/tests/P_quantized_avgpool/ |
| H A D | averpoolfloat.mod.py | 4 cons1 = Int32Scalar("cons1", 1) variable
7 model = model.Operation("AVERAGE_POOL", i1, cons1, cons1, cons1, cons1, cons1, act).To(o)
|
| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| H A D | avg_pool_float_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3)
|
| H A D | avg_pool_quant8_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(o)
|
| H A D | avg_pool_quant8_4.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act2).To(o)
|
| H A D | l2_pool_float.mod.py | 19 cons1 = Int32Scalar("cons1", 1) variable
23 model = model.Operation("L2_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3)
|
| H A D | max_pool_float_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable
24 model = model.Operation("MAX_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3)
|
| H A D | max_pool_quant8_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable
24 model = model.Operation("MAX_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3)
|
| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| H A D | avg_pool_float_1_relaxed.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3)
|
| H A D | l2_pool_float_relaxed.mod.py | 19 cons1 = Int32Scalar("cons1", 1) variable
23 model = model.Operation("L2_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3)
|
| H A D | max_pool_float_1_relaxed.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable
24 model = model.Operation("MAX_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3)
|
| /frameworks/ml/nn/runtime/test/generated/models/ |
| H A D | avg_pool_float_1.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|
| H A D | avg_pool_float_1_relaxed.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|
| H A D | avg_pool_quant8_1.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|
| H A D | avg_pool_quant8_4.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, relu1_activitation}, {op3});
|
| H A D | l2_pool_float.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|
| H A D | l2_pool_float_relaxed.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|
| H A D | max_pool_float_1.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|
| H A D | max_pool_float_1_relaxed.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|
| H A D | max_pool_quant8_1.model.cpp | 7 auto cons1 = model->addOperand(&type1); local
13 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
18 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
|