| /frameworks/ml/nn/runtime/test/generated/models/ |
| strided_slice_float_9.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_qaunt8_10.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_qaunt8_11.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_1.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_2.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_3.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_4.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_5.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_6.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_7.model.cpp | 2 void CreateModel(Model *model) {
7 auto input = model->addOperand(&type0);
8 auto begins = model->addOperand(&type1);
9 auto ends = model->addOperand(&type1);
10 auto strides = model->addOperand(&type1);
11 auto beginMask = model->addOperand(&type2);
12 auto endMask = model->addOperand(&type2);
13 auto shrinkAxisMask = model->addOperand(&type2);
14 auto output = model->addOperand(&type0)
[all...] |
| strided_slice_quant8_8.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| strided_slice_quant8_9.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto begins = model->addOperand(&type1);
10 auto ends = model->addOperand(&type1);
11 auto strides = model->addOperand(&type1);
12 auto beginMask = model->addOperand(&type2);
13 auto endMask = model->addOperand(&type2);
14 auto shrinkAxisMask = model->addOperand(&type2);
15 auto output = model->addOperand(&type3)
[all...] |
| transpose.model.cpp | 2 void CreateModel(Model *model) {
6 auto input = model->addOperand(&type0);
7 auto perms = model->addOperand(&type1);
8 auto output = model->addOperand(&type0);
11 model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
12 model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
14 model->identifyInputsAndOutputs(
17 assert(model->isValid());
|
| fully_connected_float_large_weights_as_inputs_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto op1 = model->addOperand(&type0);
9 auto op2 = model->addOperand(&type0);
10 auto b0 = model->addOperand(&type1);
11 auto op3 = model->addOperand(&type2);
12 auto act = model->addOperand(&type3);
15 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
16 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
18 model->identifyInputsAndOutputs
[all...] |
| fully_connected_float_weights_as_inputs_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto op1 = model->addOperand(&type0);
9 auto op2 = model->addOperand(&type1);
10 auto b0 = model->addOperand(&type2);
11 auto op3 = model->addOperand(&type0);
12 auto act = model->addOperand(&type3);
15 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
16 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
18 model->identifyInputsAndOutputs
[all...] |
| lsh_projection_weights_as_inputs_relaxed.model.cpp | 2 void CreateModel(Model *model) {
9 auto hash = model->addOperand(&type0);
10 auto lookup = model->addOperand(&type1);
11 auto weight = model->addOperand(&type2);
12 auto type_param = model->addOperand(&type3);
13 auto output = model->addOperand(&type4);
16 model->setOperandValue(type_param, type_param_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_LSH_PROJECTION, {hash, lookup, weight, type_param}, {output});
19 model->identifyInputsAndOutputs
[all...] |
| mean_float_1_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto axis = model->addOperand(&type1);
10 auto keepDims = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
19 model->identifyInputsAndOutputs
[all...] |
| mean_float_2_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto axis = model->addOperand(&type1);
10 auto keepDims = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
19 model->identifyInputsAndOutputs
[all...] |
| mean_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto axis = model->addOperand(&type1);
10 auto keepDims = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
19 model->identifyInputsAndOutputs
[all...] |
| resize_bilinear_2_relaxed.model.cpp | 2 void CreateModel(Model *model) {
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto height = model->addOperand(&type2);
10 auto width = model->addOperand(&type2);
13 model->setOperandValue(height, height_init, sizeof(int32_t) * 1);
15 model->setOperandValue(width, width_init, sizeof(int32_t) * 1);
16 model->addOperation(ANEURALNETWORKS_RESIZE_BILINEAR, {op1, height, width}, {op2});
18 model->identifyInputsAndOutputs
[all...] |
| resize_bilinear_relaxed.model.cpp | 2 void CreateModel(Model *model) {
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto height = model->addOperand(&type2);
10 auto width = model->addOperand(&type2);
13 model->setOperandValue(height, height_init, sizeof(int32_t) * 1);
15 model->setOperandValue(width, width_init, sizeof(int32_t) * 1);
16 model->addOperation(ANEURALNETWORKS_RESIZE_BILINEAR, {op1, height, width}, {op2});
18 model->identifyInputsAndOutputs
[all...] |
| space_to_batch_float_1_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs
[all...] |
| space_to_batch_float_2_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs
[all...] |
| space_to_batch_float_3_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs
[all...] |
| space_to_batch_relaxed.model.cpp | 2 void CreateModel(Model *model) {
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs
[all...] |
