| /external/caliper/caliper/src/main/java/com/google/caliper/model/ |
| package-info.java | 18 * These classes model the data that is collected by the caliper {@linkplain
25 package com.google.caliper.model
|
| /frameworks/ml/nn/runtime/test/generated/models/ |
| conv_1_h3_w2_SAME.model.cpp | 1 void CreateModel(Model *model) {
8 auto pad0 = model->addOperand(&type0);
9 auto pad1 = model->addOperand(&type0);
10 auto b5 = model->addOperand(&type0);
11 auto b6 = model->addOperand(&type0);
12 auto b7 = model->addOperand(&type0);
13 auto op2 = model->addOperand(&type1);
14 auto op3 = model->addOperand(&type2);
15 auto op0 = model->addOperand(&type3)
[all...] |
| conv_3_h3_w2_SAME.model.cpp | 1 void CreateModel(Model *model) {
7 auto pad0 = model->addOperand(&type0);
8 auto pad1 = model->addOperand(&type0);
9 auto b5 = model->addOperand(&type0);
10 auto b6 = model->addOperand(&type0);
11 auto b7 = model->addOperand(&type0);
12 auto op2 = model->addOperand(&type1);
13 auto op3 = model->addOperand(&type1);
14 auto op0 = model->addOperand(&type2)
[all...] |
| depthwise_conv.model.cpp | 1 void CreateModel(Model *model) {
7 auto pad0 = model->addOperand(&type0);
8 auto b5 = model->addOperand(&type0);
9 auto b6 = model->addOperand(&type0);
10 auto b7 = model->addOperand(&type0);
11 auto b8 = model->addOperand(&type0);
12 auto op2 = model->addOperand(&type1);
13 auto op3 = model->addOperand(&type1);
14 auto op0 = model->addOperand(&type2)
[all...] |
| floor.model.cpp | 2 void CreateModel(Model *model) {
5 auto op1 = model->addOperand(&type0);
6 auto op2 = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_FLOOR, {op1}, {op2});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| l2_normalization.model.cpp | 2 void CreateModel(Model *model) {
5 auto op1 = model->addOperand(&type0);
6 auto op2 = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| l2_normalization_large.model.cpp | 2 void CreateModel(Model *model) {
5 auto op1 = model->addOperand(&type0);
6 auto op2 = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| logistic_float_1.model.cpp | 2 void CreateModel(Model *model) {
5 auto op1 = model->addOperand(&type0);
6 auto op3 = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_LOGISTIC, {op1}, {op3});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| logistic_float_2.model.cpp | 2 void CreateModel(Model *model) {
5 auto input = model->addOperand(&type0);
6 auto output = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_LOGISTIC, {input}, {output});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| relu1_float_1.model.cpp | 2 void CreateModel(Model *model) {
5 auto op1 = model->addOperand(&type0);
6 auto op2 = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_RELU1, {op1}, {op2});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| relu1_float_2.model.cpp | 2 void CreateModel(Model *model) {
5 auto input = model->addOperand(&type0);
6 auto output = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_RELU1, {input}, {output});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| relu1_quant8_1.model.cpp | 2 void CreateModel(Model *model) {
5 auto op1 = model->addOperand(&type0);
6 auto op2 = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_RELU1, {op1}, {op2});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| relu1_quant8_2.model.cpp | 2 void CreateModel(Model *model) {
5 auto input = model->addOperand(&type0);
6 auto output = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_RELU1, {input}, {output});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| relu6_float_1.model.cpp | 2 void CreateModel(Model *model) {
5 auto op1 = model->addOperand(&type0);
6 auto op2 = model->addOperand(&type0);
8 model->addOperation(ANEURALNETWORKS_RELU6, {op1}, {op2});
10 model->identifyInputsAndOutputs(
13 assert(model->isValid());
|
| /frameworks/ml/nn/tools/test_generator/tests/P_explicit/ |
| explicit_add.mod.py | 4 model = Model() variable
5 model = model.RawAdd(i1, i1).To(i0) variable
6 model = model.RawAdd(i0, i1).To(i2) variable
|
| /frameworks/ml/nn/runtime/test/specs/ |
| dequantize.mod.py | 0 # model
2 model = Model() variable
5 model = model.Operation("DEQUANTIZE", i1).To(i2) variable
|
| floor.mod.py | 0 # model
2 model = Model() variable
5 model = model.Operation("FLOOR", i1).To(i2) variable
|
| l2_normalization.mod.py | 17 model = Model() variable
22 model = model.Operation("L2_NORMALIZATION", i1).To(i2) variable
|
| l2_normalization_large.mod.py | 17 model = Model() variable
22 model = model.Operation("L2_NORMALIZATION", i1).To(i2) variable
|
| logistic_float_1.mod.py | 17 # model
18 model = Model() variable
22 model = model.Operation("LOGISTIC", i1).To(i3) variable
|
| logistic_quant8_1.mod.py | 17 # model
18 model = Model() variable
22 model = model.Operation("LOGISTIC", i1).To(i3) variable
|
| relu1_float_1.mod.py | 17 # model
18 model = Model() variable
21 model = model.Operation("RELU1", i1).To(i2) variable
|
| relu6_float_1.mod.py | 17 # model
18 model = Model() variable
21 model = model.Operation("RELU6", i1).To(i2) variable
|
| relu_float_1.mod.py | 17 # model
18 model = Model() variable
21 model = model.Operation("RELU", i1).To(i2) variable
|
| tanh.mod.py | 0 # model
2 model = Model() variable
6 model = model.Operation("TANH", i1).To(i2) variable
|
