Searched defs:model (Results 151 - 175 of 784) sorted by relevance

1234567891011>>

/frameworks/ml/nn/runtime/test/specs/V1_1/
H A Dtranspose_float_1_relaxed.mod.py17 model = Model() variable
22 model = model.Operation("TRANSPOSE", i1, perms).To(output) variable
23 model = model.RelaxedExecution(True) variable
H A Dtranspose_quant8_1.mod.py0 model = Model()
6 model = model.Operation("TRANSPOSE", i1, perms).To(output) variable
1 model = Model() variable
H A Dtranspose_relaxed.mod.py17 model = Model() variable
22 model = model.Operation("TRANSPOSE", i1, perms).To(output) variable
23 model = model.RelaxedExecution(True) variable
/frameworks/ml/nn/tools/test_generator/tests/P_full/
H A Daddfloat.mod.py0 # model
2 model = Model() variable
7 model = model.Operation("ADD", i1, i2, b0).To(i3) variable
/frameworks/ml/nn/tools/test_generator/tests/P_quantized_avgpool/
H A Daverpoolfloat.mod.py0 # model
2 model = Model() variable
7 model = model.Operation("AVERAGE_POOL", i1, cons1, cons1, cons1, cons1, cons1, act).To(o) variable
/frameworks/ml/nn/tools/test_generator/tests/P_vts_full/
H A Dvts_full.mod.py3 # model
4 model = Model() variable
10 model.Operation("ADD", i0, p0, b0).To(o)
/frameworks/support/work/workmanager/src/main/java/androidx/work/impl/model/
H A DDependency.java17 package androidx.work.impl.model;
H A DWorkName.java17 package androidx.work.impl.model;
H A DWorkTag.java17 package androidx.work.impl.model;
/frameworks/base/packages/PrintSpooler/src/com/android/printspooler/model/
H A DOpenDocumentCallback.java17 package com.android.printspooler.model;
/frameworks/ml/nn/runtime/test/
H A DBridge.cpp30 void graphDump(const char* name, const ModelBuilder* model, std::ostream& outStream) { argument
32 model->setHidlModel(&hidlModel);
/frameworks/ml/nn/runtime/test/generated/models/
H A Dadd.model.cpp2 void CreateModel(Model *model) { argument
6 auto op1 = model->addOperand(&type0);
7 auto op2 = model->addOperand(&type0);
8 auto act = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type0);
12 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dadd_broadcast_quant8.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto act = model->addOperand(&type2);
10 auto op3 = model->addOperand(&type1);
13 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
14 model->addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
16 model->identifyInputsAndOutputs(
19 assert(model->isValid());
H A Dadd_quant8.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto act = model->addOperand(&type2);
10 auto op3 = model->addOperand(&type1);
13 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
14 model->addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
16 model->identifyInputsAndOutputs(
19 assert(model->isValid());
H A Dadd_relaxed.model.cpp2 void CreateModel(Model *model) { argument
6 auto op1 = model->addOperand(&type0);
7 auto op2 = model->addOperand(&type0);
8 auto act = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type0);
12 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model
[all...]
H A Dbatch_to_space.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
13 model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dbatch_to_space_float_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
13 model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dbatch_to_space_float_1_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
13 model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dbatch_to_space_quant8_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
13 model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dbatch_to_space_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
13 model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dconcat_float_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type0);
9 auto axis0 = model->addOperand(&type1);
10 auto result = model->addOperand(&type2);
13 model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
14 model->addOperation(ANEURALNETWORKS_CONCATENATION, {op1, op2, axis0}, {result});
16 model->identifyInputsAndOutputs(
19 assert(model->isValid());
H A Dconcat_float_1_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type0);
9 auto axis0 = model->addOperand(&type1);
10 auto result = model->addOperand(&type2);
13 model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
14 model->addOperation(ANEURALNETWORKS_CONCATENATION, {op1, op2, axis0}, {result});
16 model->identifyInputsAndOutputs(
20 model->relaxComputationFloat32toFloat16(true);
21 assert(model
[all...]
H A Dconcat_float_2.model.cpp2 void CreateModel(Model *model) { argument
8 auto input1 = model->addOperand(&type0);
9 auto input2 = model->addOperand(&type1);
10 auto axis0 = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
15 model->addOperation(ANEURALNETWORKS_CONCATENATION, {input1, input2, axis0}, {output});
17 model->identifyInputsAndOutputs(
20 assert(model->isValid());
H A Dconcat_float_2_relaxed.model.cpp2 void CreateModel(Model *model) { argument
8 auto input1 = model->addOperand(&type0);
9 auto input2 = model->addOperand(&type1);
10 auto axis0 = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
15 model->addOperation(ANEURALNETWORKS_CONCATENATION, {input1, input2, axis0}, {output});
17 model->identifyInputsAndOutputs(
21 model->relaxComputationFloat32toFloat16(true);
22 assert(model
[all...]
H A Dconcat_float_3.model.cpp2 void CreateModel(Model *model) { argument
8 auto input1 = model->addOperand(&type0);
9 auto input2 = model->addOperand(&type1);
10 auto axis1 = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(axis1, axis1_init, sizeof(int32_t) * 1);
15 model->addOperation(ANEURALNETWORKS_CONCATENATION, {input1, input2, axis1}, {output});
17 model->identifyInputsAndOutputs(
20 assert(model->isValid());

Completed in 180 milliseconds

1234567891011>>