/frameworks/ml/nn/runtime/test/generated/models/ |
H A D | floor_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_FLOOR, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | l2_normalization_2_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | l2_normalization_large_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | l2_normalization_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | logistic_float_1_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op3 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_LOGISTIC, {op1}, {op3}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | logistic_float_2_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto input = model->addOperand(&type0); 6 auto output = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_LOGISTIC, {input}, {output}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | relu1_float_1_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_RELU1, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | relu1_float_2_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto input = model->addOperand(&type0); 6 auto output = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_RELU1, {input}, {output}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | relu6_float_1_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_RELU6, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | relu6_float_2_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto input = model->addOperand(&type0); 6 auto output = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_RELU6, {input}, {output}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | relu_float_1_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_RELU, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | relu_float_2_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto input = model->addOperand(&type0); 6 auto output = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_RELU, {input}, {output}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | tanh_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 5 auto op1 = model->addOperand(&type0); 6 auto op2 = model->addOperand(&type0); 8 model->addOperation(ANEURALNETWORKS_TANH, {op1}, {op2}); 10 model->identifyInputsAndOutputs( 14 model->relaxComputationFloat32toFloat16(true); 15 assert(model->isValid());
|
H A D | softmax_float_1_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 6 auto input = model->addOperand(&type0); 7 auto beta = model->addOperand(&type1); 8 auto output = model->addOperand(&type0); 11 model->setOperandValue(beta, beta_init, sizeof(float) * 1); 12 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); 14 model->identifyInputsAndOutputs( 18 model->relaxComputationFloat32toFloat16(true); 19 assert(model->isValid());
|
H A D | softmax_float_2_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 6 auto input = model->addOperand(&type0); 7 auto beta = model->addOperand(&type1); 8 auto output = model->addOperand(&type0); 11 model->setOperandValue(beta, beta_init, sizeof(float) * 1); 12 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}); 14 model->identifyInputsAndOutputs( 18 model->relaxComputationFloat32toFloat16(true); 19 assert(model->isValid());
|
H A D | transpose_relaxed.model.cpp | 2 void CreateModel(Model *model) { argument 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( 18 model->relaxComputationFloat32toFloat16(true); 19 assert(model->isValid());
|
/frameworks/ml/nn/runtime/test/specs/V1_1/ |
H A D | add_relaxed.mod.py | 17 # model 18 model = Model() variable 23 model = model.Operation("ADD", i1, i2, act).To(i3) variable 24 model = model.RelaxedExecution(True) variable
|
H A D | batch_to_space_float_1_relaxed.mod.py | 18 model = Model() variable 23 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output) variable 24 model = model.RelaxedExecution(True) variable
|
H A D | batch_to_space_relaxed.mod.py | 17 model = Model() variable 22 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output) variable 23 model = model.RelaxedExecution(True) variable
|
H A D | concat_float_1_relaxed.mod.py | 17 # model 18 model = Model() variable 23 model = model.Operation("CONCATENATION", i1, i2, axis0).To(r) variable 24 model = model.RelaxedExecution(True) variable
|
H A D | depth_to_space_float_1_relaxed.mod.py | 17 model = Model() variable 22 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output) variable 23 model = model.RelaxedExecution(True) variable
|
H A D | depth_to_space_float_2_relaxed.mod.py | 17 model = Model() variable 22 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output) variable 23 model = model.RelaxedExecution(True) variable
|
H A D | depth_to_space_float_3_relaxed.mod.py | 17 model = Model() variable 22 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output) variable 23 model = model.RelaxedExecution(True) variable
|
H A D | dequantize_relaxed.mod.py | 17 # model 18 model = Model() variable 21 model = model.Operation("DEQUANTIZE", i1).To(i2) variable 22 model = model.RelaxedExecution(True) variable
|
H A D | div_broadcast_float_relaxed.mod.py | 17 # model 18 model = Model() variable 23 model = model.Operation("DIV", i1, i2, act).To(i3) variable 24 model = model.RelaxedExecution(True) variable
|