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[nnfw_tests] Move a test from wrong location #13545

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Jul 29, 2024
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[nnfw_tests] Move a test from wrong location #13545

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62 changes: 31 additions & 31 deletions tests/nnfw_api/src/GenModelTests/BranchModelTrain.test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -56,28 +56,26 @@ TEST_F(GenModelTrain, BranchOps_FC_Add)

SUCCEED();
}
}

TEST_F(GenModelTrain, BranchOps_FC_Sub)
{
// (( Input 0 )) --------------\
// |=> [ Sub ] -> (( Output 0 ))
// (( Input 1 )) -> [ FC ] ----/
// (( Input 0 )) -> [ FC ] -> (fc_out) --------------------------╲
// ╲ |=> [ Add ] -> (( Output 0 ))
// ╲-> [ Relu6 ]⎼> (ea_out) -╱
{
CirclePlusGen cgen;

uint32_t weight_buf = cgen.addBuffer(std::vector<float>(8 * 2, 0.f));
uint32_t bias_buf = cgen.addBuffer(std::vector<float>(8, 0.f));
int input0 = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
int input1 = cgen.addTensor({{1, 2}, circle::TensorType::TensorType_FLOAT32});
int input0 = cgen.addTensor({{1, 2}, circle::TensorType::TensorType_FLOAT32});
int weight = cgen.addTensor({{8, 2}, circle::TensorType::TensorType_FLOAT32, weight_buf});
int bias = cgen.addTensor({{8}, circle::TensorType::TensorType_FLOAT32, bias_buf});
int fc_output = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
int ea_output = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
int output = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorFullyConnected({{input1, weight, bias}, {fc_output}});
cgen.addOperatorSub({{input0, fc_output}, {output}},
cgen.addOperatorFullyConnected({{input0, weight, bias}, {fc_output}});
cgen.addOperatorRelu6({{fc_output}, {ea_output}});
cgen.addOperatorAdd({{fc_output, ea_output}, {output}},
circle::ActivationFunctionType::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({input0, input1}, {output});
cgen.setInputsAndOutputs({input0}, {output});

float learning_rate = 0.01f;
int32_t batch_size = 1;
Expand All @@ -87,37 +85,40 @@ TEST_F(GenModelTrain, BranchOps_FC_Sub)
NNFW_TRAIN_TRAINABLE_ALL});

_context = std::make_unique<GenModelTrainContext>(cgen.finish());
_context->addTrainCase(uniformTCD<float>(
{{{0, 1, 2, 3, 4, 5, 1, 3}, {6, 7}}, {{5, 4, 3, 2, 1, 0, 2, 1}, {7, 6}}}, // inputs
{{{2, 1, 5, 5, 2, 1, 5, 5}}, {{2, 1, 5, 5, 2, 1, 5, 6}}}, // expected
{{7.3265f}, {4.6811f}, {3.6735f}, {3.2863f}} // loss
));
_context->addTrainCase(
uniformTCD<float>({{{1, 3}}, {{2, 1}}}, // inputs
{{{2, 1, 5, 5, 2, 1, 5, 5}}, {{2, 1, 5, 5, 2, 1, 5, 6}}}, // expected
// TODO Modify loss values to results of tensorflow
{{14.0124f}, {11.0036f}, {8.1681f}, {6.0974f}} // loss
));

_context->setBackends({"train"});
_context->setEpoch(4);

SUCCEED();
}
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This block just moved from BranchOps_FC_Sub.

}

// (( Input 0 )) -> [ FC ] -> (fc_out) --------------------------╲
// ╲ |=> [ Add ] -> (( Output 0 ))
// ╲-> [ Relu6 ]⎼> (ea_out) -╱
TEST_F(GenModelTrain, BranchOps_FC_Sub)
{
// (( Input 0 )) --------------\
// |=> [ Sub ] -> (( Output 0 ))
// (( Input 1 )) -> [ FC ] ----/
{
CirclePlusGen cgen;

uint32_t weight_buf = cgen.addBuffer(std::vector<float>(8 * 2, 0.f));
uint32_t bias_buf = cgen.addBuffer(std::vector<float>(8, 0.f));
int input0 = cgen.addTensor({{1, 2}, circle::TensorType::TensorType_FLOAT32});
int input0 = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
int input1 = cgen.addTensor({{1, 2}, circle::TensorType::TensorType_FLOAT32});
int weight = cgen.addTensor({{8, 2}, circle::TensorType::TensorType_FLOAT32, weight_buf});
int bias = cgen.addTensor({{8}, circle::TensorType::TensorType_FLOAT32, bias_buf});
int fc_output = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
int ea_output = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
int output = cgen.addTensor({{1, 8}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorFullyConnected({{input0, weight, bias}, {fc_output}});
cgen.addOperatorRelu6({{fc_output}, {ea_output}});
cgen.addOperatorAdd({{fc_output, ea_output}, {output}},
cgen.addOperatorFullyConnected({{input1, weight, bias}, {fc_output}});
cgen.addOperatorSub({{input0, fc_output}, {output}},
circle::ActivationFunctionType::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({input0}, {output});
cgen.setInputsAndOutputs({input0, input1}, {output});

float learning_rate = 0.01f;
int32_t batch_size = 1;
Expand All @@ -127,12 +128,11 @@ TEST_F(GenModelTrain, BranchOps_FC_Sub)
NNFW_TRAIN_TRAINABLE_ALL});

_context = std::make_unique<GenModelTrainContext>(cgen.finish());
_context->addTrainCase(
uniformTCD<float>({{{1, 3}}, {{2, 1}}}, // inputs
{{{2, 1, 5, 5, 2, 1, 5, 5}}, {{2, 1, 5, 5, 2, 1, 5, 6}}}, // expected
// TODO Modify loss values to results of tensorflow
{{14.0124f}, {11.0036f}, {8.1681f}, {6.0974f}} // loss
));
_context->addTrainCase(uniformTCD<float>(
{{{0, 1, 2, 3, 4, 5, 1, 3}, {6, 7}}, {{5, 4, 3, 2, 1, 0, 2, 1}, {7, 6}}}, // inputs
{{{2, 1, 5, 5, 2, 1, 5, 5}}, {{2, 1, 5, 5, 2, 1, 5, 6}}}, // expected
{{7.3265f}, {4.6811f}, {3.6735f}, {3.2863f}} // loss
));

_context->setBackends({"train"});
_context->setEpoch(4);
Expand Down