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-rw-r--r--delegate/test/ActivationTest.cpp482
1 files changed, 138 insertions, 344 deletions
diff --git a/delegate/test/ActivationTest.cpp b/delegate/test/ActivationTest.cpp
index 5eafa49948..113e645f82 100644
--- a/delegate/test/ActivationTest.cpp
+++ b/delegate/test/ActivationTest.cpp
@@ -15,370 +15,164 @@
namespace armnnDelegate
{
-
-void ActivationReLuTest(std::vector<armnn::BackendId>& backends)
+TEST_SUITE("Activation_Tests")
{
- std::vector<float> inputData = {
- -0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
- -1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
- // Calculate output values for input.
- auto f = [](float value)
+ TEST_CASE("Activation_ReLu_Test")
{
- return std::fmax(0.0f, value);
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-
- ActivationTest(tflite::BuiltinOperator_RELU,
- backends,
- inputData,
- outputExpectedData);
-}
-
-void ActivationBoundedReluTest(std::vector<armnn::BackendId>& backends)
-{
- std::vector<float> inputData = {
+ std::vector<float> inputData = {
-0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
-1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
- const float a = 6.0f;
- const float b = 0.0f;
- // Calculate output values for input.
- auto f = [a, b](float value)
- {
- return std::min(a, std::max(b, value));
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+ // Calculate output values for input.
+ auto f = [](float value) { return std::fmax(0.0f, value); };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+ ActivationTest(tflite::BuiltinOperator_RELU, inputData, outputExpectedData);
+ }
- ActivationTest(tflite::BuiltinOperator_RELU6,
- backends,
- inputData,
- outputExpectedData);
-}
-
-void ActivationSigmoidTest(std::vector<armnn::BackendId>& backends)
-{
- std::vector<float> inputData = {
- -0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
- -1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
-
- // Calculate output values for input.
- auto f = [](float value)
+ TEST_CASE("Activation_Bounded_Relu6_Test")
{
- return 1.0f / (1.0f + std::exp(-value));
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-
- ActivationTest(tflite::BuiltinOperator_LOGISTIC,
- backends,
- inputData,
- outputExpectedData);
-}
-
-
-void ActivationTanHTest(std::vector<armnn::BackendId>& backends)
-{
- std::vector<float> inputData = {
- -0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
- -1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
-
- // Calculate output values for input.
- auto f = [](float value)
+ std::vector<float> inputData = { -0.1f, -0.2f, -0.3f, -0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
+ -1.0f, -2.0f, -3.0f, -4.0f,
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
+
+ const float a = 6.0f;
+ const float b = 0.0f;
+ // Calculate output values for input.
+ auto f = [a, b](float value)
+ {
+ return std::min(a, std::max(b, value));
+ };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+ ActivationTest(tflite::BuiltinOperator_RELU6,
+ inputData, outputExpectedData);
+ }
+
+ TEST_CASE("Activation_Sigmoid_Test")
{
- return tanhf(value);
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+ std::vector<float> inputData = { -0.1f, -0.2f, -0.3f, -0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
+ -1.0f, -2.0f, -3.0f, -4.0f,
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
- ActivationTest(tflite::BuiltinOperator_TANH,
- backends,
- inputData,
- outputExpectedData);
-}
+ // Calculate output values for input.
+ auto f = [](float value) { return 1.0f / (1.0f + std::exp(-value)); };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-void ActivationEluTest(std::vector<armnn::BackendId>& backends)
-{
- std::vector<float> inputData = {
- -0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
- -1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
+ ActivationTest(tflite::BuiltinOperator_LOGISTIC, inputData, outputExpectedData);
+ }
- // Calculate output values for input.
- auto f = [](float value)
+ TEST_CASE("Activation_TanH_Test")
{
- if (value < 0)
- {
- // alpha * (exp(x) - 1)
- return 1 * (std::exp(value) - 1);
- }
- return value;
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+ std::vector<float> inputData = { -0.1f, -0.2f, -0.3f, -0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
+ -1.0f, -2.0f, -3.0f, -4.0f,
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
- ActivationTest(tflite::BuiltinOperator_ELU,
- backends,
- inputData,
- outputExpectedData);
-}
+ // Calculate output values for input.
+ auto f = [](float value) { return tanhf(value); };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-void ActivationHardSwishTest(std::vector<armnn::BackendId>& backends)
-{
- std::vector<float> inputData = {
- -0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
- -1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
+ ActivationTest(tflite::BuiltinOperator_TANH, inputData, outputExpectedData);
+ }
- // Calculate output values for input.
- auto f = [](float x)
+ TEST_CASE("Activation_Elu_Test")
{
- // Break down the calculation to help with verification.
- // hard_swish(x) = x * relu6(x+3) / 6
- // relu6(x) = min(max(x,0),6)
- float reLu6_step1 = std::max((x + 3),0.0f);
- float reLu6Complete = std::min(reLu6_step1, 6.0f);
- float hardSwish_step1 = x * reLu6Complete;
- float result = hardSwish_step1 / 6;
- return result;
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-
- ActivationTest(tflite::BuiltinOperator_HARD_SWISH,
- backends,
- inputData,
- outputExpectedData);
-}
-
-void ActivationLeakyReLuTest(std::vector<armnn::BackendId>& backends)
-{
- std::vector<float> inputData = {
- -0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
- -1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
-
- float alpha = 0.3f;
-
- // Calculate output values for input.
- auto f = [alpha](float value)
- {
- return value > 0 ? value : value * alpha;
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-
- ActivationTest(tflite::BuiltinOperator_LEAKY_RELU,
- backends,
- inputData,
- outputExpectedData,
- alpha);
-}
-
-void ActivationGeluTest(std::vector<armnn::BackendId>& backends)
-{
- std::vector<float> inputData =
+ std::vector<float> inputData = { -0.1f, -0.2f, -0.3f, -0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
+ -1.0f, -2.0f, -3.0f, -4.0f,
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
+
+ // Calculate output values for input.
+ auto f = [](float value) {
+ if (value < 0)
+ {
+ // alpha * (exp(x) - 1)
+ return 1 * (std::exp(value) - 1);
+ }
+ return value;
+ };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+ ActivationTest(tflite::BuiltinOperator_ELU, inputData, outputExpectedData);
+ }
+
+ TEST_CASE("Activation_HardSwish_Test")
{
- -0.1f, -0.2f, -0.3f, -0.4f,
- 0.1f, 0.2f, 0.3f, 0.4f,
- -1.0f, -2.0f, -3.0f, -4.0f,
- 1.0f, 2.0f, 3.0f, 4.0f
- };
-
- // Calculate output values for input.
- auto f = [](float x)
+ std::vector<float> inputData = { -0.1f, -0.2f, -0.3f, -0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
+ -1.0f, -2.0f, -3.0f, -4.0f,
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
+
+ // Calculate output values for input.
+ auto f = [](float x) {
+ // Break down the calculation to help with verification.
+ // hard_swish(x) = x * relu6(x+3) / 6
+ // relu6(x) = min(max(x,0),6)
+ float reLu6_step1 = std::max((x + 3), 0.0f);
+ float reLu6Complete = std::min(reLu6_step1, 6.0f);
+ float hardSwish_step1 = x * reLu6Complete;
+ float result = hardSwish_step1 / 6;
+ return result;
+ };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+ ActivationTest(tflite::BuiltinOperator_HARD_SWISH, inputData, outputExpectedData);
+ }
+
+ TEST_CASE("Activation_LeakyRelu_Test")
{
- // gelu(x) = x * 1/2 * (1 + erf(x / sqrt(2))),
- // where erf is Gaussian error function
- auto result = x * (0.5f * (1.0f + erff(static_cast<float>(x / std::sqrt(2)))));
- return result;
- };
- std::vector<float> outputExpectedData(inputData.size());
- std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-
- ActivationTest(tflite::BuiltinOperator_GELU,
- backends,
- inputData,
- outputExpectedData);
-}
-
-TEST_SUITE("Activation_CpuRefTests")
-{
-
-TEST_CASE ("Activation_ReLu_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationReLuTest(backends);
-}
-
-TEST_CASE ("Activation_Bounded_Relu6_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationBoundedReluTest(backends);
-}
-
-TEST_CASE ("Activation_Sigmoid_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationSigmoidTest(backends);
-}
-
-TEST_CASE ("Activation_TanH_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationTanHTest(backends);
-}
-
-TEST_CASE ("Activation_Elu_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationEluTest(backends);
-}
+ std::vector<float> inputData = { -0.1f, -0.2f, -0.3f, -0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
+ -1.0f, -2.0f, -3.0f, -4.0f,
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
-TEST_CASE ("Activation_HardSwish_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationHardSwishTest(backends);
-}
+ float alpha = 0.3f;
-TEST_CASE ("Activation_LeakyRelu_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationLeakyReLuTest(backends);
-}
+ // Calculate output values for input.
+ auto f = [alpha](float value) { return value > 0 ? value : value * alpha; };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
-TEST_CASE ("Activation_Gelu_CpuRef_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
- ActivationGeluTest(backends);
-}
-
-}
+ ActivationTest(tflite::BuiltinOperator_LEAKY_RELU, inputData, outputExpectedData, alpha);
+ }
-TEST_SUITE("Activation_CpuAccTests")
-{
-
-TEST_CASE ("Activation_ReLu_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationReLuTest(backends);
-}
-
-TEST_CASE ("Activation_Bounded_Relu6_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationBoundedReluTest(backends);
-}
-
-TEST_CASE ("Activation_Sigmoid_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationSigmoidTest(backends);
-}
-
-TEST_CASE ("Activation_TanH_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationTanHTest(backends);
-}
-
-TEST_CASE ("Activation_Elu_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationEluTest(backends);
-}
-
-TEST_CASE ("Activation_HardSwish_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationHardSwishTest(backends);
-}
-
-TEST_CASE ("Activation_LeakyRelu_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationLeakyReLuTest(backends);
-}
-
-TEST_CASE ("Activation_Gelu_CpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
- ActivationGeluTest(backends);
-}
-
-}
-
-TEST_SUITE("Activation_GpuAccTests")
-{
-
-TEST_CASE ("Activation_ReLu_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationReLuTest(backends);
-}
-
-TEST_CASE ("Activation_Bounded_Relu6_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationBoundedReluTest(backends);
-}
-
-TEST_CASE ("Activation_Sigmoid_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationSigmoidTest(backends);
-}
-
-TEST_CASE ("Activation_TanH_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationTanHTest(backends);
-}
-
-TEST_CASE ("Activation_Elu_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationEluTest(backends);
-}
-
-TEST_CASE ("Activation_HardSwish_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationHardSwishTest(backends);
-}
-
-TEST_CASE ("Activation_LeakyRelu_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationLeakyReLuTest(backends);
-}
-
-TEST_CASE ("Activation_Gelu_GpuAcc_Test")
-{
- std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
- ActivationGeluTest(backends);
-}
-
-}
-
-} // namespace armnnDelegate \ No newline at end of file
+ TEST_CASE("Activation_Gelu_Test")
+ {
+ std::vector<float> inputData = { -0.1f, -0.2f, -0.3f, -0.4f,
+ 0.1f, 0.2f, 0.3f, 0.4f,
+ -1.0f, -2.0f, -3.0f, -4.0f,
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
+
+ // Calculate output values for input.
+ auto f = [](float x) {
+ // gelu(x) = x * 1/2 * (1 + erf(x / sqrt(2))),
+ // where erf is Gaussian error function
+ auto result = x * (0.5f * (1.0f + erff(static_cast<float>(x / std::sqrt(2)))));
+ return result;
+ };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+ ActivationTest(tflite::BuiltinOperator_GELU, inputData, outputExpectedData);
+ }
+}
+
+} // namespace armnnDelegate \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 12:29:47 +0000