Merge changes from topics "replace_asymm", "fp16-op-add"
* changes:
Replace TENSOR_QUANT16_ASYMM with TENSOR_QUANT16_SYMM
Fix VTS ValidationTest for 1.2 ops.
Adds float16 support to generated tests.
Autogenerates VTS ValidationTest tests.
Fix VTS ValidationTest for 1.2 ops.
Separates VTS tests by HAL version.
diff --git a/neuralnetworks/1.0/vts/functional/Android.bp b/neuralnetworks/1.0/vts/functional/Android.bp
index ffba45c..234527a 100644
--- a/neuralnetworks/1.0/vts/functional/Android.bp
+++ b/neuralnetworks/1.0/vts/functional/Android.bp
@@ -39,17 +39,14 @@
],
}
-cc_test {
- name: "VtsHalNeuralnetworksV1_0TargetTest",
+cc_defaults {
+ name: "VtsHalNeuralNetworksTargetTestDefaults",
+ defaults: ["VtsHalTargetTestDefaults"],
srcs: [
- "BasicTests.cpp",
- "GeneratedTests.cpp",
"ValidateModel.cpp",
"ValidateRequest.cpp",
- "ValidationTests.cpp",
"VtsHalNeuralnetworks.cpp",
],
- defaults: ["VtsHalTargetTestDefaults"],
static_libs: [
"android.hardware.neuralnetworks@1.0",
"android.hardware.neuralnetworks@1.1",
@@ -66,4 +63,22 @@
"libneuralnetworks_generated_test_harness_headers",
"libneuralnetworks_generated_tests",
],
+ // Bug: http://b/74200014 - Disable arm32 asan since it triggers internal
+ // error in ld.gold.
+ arch: {
+ arm: {
+ sanitize: {
+ never: true,
+ },
+ },
+ },
+}
+
+cc_test {
+ name: "VtsHalNeuralnetworksV1_0TargetTest",
+ defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
+ srcs: [
+ "BasicTests.cpp",
+ "GeneratedTests.cpp",
+ ],
}
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
index 1f66c43..802d018 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
@@ -45,6 +45,7 @@
using ::test_helper::Int32Operands;
using ::test_helper::MixedTyped;
using ::test_helper::MixedTypedExample;
+using ::test_helper::MixedTypedIndex;
using ::test_helper::Quant8Operands;
using ::test_helper::resize_accordingly;
@@ -63,14 +64,16 @@
copy_back_<int32_t>(dst, ra, src);
copy_back_<uint8_t>(dst, ra, src);
copy_back_<int16_t>(dst, ra, src);
- static_assert(4 == std::tuple_size<MixedTyped>::value,
+ copy_back_<_Float16>(dst, ra, src);
+ static_assert(5 == std::tuple_size<MixedTyped>::value,
"Number of types in MixedTyped changed, but copy_back function wasn't updated");
}
// Top level driver for models and examples generated by test_generator.py
// Test driver for those generated from ml/nn/runtime/test/spec
void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
- const std::vector<MixedTypedExample>& examples, float fpAtol = 1e-5f,
+ const std::vector<MixedTypedExample>& examples,
+ bool hasRelaxedFloat32Model = false, float fpAtol = 1e-5f,
float fpRtol = 1e-5f) {
const uint32_t INPUT = 0;
const uint32_t OUTPUT = 1;
@@ -78,13 +81,20 @@
int example_no = 1;
for (auto& example : examples) {
SCOPED_TRACE(example_no++);
-
const MixedTyped& inputs = example.operands.first;
const MixedTyped& golden = example.operands.second;
+ const bool hasFloat16Inputs = !std::get<MixedTypedIndex<_Float16>::index>(inputs).empty();
+ if (hasRelaxedFloat32Model || hasFloat16Inputs) {
+ // TODO: Adjust the error limit based on testing.
+ // If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
+ fpAtol = 5.0f * 0.0009765625f;
+ // Set the relative tolerance to be 5ULP of the corresponding FP precision.
+ fpRtol = 5.0f * 0.0009765625f;
+ }
+
std::vector<RequestArgument> inputs_info, outputs_info;
uint32_t inputSize = 0, outputSize = 0;
-
// This function only partially specifies the metadata (vector of RequestArguments).
// The contents are copied over below.
for_all(inputs, [&inputs_info, &inputSize](int index, auto, auto s) {
@@ -228,7 +238,8 @@
ASSERT_NE(nullptr, preparedModel.get());
float fpAtol = 1e-5f, fpRtol = 5.0f * 1.1920928955078125e-7f;
- EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
+ EvaluatePreparedModel(preparedModel, is_ignored, examples,
+ /*hasRelaxedFloat32Model=*/false, fpAtol, fpRtol);
}
void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> create_model,
@@ -272,13 +283,8 @@
EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel.get());
- // TODO: Adjust the error limit based on testing.
- // If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
- float fpAtol = !model.relaxComputationFloat32toFloat16 ? 1e-5f : 5.0f * 0.0009765625f;
- // Set the relative tolerance to be 5ULP of the corresponding FP precision.
- float fpRtol = !model.relaxComputationFloat32toFloat16 ? 5.0f * 1.1920928955078125e-7f
- : 5.0f * 0.0009765625f;
- EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
+ EvaluatePreparedModel(preparedModel, is_ignored, examples,
+ model.relaxComputationFloat32toFloat16);
}
// TODO: Reduce code duplication.
@@ -323,13 +329,8 @@
EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel.get());
- // TODO: Adjust the error limit based on testing.
- // If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
- float fpAtol = !model.relaxComputationFloat32toFloat16 ? 1e-5f : 5.0f * 0.0009765625f;
- // Set the relative tolerance to be 5ULP of the corresponding FP precision.
- float fpRtol = !model.relaxComputationFloat32toFloat16 ? 5.0f * 1.1920928955078125e-7f
- : 5.0f * 0.0009765625f;
- EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
+ EvaluatePreparedModel(preparedModel, is_ignored, examples,
+ model.relaxComputationFloat32toFloat16);
}
} // namespace generated_tests
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTests.cpp b/neuralnetworks/1.0/vts/functional/GeneratedTests.cpp
index ac1ae60..26b4d8b 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTests.cpp
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTests.cpp
@@ -45,6 +45,8 @@
using ::android::nn::allocateSharedMemory;
using ::test_helper::MixedTypedExample;
+std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
+
// in frameworks/ml/nn/runtime/tests/generated/
#include "all_generated_V1_0_vts_tests.cpp"
diff --git a/neuralnetworks/1.0/vts/functional/Models.h b/neuralnetworks/1.0/vts/functional/Models.h
deleted file mode 100644
index 268e671..0000000
--- a/neuralnetworks/1.0/vts/functional/Models.h
+++ /dev/null
@@ -1,200 +0,0 @@
-/*
- * Copyright (C) 2018 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VTS_HAL_NEURALNETWORKS_V1_0_VTS_FUNCTIONAL_MODELS_H
-#define VTS_HAL_NEURALNETWORKS_V1_0_VTS_FUNCTIONAL_MODELS_H
-
-#define LOG_TAG "neuralnetworks_hidl_hal_test"
-
-#include "TestHarness.h"
-
-#include <android/hardware/neuralnetworks/1.0/types.h>
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_0 {
-namespace vts {
-namespace functional {
-
-using MixedTypedExample = test_helper::MixedTypedExample;
-
-#define FOR_EACH_TEST_MODEL(FN) \
- FN(add_broadcast_quant8) \
- FN(add) \
- FN(add_quant8) \
- FN(avg_pool_float_1) \
- FN(avg_pool_float_2) \
- FN(avg_pool_float_3) \
- FN(avg_pool_float_4) \
- FN(avg_pool_float_5) \
- FN(avg_pool_quant8_1) \
- FN(avg_pool_quant8_2) \
- FN(avg_pool_quant8_3) \
- FN(avg_pool_quant8_4) \
- FN(avg_pool_quant8_5) \
- FN(concat_float_1) \
- FN(concat_float_2) \
- FN(concat_float_3) \
- FN(concat_quant8_1) \
- FN(concat_quant8_2) \
- FN(concat_quant8_3) \
- FN(conv_1_h3_w2_SAME) \
- FN(conv_1_h3_w2_VALID) \
- FN(conv_3_h3_w2_SAME) \
- FN(conv_3_h3_w2_VALID) \
- FN(conv_float_2) \
- FN(conv_float_channels) \
- FN(conv_float_channels_weights_as_inputs) \
- FN(conv_float_large) \
- FN(conv_float_large_weights_as_inputs) \
- FN(conv_float) \
- FN(conv_float_weights_as_inputs) \
- FN(conv_quant8_2) \
- FN(conv_quant8_channels) \
- FN(conv_quant8_channels_weights_as_inputs) \
- FN(conv_quant8_large) \
- FN(conv_quant8_large_weights_as_inputs) \
- FN(conv_quant8) \
- FN(conv_quant8_overflow) \
- FN(conv_quant8_overflow_weights_as_inputs) \
- FN(conv_quant8_weights_as_inputs) \
- FN(depth_to_space_float_1) \
- FN(depth_to_space_float_2) \
- FN(depth_to_space_float_3) \
- FN(depth_to_space_quant8_1) \
- FN(depth_to_space_quant8_2) \
- FN(depthwise_conv2d_float_2) \
- FN(depthwise_conv2d_float_large_2) \
- FN(depthwise_conv2d_float_large_2_weights_as_inputs) \
- FN(depthwise_conv2d_float_large) \
- FN(depthwise_conv2d_float_large_weights_as_inputs) \
- FN(depthwise_conv2d_float) \
- FN(depthwise_conv2d_float_weights_as_inputs) \
- FN(depthwise_conv2d_quant8_2) \
- FN(depthwise_conv2d_quant8_large) \
- FN(depthwise_conv2d_quant8_large_weights_as_inputs) \
- FN(depthwise_conv2d_quant8) \
- FN(depthwise_conv2d_quant8_weights_as_inputs) \
- FN(depthwise_conv) \
- FN(dequantize) \
- FN(embedding_lookup) \
- FN(floor) \
- FN(fully_connected_float_2) \
- FN(fully_connected_float_large) \
- FN(fully_connected_float_large_weights_as_inputs) \
- FN(fully_connected_float) \
- FN(fully_connected_float_weights_as_inputs) \
- FN(fully_connected_quant8_2) \
- FN(fully_connected_quant8_large) \
- FN(fully_connected_quant8_large_weights_as_inputs) \
- FN(fully_connected_quant8) \
- FN(fully_connected_quant8_weights_as_inputs) \
- FN(hashtable_lookup_float) \
- FN(hashtable_lookup_quant8) \
- FN(l2_normalization_2) \
- FN(l2_normalization_large) \
- FN(l2_normalization) \
- FN(l2_pool_float_2) \
- FN(l2_pool_float_large) \
- FN(l2_pool_float) \
- FN(local_response_norm_float_1) \
- FN(local_response_norm_float_2) \
- FN(local_response_norm_float_3) \
- FN(local_response_norm_float_4) \
- FN(logistic_float_1) \
- FN(logistic_float_2) \
- FN(logistic_quant8_1) \
- FN(logistic_quant8_2) \
- FN(lsh_projection_2) \
- FN(lsh_projection) \
- FN(lsh_projection_weights_as_inputs) \
- FN(lstm2) \
- FN(lstm2_state2) \
- FN(lstm2_state) \
- FN(lstm3) \
- FN(lstm3_state2) \
- FN(lstm3_state3) \
- FN(lstm3_state) \
- FN(lstm) \
- FN(lstm_state2) \
- FN(lstm_state) \
- FN(max_pool_float_1) \
- FN(max_pool_float_2) \
- FN(max_pool_float_3) \
- FN(max_pool_float_4) \
- FN(max_pool_quant8_1) \
- FN(max_pool_quant8_2) \
- FN(max_pool_quant8_3) \
- FN(max_pool_quant8_4) \
- FN(mobilenet_224_gender_basic_fixed) \
- FN(mobilenet_quantized) \
- FN(mul_broadcast_quant8) \
- FN(mul) \
- FN(mul_quant8) \
- FN(mul_relu) \
- FN(relu1_float_1) \
- FN(relu1_float_2) \
- FN(relu1_quant8_1) \
- FN(relu1_quant8_2) \
- FN(relu6_float_1) \
- FN(relu6_float_2) \
- FN(relu6_quant8_1) \
- FN(relu6_quant8_2) \
- FN(relu_float_1) \
- FN(relu_float_2) \
- FN(relu_quant8_1) \
- FN(relu_quant8_2) \
- FN(reshape) \
- FN(reshape_quant8) \
- FN(reshape_quant8_weights_as_inputs) \
- FN(reshape_weights_as_inputs) \
- FN(resize_bilinear_2) \
- FN(resize_bilinear) \
- FN(rnn) \
- FN(rnn_state) \
- FN(softmax_float_1) \
- FN(softmax_float_2) \
- FN(softmax_quant8_1) \
- FN(softmax_quant8_2) \
- FN(space_to_depth_float_1) \
- FN(space_to_depth_float_2) \
- FN(space_to_depth_float_3) \
- FN(space_to_depth_quant8_1) \
- FN(space_to_depth_quant8_2) \
- FN(svdf2) \
- FN(svdf) \
- FN(svdf_state) \
- FN(tanh)
-
-#define FORWARD_DECLARE_GENERATED_OBJECTS(function) \
- namespace function { \
- extern std::vector<MixedTypedExample> examples; \
- Model createTestModel(); \
- }
-
-FOR_EACH_TEST_MODEL(FORWARD_DECLARE_GENERATED_OBJECTS)
-
-#undef FORWARD_DECLARE_GENERATED_OBJECTS
-
-} // namespace functional
-} // namespace vts
-} // namespace V1_0
-} // namespace neuralnetworks
-} // namespace hardware
-} // namespace android
-
-#endif // VTS_HAL_NEURALNETWORKS_V1_0_VTS_FUNCTIONAL_MODELS_H
diff --git a/neuralnetworks/1.0/vts/functional/ValidationTests.cpp b/neuralnetworks/1.0/vts/functional/ValidationTests.cpp
deleted file mode 100644
index d3cbcff..0000000
--- a/neuralnetworks/1.0/vts/functional/ValidationTests.cpp
+++ /dev/null
@@ -1,50 +0,0 @@
-/*
- * Copyright (C) 2018 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#define LOG_TAG "neuralnetworks_hidl_hal_test"
-
-#include "Models.h"
-#include "VtsHalNeuralnetworks.h"
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_0 {
-namespace vts {
-namespace functional {
-
-// forward declarations
-std::vector<Request> createRequests(const std::vector<::test_helper::MixedTypedExample>& examples);
-
-// generate validation tests
-#define VTS_CURRENT_TEST_CASE(TestName) \
- TEST_F(ValidationTest, TestName) { \
- const Model model = TestName::createTestModel(); \
- const std::vector<Request> requests = createRequests(TestName::examples); \
- validateModel(model); \
- validateRequests(model, requests); \
- }
-
-FOR_EACH_TEST_MODEL(VTS_CURRENT_TEST_CASE)
-
-#undef VTS_CURRENT_TEST_CASE
-
-} // namespace functional
-} // namespace vts
-} // namespace V1_0
-} // namespace neuralnetworks
-} // namespace hardware
-} // namespace android
diff --git a/neuralnetworks/1.1/vts/functional/Android.bp b/neuralnetworks/1.1/vts/functional/Android.bp
index a1c0f1f..07c9b6e 100644
--- a/neuralnetworks/1.1/vts/functional/Android.bp
+++ b/neuralnetworks/1.1/vts/functional/Android.bp
@@ -14,40 +14,21 @@
// limitations under the License.
//
+// Tests for V1_0 models using the V1_1 HAL.
+cc_test {
+ name: "VtsHalNeuralnetworksV1_1CompatV1_0TargetTest",
+ defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
+ srcs: [
+ "GeneratedTestsV1_0.cpp",
+ ],
+}
+
+// Tests for V1_1 models.
cc_test {
name: "VtsHalNeuralnetworksV1_1TargetTest",
+ defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
srcs: [
"BasicTests.cpp",
"GeneratedTests.cpp",
- "ValidateModel.cpp",
- "ValidateRequest.cpp",
- "ValidationTests.cpp",
- "VtsHalNeuralnetworks.cpp",
],
- defaults: ["VtsHalTargetTestDefaults"],
- static_libs: [
- "android.hardware.neuralnetworks@1.0",
- "android.hardware.neuralnetworks@1.1",
- "android.hardware.neuralnetworks@1.2",
- "android.hidl.allocator@1.0",
- "android.hidl.memory@1.0",
- "libgmock",
- "libhidlmemory",
- "libneuralnetworks_utils",
- "VtsHalNeuralnetworksTest_utils",
- ],
- header_libs: [
- "libneuralnetworks_headers",
- "libneuralnetworks_generated_test_harness_headers",
- "libneuralnetworks_generated_tests",
- ],
- // Bug: http://b/74200014 - Disable arm32 asan since it triggers internal
- // error in ld.gold.
- arch: {
- arm: {
- sanitize: {
- never: true,
- },
- },
- },
}
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTests.cpp b/neuralnetworks/1.1/vts/functional/GeneratedTests.cpp
index 1f49904..290a9d3 100644
--- a/neuralnetworks/1.1/vts/functional/GeneratedTests.cpp
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTests.cpp
@@ -45,8 +45,9 @@
using ::android::nn::allocateSharedMemory;
using ::test_helper::MixedTypedExample;
+std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
+
// in frameworks/ml/nn/runtime/tests/generated/
-#include "all_generated_V1_0_vts_tests.cpp"
#include "all_generated_V1_1_vts_tests.cpp"
} // namespace functional
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_0.cpp b/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_0.cpp
new file mode 100644
index 0000000..a36b24c
--- /dev/null
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTestsV1_0.cpp
@@ -0,0 +1,58 @@
+/*
+ * Copyright (C) 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_hidl_hal_test"
+
+#include "VtsHalNeuralnetworks.h"
+
+#include "Callbacks.h"
+#include "TestHarness.h"
+#include "Utils.h"
+
+#include <android-base/logging.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <hidlmemory/mapping.h>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+
+namespace generated_tests {
+using ::test_helper::MixedTypedExample;
+extern void Execute(const sp<V1_1::IDevice>&, std::function<V1_1::Model(void)>,
+ std::function<bool(int)>, const std::vector<MixedTypedExample>&);
+} // namespace generated_tests
+
+namespace V1_1 {
+namespace vts {
+namespace functional {
+
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
+using ::android::nn::allocateSharedMemory;
+using ::test_helper::MixedTypedExample;
+
+std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
+
+// in frameworks/ml/nn/runtime/tests/generated/
+#include "all_generated_V1_0_vts_tests.cpp"
+
+} // namespace functional
+} // namespace vts
+} // namespace V1_1
+} // namespace neuralnetworks
+} // namespace hardware
+} // namespace android
diff --git a/neuralnetworks/1.1/vts/functional/Models.h b/neuralnetworks/1.1/vts/functional/Models.h
deleted file mode 100644
index 62bc95e..0000000
--- a/neuralnetworks/1.1/vts/functional/Models.h
+++ /dev/null
@@ -1,377 +0,0 @@
-/*
- * Copyright (C) 2018 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VTS_HAL_NEURALNETWORKS_V1_1_VTS_FUNCTIONAL_MODELS_H
-#define VTS_HAL_NEURALNETWORKS_V1_1_VTS_FUNCTIONAL_MODELS_H
-
-#define LOG_TAG "neuralnetworks_hidl_hal_test"
-
-#include "TestHarness.h"
-
-#include <android/hardware/neuralnetworks/1.0/types.h>
-#include <android/hardware/neuralnetworks/1.1/types.h>
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_1 {
-namespace vts {
-namespace functional {
-
-using MixedTypedExample = test_helper::MixedTypedExample;
-
-#define FOR_EACH_TEST_MODEL(FN) \
- FN(add) \
- FN(add_broadcast_quant8) \
- FN(add_quant8) \
- FN(add_relaxed) \
- FN(avg_pool_float_1) \
- FN(avg_pool_float_1_relaxed) \
- FN(avg_pool_float_2) \
- FN(avg_pool_float_2_relaxed) \
- FN(avg_pool_float_3) \
- FN(avg_pool_float_3_relaxed) \
- FN(avg_pool_float_4) \
- FN(avg_pool_float_4_relaxed) \
- FN(avg_pool_float_5) \
- FN(avg_pool_float_5_relaxed) \
- FN(avg_pool_quant8_1) \
- FN(avg_pool_quant8_2) \
- FN(avg_pool_quant8_3) \
- FN(avg_pool_quant8_4) \
- FN(avg_pool_quant8_5) \
- FN(batch_to_space) \
- FN(batch_to_space_float_1) \
- FN(batch_to_space_float_1_relaxed) \
- FN(batch_to_space_quant8_1) \
- FN(batch_to_space_relaxed) \
- FN(concat_float_1) \
- FN(concat_float_1_relaxed) \
- FN(concat_float_2) \
- FN(concat_float_2_relaxed) \
- FN(concat_float_3) \
- FN(concat_float_3_relaxed) \
- FN(concat_quant8_1) \
- FN(concat_quant8_2) \
- FN(concat_quant8_3) \
- FN(conv_1_h3_w2_SAME) \
- FN(conv_1_h3_w2_SAME_relaxed) \
- FN(conv_1_h3_w2_VALID) \
- FN(conv_1_h3_w2_VALID_relaxed) \
- FN(conv_3_h3_w2_SAME) \
- FN(conv_3_h3_w2_SAME_relaxed) \
- FN(conv_3_h3_w2_VALID) \
- FN(conv_3_h3_w2_VALID_relaxed) \
- FN(conv_float) \
- FN(conv_float_2) \
- FN(conv_float_2_relaxed) \
- FN(conv_float_channels) \
- FN(conv_float_channels_relaxed) \
- FN(conv_float_channels_weights_as_inputs) \
- FN(conv_float_channels_weights_as_inputs_relaxed) \
- FN(conv_float_large) \
- FN(conv_float_large_relaxed) \
- FN(conv_float_large_weights_as_inputs) \
- FN(conv_float_large_weights_as_inputs_relaxed) \
- FN(conv_float_relaxed) \
- FN(conv_float_weights_as_inputs) \
- FN(conv_float_weights_as_inputs_relaxed) \
- FN(conv_quant8) \
- FN(conv_quant8_2) \
- FN(conv_quant8_channels) \
- FN(conv_quant8_channels_weights_as_inputs) \
- FN(conv_quant8_large) \
- FN(conv_quant8_large_weights_as_inputs) \
- FN(conv_quant8_overflow) \
- FN(conv_quant8_overflow_weights_as_inputs) \
- FN(conv_quant8_weights_as_inputs) \
- FN(depth_to_space_float_1) \
- FN(depth_to_space_float_1_relaxed) \
- FN(depth_to_space_float_2) \
- FN(depth_to_space_float_2_relaxed) \
- FN(depth_to_space_float_3) \
- FN(depth_to_space_float_3_relaxed) \
- FN(depth_to_space_quant8_1) \
- FN(depth_to_space_quant8_2) \
- FN(depthwise_conv) \
- FN(depthwise_conv2d_float) \
- FN(depthwise_conv2d_float_2) \
- FN(depthwise_conv2d_float_2_relaxed) \
- FN(depthwise_conv2d_float_large) \
- FN(depthwise_conv2d_float_large_2) \
- FN(depthwise_conv2d_float_large_2_relaxed) \
- FN(depthwise_conv2d_float_large_2_weights_as_inputs) \
- FN(depthwise_conv2d_float_large_2_weights_as_inputs_relaxed) \
- FN(depthwise_conv2d_float_large_relaxed) \
- FN(depthwise_conv2d_float_large_weights_as_inputs) \
- FN(depthwise_conv2d_float_large_weights_as_inputs_relaxed) \
- FN(depthwise_conv2d_float_relaxed) \
- FN(depthwise_conv2d_float_weights_as_inputs) \
- FN(depthwise_conv2d_float_weights_as_inputs_relaxed) \
- FN(depthwise_conv2d_quant8) \
- FN(depthwise_conv2d_quant8_2) \
- FN(depthwise_conv2d_quant8_large) \
- FN(depthwise_conv2d_quant8_large_weights_as_inputs) \
- FN(depthwise_conv2d_quant8_weights_as_inputs) \
- FN(depthwise_conv_relaxed) \
- FN(dequantize) \
- FN(dequantize_relaxed) \
- FN(div) \
- FN(div_broadcast_float) \
- FN(div_broadcast_float_relaxed) \
- FN(div_relaxed) \
- FN(embedding_lookup) \
- FN(embedding_lookup_relaxed) \
- FN(floor) \
- FN(floor_relaxed) \
- FN(fully_connected_float) \
- FN(fully_connected_float_2) \
- FN(fully_connected_float_2_relaxed) \
- FN(fully_connected_float_4d_simple) \
- FN(fully_connected_float_4d_simple_relaxed) \
- FN(fully_connected_float_large) \
- FN(fully_connected_float_large_relaxed) \
- FN(fully_connected_float_large_weights_as_inputs) \
- FN(fully_connected_float_large_weights_as_inputs_relaxed) \
- FN(fully_connected_float_relaxed) \
- FN(fully_connected_float_weights_as_inputs) \
- FN(fully_connected_float_weights_as_inputs_relaxed) \
- FN(fully_connected_quant8) \
- FN(fully_connected_quant8_2) \
- FN(fully_connected_quant8_large) \
- FN(fully_connected_quant8_large_weights_as_inputs) \
- FN(fully_connected_quant8_weights_as_inputs) \
- FN(hashtable_lookup_float) \
- FN(hashtable_lookup_float_relaxed) \
- FN(hashtable_lookup_quant8) \
- FN(l2_normalization) \
- FN(l2_normalization_2) \
- FN(l2_normalization_2_relaxed) \
- FN(l2_normalization_large) \
- FN(l2_normalization_large_relaxed) \
- FN(l2_normalization_relaxed) \
- FN(l2_pool_float) \
- FN(l2_pool_float_2) \
- FN(l2_pool_float_2_relaxed) \
- FN(l2_pool_float_large) \
- FN(l2_pool_float_large_relaxed) \
- FN(l2_pool_float_relaxed) \
- FN(local_response_norm_float_1) \
- FN(local_response_norm_float_1_relaxed) \
- FN(local_response_norm_float_2) \
- FN(local_response_norm_float_2_relaxed) \
- FN(local_response_norm_float_3) \
- FN(local_response_norm_float_3_relaxed) \
- FN(local_response_norm_float_4) \
- FN(local_response_norm_float_4_relaxed) \
- FN(logistic_float_1) \
- FN(logistic_float_1_relaxed) \
- FN(logistic_float_2) \
- FN(logistic_float_2_relaxed) \
- FN(logistic_quant8_1) \
- FN(logistic_quant8_2) \
- FN(lsh_projection) \
- FN(lsh_projection_2) \
- FN(lsh_projection_2_relaxed) \
- FN(lsh_projection_relaxed) \
- FN(lsh_projection_weights_as_inputs) \
- FN(lsh_projection_weights_as_inputs_relaxed) \
- FN(lstm) \
- FN(lstm2) \
- FN(lstm2_relaxed) \
- FN(lstm2_state) \
- FN(lstm2_state2) \
- FN(lstm2_state2_relaxed) \
- FN(lstm2_state_relaxed) \
- FN(lstm3) \
- FN(lstm3_relaxed) \
- FN(lstm3_state) \
- FN(lstm3_state2) \
- FN(lstm3_state2_relaxed) \
- FN(lstm3_state3) \
- FN(lstm3_state3_relaxed) \
- FN(lstm3_state_relaxed) \
- FN(lstm_relaxed) \
- FN(lstm_state) \
- FN(lstm_state2) \
- FN(lstm_state2_relaxed) \
- FN(lstm_state_relaxed) \
- FN(max_pool_float_1) \
- FN(max_pool_float_1_relaxed) \
- FN(max_pool_float_2) \
- FN(max_pool_float_2_relaxed) \
- FN(max_pool_float_3) \
- FN(max_pool_float_3_relaxed) \
- FN(max_pool_float_4) \
- FN(max_pool_float_4_relaxed) \
- FN(max_pool_quant8_1) \
- FN(max_pool_quant8_2) \
- FN(max_pool_quant8_3) \
- FN(max_pool_quant8_4) \
- FN(mean) \
- FN(mean_float_1) \
- FN(mean_float_1_relaxed) \
- FN(mean_float_2) \
- FN(mean_float_2_relaxed) \
- FN(mean_quant8_1) \
- FN(mean_quant8_2) \
- FN(mean_relaxed) \
- FN(mobilenet_224_gender_basic_fixed) \
- FN(mobilenet_224_gender_basic_fixed_relaxed) \
- FN(mobilenet_quantized) \
- FN(mul) \
- FN(mul_broadcast_quant8) \
- FN(mul_quant8) \
- FN(mul_relaxed) \
- FN(mul_relu) \
- FN(mul_relu_relaxed) \
- FN(pad) \
- FN(pad_float_1) \
- FN(pad_float_1_relaxed) \
- FN(pad_relaxed) \
- FN(relu1_float_1) \
- FN(relu1_float_1_relaxed) \
- FN(relu1_float_2) \
- FN(relu1_float_2_relaxed) \
- FN(relu1_quant8_1) \
- FN(relu1_quant8_2) \
- FN(relu6_float_1) \
- FN(relu6_float_1_relaxed) \
- FN(relu6_float_2) \
- FN(relu6_float_2_relaxed) \
- FN(relu6_quant8_1) \
- FN(relu6_quant8_2) \
- FN(relu_float_1) \
- FN(relu_float_1_relaxed) \
- FN(relu_float_2) \
- FN(relu_float_2_relaxed) \
- FN(relu_quant8_1) \
- FN(relu_quant8_2) \
- FN(reshape) \
- FN(reshape_quant8) \
- FN(reshape_quant8_weights_as_inputs) \
- FN(reshape_relaxed) \
- FN(reshape_weights_as_inputs) \
- FN(reshape_weights_as_inputs_relaxed) \
- FN(resize_bilinear) \
- FN(resize_bilinear_2) \
- FN(resize_bilinear_2_relaxed) \
- FN(resize_bilinear_relaxed) \
- FN(rnn) \
- FN(rnn_relaxed) \
- FN(rnn_state) \
- FN(rnn_state_relaxed) \
- FN(softmax_float_1) \
- FN(softmax_float_1_relaxed) \
- FN(softmax_float_2) \
- FN(softmax_float_2_relaxed) \
- FN(softmax_quant8_1) \
- FN(softmax_quant8_2) \
- FN(space_to_batch) \
- FN(space_to_batch_float_1) \
- FN(space_to_batch_float_1_relaxed) \
- FN(space_to_batch_float_2) \
- FN(space_to_batch_float_2_relaxed) \
- FN(space_to_batch_float_3) \
- FN(space_to_batch_float_3_relaxed) \
- FN(space_to_batch_quant8_1) \
- FN(space_to_batch_quant8_2) \
- FN(space_to_batch_quant8_3) \
- FN(space_to_batch_relaxed) \
- FN(space_to_depth_float_1) \
- FN(space_to_depth_float_1_relaxed) \
- FN(space_to_depth_float_2) \
- FN(space_to_depth_float_2_relaxed) \
- FN(space_to_depth_float_3) \
- FN(space_to_depth_float_3_relaxed) \
- FN(space_to_depth_quant8_1) \
- FN(space_to_depth_quant8_2) \
- FN(squeeze) \
- FN(squeeze_float_1) \
- FN(squeeze_float_1_relaxed) \
- FN(squeeze_quant8_1) \
- FN(squeeze_relaxed) \
- FN(strided_slice) \
- FN(strided_slice_float_1) \
- FN(strided_slice_float_10) \
- FN(strided_slice_float_10_relaxed) \
- FN(strided_slice_float_11) \
- FN(strided_slice_float_11_relaxed) \
- FN(strided_slice_float_1_relaxed) \
- FN(strided_slice_float_2) \
- FN(strided_slice_float_2_relaxed) \
- FN(strided_slice_float_3) \
- FN(strided_slice_float_3_relaxed) \
- FN(strided_slice_float_4) \
- FN(strided_slice_float_4_relaxed) \
- FN(strided_slice_float_5) \
- FN(strided_slice_float_5_relaxed) \
- FN(strided_slice_float_6) \
- FN(strided_slice_float_6_relaxed) \
- FN(strided_slice_float_7) \
- FN(strided_slice_float_7_relaxed) \
- FN(strided_slice_float_8) \
- FN(strided_slice_float_8_relaxed) \
- FN(strided_slice_float_9) \
- FN(strided_slice_float_9_relaxed) \
- FN(strided_slice_qaunt8_10) \
- FN(strided_slice_qaunt8_11) \
- FN(strided_slice_quant8_1) \
- FN(strided_slice_quant8_2) \
- FN(strided_slice_quant8_3) \
- FN(strided_slice_quant8_4) \
- FN(strided_slice_quant8_5) \
- FN(strided_slice_quant8_6) \
- FN(strided_slice_quant8_7) \
- FN(strided_slice_quant8_8) \
- FN(strided_slice_quant8_9) \
- FN(strided_slice_relaxed) \
- FN(sub) \
- FN(sub_broadcast_float) \
- FN(sub_broadcast_float_relaxed) \
- FN(sub_relaxed) \
- FN(svdf) \
- FN(svdf2) \
- FN(svdf2_relaxed) \
- FN(svdf_relaxed) \
- FN(svdf_state) \
- FN(svdf_state_relaxed) \
- FN(tanh) \
- FN(tanh_relaxed) \
- FN(transpose) \
- FN(transpose_float_1) \
- FN(transpose_float_1_relaxed) \
- FN(transpose_quant8_1) \
- FN(transpose_relaxed)
-
-#define FORWARD_DECLARE_GENERATED_OBJECTS(function) \
- namespace function { \
- extern std::vector<MixedTypedExample> examples; \
- Model createTestModel(); \
- }
-
-FOR_EACH_TEST_MODEL(FORWARD_DECLARE_GENERATED_OBJECTS)
-
-#undef FORWARD_DECLARE_GENERATED_OBJECTS
-
-} // namespace functional
-} // namespace vts
-} // namespace V1_1
-} // namespace neuralnetworks
-} // namespace hardware
-} // namespace android
-
-#endif // VTS_HAL_NEURALNETWORKS_V1_1_VTS_FUNCTIONAL_MODELS_H
diff --git a/neuralnetworks/1.1/vts/functional/ValidationTests.cpp b/neuralnetworks/1.1/vts/functional/ValidationTests.cpp
deleted file mode 100644
index 1c35ba8..0000000
--- a/neuralnetworks/1.1/vts/functional/ValidationTests.cpp
+++ /dev/null
@@ -1,50 +0,0 @@
-/*
- * Copyright (C) 2018 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#define LOG_TAG "neuralnetworks_hidl_hal_test"
-
-#include "Models.h"
-#include "VtsHalNeuralnetworks.h"
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_1 {
-namespace vts {
-namespace functional {
-
-// forward declarations
-std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
-
-// generate validation tests
-#define VTS_CURRENT_TEST_CASE(TestName) \
- TEST_F(ValidationTest, TestName) { \
- const Model model = TestName::createTestModel(); \
- const std::vector<Request> requests = createRequests(TestName::examples); \
- validateModel(model); \
- validateRequests(model, requests); \
- }
-
-FOR_EACH_TEST_MODEL(VTS_CURRENT_TEST_CASE)
-
-#undef VTS_CURRENT_TEST_CASE
-
-} // namespace functional
-} // namespace vts
-} // namespace V1_1
-} // namespace neuralnetworks
-} // namespace hardware
-} // namespace android
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 366e626..fe9b312 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -33,15 +33,13 @@
/**
* A tensor of 16 bit signed integers that represent real numbers.
*
- * Attached to this tensor are two numbers that are used to convert the 16
- * bit integer to the real value and vice versa. These two numbers are:
- * - scale: a 32 bit floating point value greater than zero.
- * - zeroPoint: a 32 bit integer, in range [-32768, 32767].
+ * Attached to this tensor is a number representing real value scale that is
+ * used to convert the 16 bit number to a real value in the following way:
+ * realValue = integerValue * scale.
*
- * The formula is:
- * realValue = (integerValue - zeroPoint) * scale.
+ * scale is a 32 bit floating point with value greater then zero.
*/
- TENSOR_QUANT16_ASYMM = 7,
+ TENSOR_QUANT16_SYMM = 7,
/** A tensor of 16 bit floating point values. */
TENSOR_FLOAT16 = 8,
};
diff --git a/neuralnetworks/1.2/vts/functional/Android.bp b/neuralnetworks/1.2/vts/functional/Android.bp
index 09d0dc3..085d5db 100644
--- a/neuralnetworks/1.2/vts/functional/Android.bp
+++ b/neuralnetworks/1.2/vts/functional/Android.bp
@@ -14,40 +14,30 @@
// limitations under the License.
//
+// Tests for V1_0 models using the V1_2 HAL.
+cc_test {
+ name: "VtsHalNeuralnetworksV1_2CompatV1_0TargetTest",
+ defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
+ srcs: [
+ "GeneratedTestsV1_0.cpp",
+ ]
+}
+
+// Tests for V1_1 models using the V1_2 HAL.
+cc_test {
+ name: "VtsHalNeuralnetworksV1_2CompatV1_1TargetTest",
+ defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
+ srcs: [
+ "GeneratedTestsV1_1.cpp",
+ ],
+}
+
+// Tests for V1_2 models.
cc_test {
name: "VtsHalNeuralnetworksV1_2TargetTest",
+ defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
srcs: [
"BasicTests.cpp",
"GeneratedTests.cpp",
- "ValidateModel.cpp",
- "ValidateRequest.cpp",
- "ValidationTests.cpp",
- "VtsHalNeuralnetworks.cpp",
],
- defaults: ["VtsHalTargetTestDefaults"],
- static_libs: [
- "android.hardware.neuralnetworks@1.0",
- "android.hardware.neuralnetworks@1.1",
- "android.hardware.neuralnetworks@1.2",
- "android.hidl.allocator@1.0",
- "android.hidl.memory@1.0",
- "libgmock",
- "libhidlmemory",
- "libneuralnetworks_utils",
- "VtsHalNeuralnetworksTest_utils",
- ],
- header_libs: [
- "libneuralnetworks_headers",
- "libneuralnetworks_generated_test_harness_headers",
- "libneuralnetworks_generated_tests",
- ],
- // Bug: http://b/74200014 - Disable arm32 asan since it triggers internal
- // error in ld.gold.
- arch: {
- arm: {
- sanitize: {
- never: true,
- },
- },
- },
}
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
index e87fa6b..79d5a60 100644
--- a/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
@@ -45,9 +45,9 @@
using ::android::nn::allocateSharedMemory;
using ::test_helper::MixedTypedExample;
+std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
+
// in frameworks/ml/nn/runtime/tests/generated/
-#include "all_generated_V1_0_vts_tests.cpp"
-#include "all_generated_V1_1_vts_tests.cpp"
#include "all_generated_V1_2_vts_tests.cpp"
} // namespace functional
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_0.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_0.cpp
new file mode 100644
index 0000000..42e22b0
--- /dev/null
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_0.cpp
@@ -0,0 +1,58 @@
+/*
+ * Copyright (C) 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_hidl_hal_test"
+
+#include "VtsHalNeuralnetworks.h"
+
+#include "Callbacks.h"
+#include "TestHarness.h"
+#include "Utils.h"
+
+#include <android-base/logging.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <hidlmemory/mapping.h>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+
+namespace generated_tests {
+using ::test_helper::MixedTypedExample;
+extern void Execute(const sp<V1_2::IDevice>&, std::function<V1_2::Model(void)>,
+ std::function<bool(int)>, const std::vector<MixedTypedExample>&);
+} // namespace generated_tests
+
+namespace V1_2 {
+namespace vts {
+namespace functional {
+
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
+using ::android::nn::allocateSharedMemory;
+using ::test_helper::MixedTypedExample;
+
+std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
+
+// in frameworks/ml/nn/runtime/tests/generated/
+#include "all_generated_V1_0_vts_tests.cpp"
+
+} // namespace functional
+} // namespace vts
+} // namespace V1_2
+} // namespace neuralnetworks
+} // namespace hardware
+} // namespace android
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_1.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_1.cpp
new file mode 100644
index 0000000..aab5cb6
--- /dev/null
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_1.cpp
@@ -0,0 +1,58 @@
+/*
+ * Copyright (C) 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_hidl_hal_test"
+
+#include "VtsHalNeuralnetworks.h"
+
+#include "Callbacks.h"
+#include "TestHarness.h"
+#include "Utils.h"
+
+#include <android-base/logging.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <hidlmemory/mapping.h>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+
+namespace generated_tests {
+using ::test_helper::MixedTypedExample;
+extern void Execute(const sp<V1_2::IDevice>&, std::function<V1_2::Model(void)>,
+ std::function<bool(int)>, const std::vector<MixedTypedExample>&);
+} // namespace generated_tests
+
+namespace V1_2 {
+namespace vts {
+namespace functional {
+
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
+using ::android::nn::allocateSharedMemory;
+using ::test_helper::MixedTypedExample;
+
+std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
+
+// in frameworks/ml/nn/runtime/tests/generated/
+#include "all_generated_V1_1_vts_tests.cpp"
+
+} // namespace functional
+} // namespace vts
+} // namespace V1_2
+} // namespace neuralnetworks
+} // namespace hardware
+} // namespace android
diff --git a/neuralnetworks/1.2/vts/functional/Models.h b/neuralnetworks/1.2/vts/functional/Models.h
deleted file mode 100644
index 2d512fe..0000000
--- a/neuralnetworks/1.2/vts/functional/Models.h
+++ /dev/null
@@ -1,379 +0,0 @@
-/*
- * Copyright (C) 2018 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VTS_HAL_NEURALNETWORKS_V1_2_VTS_FUNCTIONAL_MODELS_H
-#define VTS_HAL_NEURALNETWORKS_V1_2_VTS_FUNCTIONAL_MODELS_H
-
-#define LOG_TAG "neuralnetworks_hidl_hal_test"
-
-#include "TestHarness.h"
-
-#include <android/hardware/neuralnetworks/1.0/types.h>
-#include <android/hardware/neuralnetworks/1.1/types.h>
-#include <android/hardware/neuralnetworks/1.2/types.h>
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_2 {
-namespace vts {
-namespace functional {
-
-using MixedTypedExample = test_helper::MixedTypedExample;
-
-#define FOR_EACH_TEST_MODEL(FN) \
- FN(add) \
- FN(add_broadcast_quant8) \
- FN(add_quant8) \
- FN(add_relaxed) \
- FN(avg_pool_float_1) \
- FN(avg_pool_float_1_relaxed) \
- FN(avg_pool_float_2) \
- FN(avg_pool_float_2_relaxed) \
- FN(avg_pool_float_3) \
- FN(avg_pool_float_3_relaxed) \
- FN(avg_pool_float_4) \
- FN(avg_pool_float_4_relaxed) \
- FN(avg_pool_float_5) \
- FN(avg_pool_float_5_relaxed) \
- FN(avg_pool_quant8_1) \
- FN(avg_pool_quant8_2) \
- FN(avg_pool_quant8_3) \
- FN(avg_pool_quant8_4) \
- FN(avg_pool_quant8_5) \
- FN(batch_to_space) \
- FN(batch_to_space_float_1) \
- FN(batch_to_space_float_1_relaxed) \
- FN(batch_to_space_quant8_1) \
- FN(batch_to_space_relaxed) \
- FN(concat_float_1) \
- FN(concat_float_1_relaxed) \
- FN(concat_float_2) \
- FN(concat_float_2_relaxed) \
- FN(concat_float_3) \
- FN(concat_float_3_relaxed) \
- FN(concat_quant8_1) \
- FN(concat_quant8_2) \
- FN(concat_quant8_3) \
- FN(conv_1_h3_w2_SAME) \
- FN(conv_1_h3_w2_SAME_relaxed) \
- FN(conv_1_h3_w2_VALID) \
- FN(conv_1_h3_w2_VALID_relaxed) \
- FN(conv_3_h3_w2_SAME) \
- FN(conv_3_h3_w2_SAME_relaxed) \
- FN(conv_3_h3_w2_VALID) \
- FN(conv_3_h3_w2_VALID_relaxed) \
- FN(conv_float) \
- FN(conv_float_2) \
- FN(conv_float_2_relaxed) \
- FN(conv_float_channels) \
- FN(conv_float_channels_relaxed) \
- FN(conv_float_channels_weights_as_inputs) \
- FN(conv_float_channels_weights_as_inputs_relaxed) \
- FN(conv_float_large) \
- FN(conv_float_large_relaxed) \
- FN(conv_float_large_weights_as_inputs) \
- FN(conv_float_large_weights_as_inputs_relaxed) \
- FN(conv_float_relaxed) \
- FN(conv_float_weights_as_inputs) \
- FN(conv_float_weights_as_inputs_relaxed) \
- FN(conv_quant8) \
- FN(conv_quant8_2) \
- FN(conv_quant8_channels) \
- FN(conv_quant8_channels_weights_as_inputs) \
- FN(conv_quant8_large) \
- FN(conv_quant8_large_weights_as_inputs) \
- FN(conv_quant8_overflow) \
- FN(conv_quant8_overflow_weights_as_inputs) \
- FN(conv_quant8_weights_as_inputs) \
- FN(depth_to_space_float_1) \
- FN(depth_to_space_float_1_relaxed) \
- FN(depth_to_space_float_2) \
- FN(depth_to_space_float_2_relaxed) \
- FN(depth_to_space_float_3) \
- FN(depth_to_space_float_3_relaxed) \
- FN(depth_to_space_quant8_1) \
- FN(depth_to_space_quant8_2) \
- FN(depthwise_conv) \
- FN(depthwise_conv2d_float) \
- FN(depthwise_conv2d_float_2) \
- FN(depthwise_conv2d_float_2_relaxed) \
- FN(depthwise_conv2d_float_large) \
- FN(depthwise_conv2d_float_large_2) \
- FN(depthwise_conv2d_float_large_2_relaxed) \
- FN(depthwise_conv2d_float_large_2_weights_as_inputs) \
- FN(depthwise_conv2d_float_large_2_weights_as_inputs_relaxed) \
- FN(depthwise_conv2d_float_large_relaxed) \
- FN(depthwise_conv2d_float_large_weights_as_inputs) \
- FN(depthwise_conv2d_float_large_weights_as_inputs_relaxed) \
- FN(depthwise_conv2d_float_relaxed) \
- FN(depthwise_conv2d_float_weights_as_inputs) \
- FN(depthwise_conv2d_float_weights_as_inputs_relaxed) \
- FN(depthwise_conv2d_quant8) \
- FN(depthwise_conv2d_quant8_2) \
- FN(depthwise_conv2d_quant8_large) \
- FN(depthwise_conv2d_quant8_large_weights_as_inputs) \
- FN(depthwise_conv2d_quant8_weights_as_inputs) \
- FN(depthwise_conv_relaxed) \
- FN(dequantize) \
- FN(dequantize_relaxed) \
- FN(div) \
- FN(div_broadcast_float) \
- FN(div_broadcast_float_relaxed) \
- FN(div_relaxed) \
- FN(embedding_lookup) \
- FN(embedding_lookup_relaxed) \
- FN(floor) \
- FN(floor_relaxed) \
- FN(fully_connected_float) \
- FN(fully_connected_float_2) \
- FN(fully_connected_float_2_relaxed) \
- FN(fully_connected_float_4d_simple) \
- FN(fully_connected_float_4d_simple_relaxed) \
- FN(fully_connected_float_large) \
- FN(fully_connected_float_large_relaxed) \
- FN(fully_connected_float_large_weights_as_inputs) \
- FN(fully_connected_float_large_weights_as_inputs_relaxed) \
- FN(fully_connected_float_relaxed) \
- FN(fully_connected_float_weights_as_inputs) \
- FN(fully_connected_float_weights_as_inputs_relaxed) \
- FN(fully_connected_quant8) \
- FN(fully_connected_quant8_2) \
- FN(fully_connected_quant8_large) \
- FN(fully_connected_quant8_large_weights_as_inputs) \
- FN(fully_connected_quant8_weights_as_inputs) \
- FN(hashtable_lookup_float) \
- FN(hashtable_lookup_float_relaxed) \
- FN(hashtable_lookup_quant8) \
- FN(l2_normalization) \
- FN(l2_normalization_2) \
- FN(l2_normalization_2_relaxed) \
- FN(l2_normalization_large) \
- FN(l2_normalization_large_relaxed) \
- FN(l2_normalization_relaxed) \
- FN(l2_pool_float) \
- FN(l2_pool_float_2) \
- FN(l2_pool_float_2_relaxed) \
- FN(l2_pool_float_large) \
- FN(l2_pool_float_large_relaxed) \
- FN(l2_pool_float_relaxed) \
- FN(local_response_norm_float_1) \
- FN(local_response_norm_float_1_relaxed) \
- FN(local_response_norm_float_2) \
- FN(local_response_norm_float_2_relaxed) \
- FN(local_response_norm_float_3) \
- FN(local_response_norm_float_3_relaxed) \
- FN(local_response_norm_float_4) \
- FN(local_response_norm_float_4_relaxed) \
- FN(logistic_float_1) \
- FN(logistic_float_1_relaxed) \
- FN(logistic_float_2) \
- FN(logistic_float_2_relaxed) \
- FN(logistic_quant8_1) \
- FN(logistic_quant8_2) \
- FN(lsh_projection) \
- FN(lsh_projection_2) \
- FN(lsh_projection_2_relaxed) \
- FN(lsh_projection_relaxed) \
- FN(lsh_projection_weights_as_inputs) \
- FN(lsh_projection_weights_as_inputs_relaxed) \
- FN(lstm) \
- FN(lstm2) \
- FN(lstm2_relaxed) \
- FN(lstm2_state) \
- FN(lstm2_state2) \
- FN(lstm2_state2_relaxed) \
- FN(lstm2_state_relaxed) \
- FN(lstm3) \
- FN(lstm3_relaxed) \
- FN(lstm3_state) \
- FN(lstm3_state2) \
- FN(lstm3_state2_relaxed) \
- FN(lstm3_state3) \
- FN(lstm3_state3_relaxed) \
- FN(lstm3_state_relaxed) \
- FN(lstm_relaxed) \
- FN(lstm_state) \
- FN(lstm_state2) \
- FN(lstm_state2_relaxed) \
- FN(lstm_state_relaxed) \
- FN(max_pool_float_1) \
- FN(max_pool_float_1_relaxed) \
- FN(max_pool_float_2) \
- FN(max_pool_float_2_relaxed) \
- FN(max_pool_float_3) \
- FN(max_pool_float_3_relaxed) \
- FN(max_pool_float_4) \
- FN(max_pool_float_4_relaxed) \
- FN(max_pool_quant8_1) \
- FN(max_pool_quant8_2) \
- FN(max_pool_quant8_3) \
- FN(max_pool_quant8_4) \
- FN(mean) \
- FN(mean_float_1) \
- FN(mean_float_1_relaxed) \
- FN(mean_float_2) \
- FN(mean_float_2_relaxed) \
- FN(mean_quant8_1) \
- FN(mean_quant8_2) \
- FN(mean_relaxed) \
- FN(mobilenet_224_gender_basic_fixed) \
- FN(mobilenet_224_gender_basic_fixed_relaxed) \
- FN(mobilenet_quantized) \
- FN(mul) \
- FN(mul_broadcast_quant8) \
- FN(mul_quant8) \
- FN(mul_relaxed) \
- FN(mul_relu) \
- FN(mul_relu_relaxed) \
- FN(pad) \
- FN(pad_float_1) \
- FN(pad_float_1_relaxed) \
- FN(pad_relaxed) \
- FN(random_multinomial) \
- FN(relu1_float_1) \
- FN(relu1_float_1_relaxed) \
- FN(relu1_float_2) \
- FN(relu1_float_2_relaxed) \
- FN(relu1_quant8_1) \
- FN(relu1_quant8_2) \
- FN(relu6_float_1) \
- FN(relu6_float_1_relaxed) \
- FN(relu6_float_2) \
- FN(relu6_float_2_relaxed) \
- FN(relu6_quant8_1) \
- FN(relu6_quant8_2) \
- FN(relu_float_1) \
- FN(relu_float_1_relaxed) \
- FN(relu_float_2) \
- FN(relu_float_2_relaxed) \
- FN(relu_quant8_1) \
- FN(relu_quant8_2) \
- FN(reshape) \
- FN(reshape_quant8) \
- FN(reshape_quant8_weights_as_inputs) \
- FN(reshape_relaxed) \
- FN(reshape_weights_as_inputs) \
- FN(reshape_weights_as_inputs_relaxed) \
- FN(resize_bilinear) \
- FN(resize_bilinear_2) \
- FN(resize_bilinear_2_relaxed) \
- FN(resize_bilinear_relaxed) \
- FN(rnn) \
- FN(rnn_relaxed) \
- FN(rnn_state) \
- FN(rnn_state_relaxed) \
- FN(softmax_float_1) \
- FN(softmax_float_1_relaxed) \
- FN(softmax_float_2) \
- FN(softmax_float_2_relaxed) \
- FN(softmax_quant8_1) \
- FN(softmax_quant8_2) \
- FN(space_to_batch) \
- FN(space_to_batch_float_1) \
- FN(space_to_batch_float_1_relaxed) \
- FN(space_to_batch_float_2) \
- FN(space_to_batch_float_2_relaxed) \
- FN(space_to_batch_float_3) \
- FN(space_to_batch_float_3_relaxed) \
- FN(space_to_batch_quant8_1) \
- FN(space_to_batch_quant8_2) \
- FN(space_to_batch_quant8_3) \
- FN(space_to_batch_relaxed) \
- FN(space_to_depth_float_1) \
- FN(space_to_depth_float_1_relaxed) \
- FN(space_to_depth_float_2) \
- FN(space_to_depth_float_2_relaxed) \
- FN(space_to_depth_float_3) \
- FN(space_to_depth_float_3_relaxed) \
- FN(space_to_depth_quant8_1) \
- FN(space_to_depth_quant8_2) \
- FN(squeeze) \
- FN(squeeze_float_1) \
- FN(squeeze_float_1_relaxed) \
- FN(squeeze_quant8_1) \
- FN(squeeze_relaxed) \
- FN(strided_slice) \
- FN(strided_slice_float_1) \
- FN(strided_slice_float_10) \
- FN(strided_slice_float_10_relaxed) \
- FN(strided_slice_float_11) \
- FN(strided_slice_float_11_relaxed) \
- FN(strided_slice_float_1_relaxed) \
- FN(strided_slice_float_2) \
- FN(strided_slice_float_2_relaxed) \
- FN(strided_slice_float_3) \
- FN(strided_slice_float_3_relaxed) \
- FN(strided_slice_float_4) \
- FN(strided_slice_float_4_relaxed) \
- FN(strided_slice_float_5) \
- FN(strided_slice_float_5_relaxed) \
- FN(strided_slice_float_6) \
- FN(strided_slice_float_6_relaxed) \
- FN(strided_slice_float_7) \
- FN(strided_slice_float_7_relaxed) \
- FN(strided_slice_float_8) \
- FN(strided_slice_float_8_relaxed) \
- FN(strided_slice_float_9) \
- FN(strided_slice_float_9_relaxed) \
- FN(strided_slice_qaunt8_10) \
- FN(strided_slice_qaunt8_11) \
- FN(strided_slice_quant8_1) \
- FN(strided_slice_quant8_2) \
- FN(strided_slice_quant8_3) \
- FN(strided_slice_quant8_4) \
- FN(strided_slice_quant8_5) \
- FN(strided_slice_quant8_6) \
- FN(strided_slice_quant8_7) \
- FN(strided_slice_quant8_8) \
- FN(strided_slice_quant8_9) \
- FN(strided_slice_relaxed) \
- FN(sub) \
- FN(sub_broadcast_float) \
- FN(sub_broadcast_float_relaxed) \
- FN(sub_relaxed) \
- FN(svdf) \
- FN(svdf2) \
- FN(svdf2_relaxed) \
- FN(svdf_relaxed) \
- FN(svdf_state) \
- FN(svdf_state_relaxed) \
- FN(tanh) \
- FN(tanh_relaxed) \
- FN(transpose) \
- FN(transpose_float_1) \
- FN(transpose_float_1_relaxed) \
- FN(transpose_quant8_1) \
- FN(transpose_relaxed)
-
-#define FORWARD_DECLARE_GENERATED_OBJECTS(function) \
- namespace function { \
- extern std::vector<MixedTypedExample> examples; \
- Model createTestModel(); \
- }
-
-FOR_EACH_TEST_MODEL(FORWARD_DECLARE_GENERATED_OBJECTS)
-
-#undef FORWARD_DECLARE_GENERATED_OBJECTS
-
-} // namespace functional
-} // namespace vts
-} // namespace V1_2
-} // namespace neuralnetworks
-} // namespace hardware
-} // namespace android
-
-#endif // VTS_HAL_NEURALNETWORKS_V1_2_VTS_FUNCTIONAL_MODELS_H
diff --git a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
index 3096028..c4f1b5e 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
@@ -161,7 +161,7 @@
case OperandType::TENSOR_FLOAT32:
case OperandType::TENSOR_INT32:
case OperandType::TENSOR_QUANT8_ASYMM:
- case OperandType::TENSOR_QUANT16_ASYMM:
+ case OperandType::TENSOR_QUANT16_SYMM:
return 0;
default:
return 0;
@@ -193,7 +193,7 @@
case OperandType::TENSOR_INT32:
return -1.0f;
case OperandType::TENSOR_QUANT8_ASYMM:
- case OperandType::TENSOR_QUANT16_ASYMM:
+ case OperandType::TENSOR_QUANT16_SYMM:
return 0.0f;
default:
return 0.0f;
@@ -224,8 +224,9 @@
case OperandType::TENSOR_INT32:
return {1};
case OperandType::TENSOR_QUANT8_ASYMM:
- case OperandType::TENSOR_QUANT16_ASYMM:
return {-1, 256};
+ case OperandType::TENSOR_QUANT16_SYMM:
+ return {-32769, -1, 1, 32768};
default:
return {};
}
@@ -278,7 +279,7 @@
newOperand.zeroPoint = 0;
break;
case OperandType::TENSOR_QUANT8_ASYMM:
- case OperandType::TENSOR_QUANT16_ASYMM:
+ case OperandType::TENSOR_QUANT16_SYMM:
newOperand.dimensions =
operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
newOperand.scale = operand->scale != 0.0f ? operand->scale : 1.0f;
@@ -291,15 +292,33 @@
*operand = newOperand;
}
-static bool mutateOperationOperandTypeSkip(size_t operand, const Model& model) {
- // LSH_PROJECTION's second argument is allowed to have any type. This is the
- // only operation that currently has a type that can be anything independent
- // from any other type. Changing the operand type to any other type will
- // result in a valid model for LSH_PROJECTION. If this is the case, skip the
- // test.
+static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, const Model& model) {
+ // Do not test OEM types
+ if (type == model.operands[operand].type || type == OperandType::OEM ||
+ type == OperandType::TENSOR_OEM_BYTE) {
+ return true;
+ }
for (const Operation& operation : model.operations) {
- if (operation.type == OperationType::LSH_PROJECTION && operand == operation.inputs[1]) {
- return true;
+ // Skip mutateOperationOperandTypeTest for the following operations.
+ // - LSH_PROJECTION's second argument is allowed to have any type.
+ // - ARGMIN and ARGMAX's first argument can be any of TENSOR_(FLOAT32|INT32|QUANT8_ASYMM).
+ // - CAST's argument can be any of TENSOR_(FLOAT32|INT32|QUANT8_ASYMM).
+ switch (operation.type) {
+ case OperationType::LSH_PROJECTION: {
+ if (operand == operation.inputs[1]) {
+ return true;
+ }
+ } break;
+ case OperationType::CAST:
+ case OperationType::ARGMAX:
+ case OperationType::ARGMIN: {
+ if (type == OperandType::TENSOR_FLOAT32 || type == OperandType::TENSOR_INT32 ||
+ type == OperandType::TENSOR_QUANT8_ASYMM) {
+ return true;
+ }
+ } break;
+ default:
+ break;
}
}
return false;
@@ -307,14 +326,8 @@
static void mutateOperationOperandTypeTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
- if (mutateOperationOperandTypeSkip(operand, model)) {
- continue;
- }
for (OperandType invalidOperandType : hidl_enum_range<OperandType>{}) {
- // Do not test OEM types
- if (invalidOperandType == model.operands[operand].type ||
- invalidOperandType == OperandType::OEM ||
- invalidOperandType == OperandType::TENSOR_OEM_BYTE) {
+ if (mutateOperationOperandTypeSkip(operand, invalidOperandType, model)) {
continue;
}
const std::string message = "mutateOperationOperandTypeTest: operand " +
@@ -406,8 +419,26 @@
removeValueAndDecrementGreaterValues(&model->outputIndexes, index);
}
+static bool removeOperandSkip(size_t operand, const Model& model) {
+ for (const Operation& operation : model.operations) {
+ // Skip removeOperandTest for the following operations.
+ // - SPLIT's outputs are not checked during prepareModel.
+ if (operation.type == OperationType::SPLIT) {
+ for (const size_t outOprand : operation.outputs) {
+ if (operand == outOprand) {
+ return true;
+ }
+ }
+ }
+ }
+ return false;
+}
+
static void removeOperandTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
+ if (removeOperandSkip(operand, model)) {
+ continue;
+ }
const std::string message = "removeOperandTest: operand " + std::to_string(operand);
validate(device, message, model,
[operand](Model* model) { removeOperand(model, operand); });
@@ -433,15 +464,76 @@
///////////////////////// REMOVE OPERATION INPUT /////////////////////////
+static bool removeOperationInputSkip(const Operation& op, size_t input) {
+ // Skip removeOperationInputTest for the following operations.
+ // - CONCATENATION has at least 2 inputs, with the last element being INT32.
+ // - CONV_2D, DEPTHWISE_CONV_2D, MAX_POOL_2D, AVERAGE_POOL_2D, L2_POOL_2D, RESIZE_BILINEAR,
+ // SPACE_TO_DEPTH, SPACE_TO_DEPTH, SPACE_TO_BATCH_ND, BATCH_TO_SPACE_ND can have an optional
+ // layout parameter.
+ // - L2_NORMALIZATION, LOCAL_RESPONSE_NORMALIZATION, SOFTMAX can have an optional axis
+ // parameter.
+ switch (op.type) {
+ case OperationType::CONCATENATION: {
+ if (op.inputs.size() > 2 && input != op.inputs.size() - 1) {
+ return true;
+ }
+ } break;
+ case OperationType::DEPTHWISE_CONV_2D: {
+ if ((op.inputs.size() == 12 && input == 11) || (op.inputs.size() == 9 && input == 8)) {
+ return true;
+ }
+ } break;
+ case OperationType::CONV_2D:
+ case OperationType::AVERAGE_POOL_2D:
+ case OperationType::MAX_POOL_2D:
+ case OperationType::L2_POOL_2D: {
+ if ((op.inputs.size() == 11 && input == 10) || (op.inputs.size() == 8 && input == 7)) {
+ return true;
+ }
+ } break;
+ case OperationType::RESIZE_BILINEAR: {
+ if (op.inputs.size() == 4 && input == 3) {
+ return true;
+ }
+ } break;
+ case OperationType::SPACE_TO_DEPTH:
+ case OperationType::DEPTH_TO_SPACE:
+ case OperationType::BATCH_TO_SPACE_ND: {
+ if (op.inputs.size() == 3 && input == 2) {
+ return true;
+ }
+ } break;
+ case OperationType::SPACE_TO_BATCH_ND: {
+ if (op.inputs.size() == 4 && input == 3) {
+ return true;
+ }
+ } break;
+ case OperationType::L2_NORMALIZATION: {
+ if (op.inputs.size() == 2 && input == 1) {
+ return true;
+ }
+ } break;
+ case OperationType::LOCAL_RESPONSE_NORMALIZATION: {
+ if (op.inputs.size() == 6 && input == 5) {
+ return true;
+ }
+ } break;
+ case OperationType::SOFTMAX: {
+ if (op.inputs.size() == 3 && input == 2) {
+ return true;
+ }
+ } break;
+ default:
+ break;
+ }
+ return false;
+}
+
static void removeOperationInputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
const Operation& op = model.operations[operation];
- // CONCATENATION has at least 2 inputs, with the last element being
- // INT32. Skip this test if removing one of CONCATENATION's
- // inputs still produces a valid model.
- if (op.type == OperationType::CONCATENATION && op.inputs.size() > 2 &&
- input != op.inputs.size() - 1) {
+ if (removeOperationInputSkip(op, input)) {
continue;
}
const std::string message = "removeOperationInputTest: operation " +
@@ -479,8 +571,23 @@
///////////////////////// ADD OPERATION INPUT /////////////////////////
+static bool addOperationInputSkip(const Operation& op) {
+ // Skip addOperationInputTest for the following operations.
+ // - L2_NORMALIZATION, LOCAL_RESPONSE_NORMALIZATION, SOFTMAX can have an optional INT32 axis
+ // parameter.
+ if ((op.type == OperationType::L2_NORMALIZATION && op.inputs.size() == 1) ||
+ (op.type == OperationType::LOCAL_RESPONSE_NORMALIZATION && op.inputs.size() == 5) ||
+ (op.type == OperationType::SOFTMAX && op.inputs.size() == 2)) {
+ return true;
+ }
+ return false;
+}
+
static void addOperationInputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
+ if (addOperationInputSkip(model.operations[operation])) {
+ continue;
+ }
const std::string message = "addOperationInputTest: operation " + std::to_string(operation);
validate(device, message, model, [operation](Model* model) {
uint32_t index = addOperand(model, OperandLifeTime::MODEL_INPUT);
diff --git a/neuralnetworks/1.2/vts/functional/ValidationTests.cpp b/neuralnetworks/1.2/vts/functional/ValidationTests.cpp
deleted file mode 100644
index 3bdc5cd..0000000
--- a/neuralnetworks/1.2/vts/functional/ValidationTests.cpp
+++ /dev/null
@@ -1,50 +0,0 @@
-/*
- * Copyright (C) 2018 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#define LOG_TAG "neuralnetworks_hidl_hal_test"
-
-#include "Models.h"
-#include "VtsHalNeuralnetworks.h"
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_2 {
-namespace vts {
-namespace functional {
-
-// forward declarations
-std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
-
-// generate validation tests
-#define VTS_CURRENT_TEST_CASE(TestName) \
- TEST_F(ValidationTest, TestName) { \
- const Model model = TestName::createTestModel(); \
- const std::vector<Request> requests = createRequests(TestName::examples); \
- validateModel(model); \
- validateRequests(model, requests); \
- }
-
-FOR_EACH_TEST_MODEL(VTS_CURRENT_TEST_CASE)
-
-#undef VTS_CURRENT_TEST_CASE
-
-} // namespace functional
-} // namespace vts
-} // namespace V1_2
-} // namespace neuralnetworks
-} // namespace hardware
-} // namespace android