Merge changes from topics "replace_asymm", "fp16-op-add" (5a080f41) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.0/vts/functional/Android.bp

+21 −6

Original line number	Diff line number	Diff line
		@@ -39,17 +39,14 @@ cc_library_static {
		],
		}

		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 @@ cc_test {
		"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",
		],
		}

neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp

+20 −19

Original line number	Diff line number	Diff line
		@@ -45,6 +45,7 @@ using ::test_helper::for_each;
		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 @@ void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* sr
		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 @@ void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool
		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 @@ void Execute(const sp<V1_0::IDevice>& device, std::function<V1_0::Model(void)> c
		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 @@ void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> c
		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 @@ void Execute(const sp<V1_2::IDevice>& device, std::function<V1_2::Model(void)> c
		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

neuralnetworks/1.0/vts/functional/GeneratedTests.cpp

+2 −0

Original line number	Diff line number	Diff line
		@@ -45,6 +45,8 @@ using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCa
		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"

neuralnetworks/1.0/vts/functional/Models.h

deleted100644 → 0

+0 −200

Original line number	Diff line number	Diff line
		/*
		* 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

neuralnetworks/1.1/vts/functional/Android.bp

+11 −30

Original line number	Diff line number	Diff line
		@@ -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,
		},
		},
		},
		}