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Move neuralnetworks HAL to hardware/interfaces

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The neuralnetworks hal was placed in
frameworks/ml/nn/hardware/interfaces while VTS tests were being
developed.

This CL moves it to hardware/interfaces and another CL removes
it from frameworks/ml/nn/hardware/interfaces.

VTS tests included in a sibling CL in this topic.

Bug: 63905942
Test: mm -j40
Change-Id: I0e6c84de72a763edbaef3e9b3063c3ecca216337
This commit is contained in:
Michael Butler 2017-07-27 18:28:20 -07:00
parent a732c00feb
commit 376ec0c0fd
5 changed files with 304 additions and 0 deletions
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70
neuralnetworks/1.0/Android.bp Normal file
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// This file is autogenerated by hidl-gen. Do not edit manually.
filegroup {
name: "android.hardware.neuralnetworks@1.0_hal",
srcs: [
"types.hal",
"IDevice.hal",
"IPreparedModel.hal",
],
}
genrule {
name: "android.hardware.neuralnetworks@1.0_genc++",
tools: ["hidl-gen"],
cmd: "$(location hidl-gen) -o $(genDir) -Lc++-sources -randroid.hardware:hardware/interfaces -randroid.hidl:system/libhidl/transport android.hardware.neuralnetworks@1.0",
srcs: [
":android.hardware.neuralnetworks@1.0_hal",
],
out: [
"android/hardware/neuralnetworks/1.0/types.cpp",
"android/hardware/neuralnetworks/1.0/DeviceAll.cpp",
"android/hardware/neuralnetworks/1.0/PreparedModelAll.cpp",
],
}
genrule {
name: "android.hardware.neuralnetworks@1.0_genc++_headers",
tools: ["hidl-gen"],
cmd: "$(location hidl-gen) -o $(genDir) -Lc++-headers -randroid.hardware:hardware/interfaces -randroid.hidl:system/libhidl/transport android.hardware.neuralnetworks@1.0",
srcs: [
":android.hardware.neuralnetworks@1.0_hal",
],
out: [
"android/hardware/neuralnetworks/1.0/types.h",
"android/hardware/neuralnetworks/1.0/hwtypes.h",
"android/hardware/neuralnetworks/1.0/IDevice.h",
"android/hardware/neuralnetworks/1.0/IHwDevice.h",
"android/hardware/neuralnetworks/1.0/BnHwDevice.h",
"android/hardware/neuralnetworks/1.0/BpHwDevice.h",
"android/hardware/neuralnetworks/1.0/BsDevice.h",
"android/hardware/neuralnetworks/1.0/IPreparedModel.h",
"android/hardware/neuralnetworks/1.0/IHwPreparedModel.h",
"android/hardware/neuralnetworks/1.0/BnHwPreparedModel.h",
"android/hardware/neuralnetworks/1.0/BpHwPreparedModel.h",
"android/hardware/neuralnetworks/1.0/BsPreparedModel.h",
],
}
cc_library_shared {
name: "android.hardware.neuralnetworks@1.0",
defaults: ["hidl-module-defaults"],
generated_sources: ["android.hardware.neuralnetworks@1.0_genc++"],
generated_headers: ["android.hardware.neuralnetworks@1.0_genc++_headers"],
export_generated_headers: ["android.hardware.neuralnetworks@1.0_genc++_headers"],
vendor_available: true,
shared_libs: [
"libhidlbase",
"libhidltransport",
"libhwbinder",
"liblog",
"libutils",
"libcutils",
],
export_shared_lib_headers: [
"libhidlbase",
"libhidltransport",
"libhwbinder",
"libutils",
],
}

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neuralnetworks/1.0/IDevice.hal Normal file
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/*
* Copyright (C) 2017 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.
*/
/* This HAL is a work in progress */
package android.hardware.neuralnetworks@1.0;
import IPreparedModel;
interface IDevice {
initialize() generates(Capabilities capabilities);
getSupportedSubgraph(Model model) generates(vec<bool> supported);
prepareModel(Model model) generates(IPreparedModel preparedModel);
getStatus() generates(DeviceStatus status);
};

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neuralnetworks/1.0/IPreparedModel.hal Normal file
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/*
* Copyright (C) 2017 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.
*/
/* This HAL is a work in progress */
package android.hardware.neuralnetworks@1.0;
interface IPreparedModel {
// TODO: The execution is synchronous. Change that to have a callback on completion.
// Multiple threads can call this execute function concurrently.
execute(Request request) generates(bool success);
};

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neuralnetworks/1.0/types.hal Normal file
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/*
* Copyright (C) 2017 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.
*/
/* This HAL is a work in progress */
package android.hardware.neuralnetworks@1.0;
// The types an operand can have.
// These values are the same as found in the NeuralNetworks.h file.
// When modifying, be sure to update HAL_NUM_OPERAND_TYPES in HalIntefaces.h.
enum OperandType : uint32_t {
FLOAT16 = 0,
FLOAT32 = 1,
INT8 = 2,
UINT8 = 3,
INT16 = 4,
UINT16 = 5,
INT32 = 6,
UINT32 = 7,
TENSOR_FLOAT16 = 8,
TENSOR_FLOAT32 = 9,
TENSOR_SYMMETRICAL_QUANT8 = 10,
};
// The type of operations. Unlike the operation types found in
// NeuralNetworks.h file, these specify the data type they operate on.
// This is done to simplify the work of drivers.
// TODO: Currently they are the same. Add a conversion when finalizing the model.
// When modifying, be sure to update HAL_NUM_OPERATION_TYPES in HalIntefaces.h.
enum OperationType : uint32_t {
AVERAGE_POOL_FLOAT32 = 0,
CONCATENATION_FLOAT32 = 1,
CONV_FLOAT32 = 2,
DEPTHWISE_CONV_FLOAT32 = 3,
MAX_POOL_FLOAT32 = 4,
L2_POOL_FLOAT32 = 5,
DEPTH_TO_SPACE_FLOAT32 = 6,
SPACE_TO_DEPTH_FLOAT32 = 7,
LOCAL_RESPONSE_NORMALIZATION_FLOAT32 = 8,
SOFTMAX_FLOAT32 = 9,
RESHAPE_FLOAT32 = 10,
SPLIT_FLOAT32 = 11,
FAKE_QUANT_FLOAT32 = 12,
ADD_FLOAT32 = 13,
FULLY_CONNECTED_FLOAT32 = 14,
CAST_FLOAT32 = 15,
MUL_FLOAT32 = 16,
L2_NORMALIZATION_FLOAT32 = 17,
LOGISTIC_FLOAT32 = 18,
RELU_FLOAT32 = 19,
RELU6_FLOAT32 = 20,
RELU1_FLOAT32 = 21,
TANH_FLOAT32 = 22,
DEQUANTIZE_FLOAT32 = 23,
FLOOR_FLOAT32 = 24,
GATHER_FLOAT32 = 25,
RESIZE_BILINEAR_FLOAT32 = 26,
LSH_PROJECTION_FLOAT32 = 27,
LSTM_FLOAT32 = 28,
SVDF_FLOAT32 = 29,
RNN_FLOAT32 = 30,
N_GRAM_FLOAT32 = 31,
LOOKUP_FLOAT32 = 32,
};
// Two special values that can be used instead of a regular poolIndex.
enum LocationValues : uint32_t {
// The location will be specified at runtime. It's either a temporary
// variable, an input, or an output.
LOCATION_AT_RUN_TIME = 0xFFFFFFFF,
// The operand's value is stored in the
// TODO: Only for old
LOCATION_SAME_BLOCK = 0xFFFFFFFE
};
// Status of a device.
enum DeviceStatus : uint32_t {
AVAILABLE,
BUSY,
OFFLINE,
UNKNOWN // Do we need this?
};
// For the reference workload
// Used by a driver to report its performance characteristics.
// TODO revisit the data types and scales.
struct PerformanceInfo {
float execTime; // in nanoseconds
float powerUsage; // in picoJoules
};
// The capabilities of a driver.
struct Capabilities {
vec<OperationType> supportedOperationTypes;
// TODO Do the same for baseline model IDs
bool cachesCompilation;
// TODO revisit the data types and scales.
float bootupTime; // in nanoseconds
PerformanceInfo float16Performance;
PerformanceInfo float32Performance;
PerformanceInfo quantized8Performance;
};
// Describes the location of a data object.
struct DataLocation {
// The index of the memory pool where this location is found.
// Two special values can also be used. See the LOCATION_* constants above.
uint32_t poolIndex;
// Offset in bytes from the start of the pool.
uint32_t offset;
// The length of the data, in bytes.
uint32_t length;
};
struct Operand {
OperandType type;
vec<uint32_t> dimensions;
// The number of operations that uses this operand as input.
// TODO It would be nice to track the actual consumers, e.g. vec<uint32_t> consumers;
uint32_t numberOfConsumers;
float scale;
int32_t zeroPoint;
// Where to find the data for this operand.
DataLocation location;
};
// Describes one operation of the graph.
struct Operation {
// The type of operation.
OperationType type;
// Describes the table that contains the indexes of the inputs of the
// operation. The offset is the index in the operandIndexes table.
vec<uint32_t> inputs;
// Describes the table that contains the indexes of the outputs of the
// operation. The offset is the index in the operandIndexes table.
vec<uint32_t> outputs;
};
struct InputOutputInfo {
DataLocation location;
// If dimensions.size() > 0, we have updated dimensions.
vec<uint32_t> dimensions;
};
struct Model {
vec<Operand> operands;
vec<Operation> operations;
vec<uint32_t> inputIndexes;
vec<uint32_t> outputIndexes;
vec<uint8_t> operandValues;
vec<memory> pools;
};
struct Request {
vec<InputOutputInfo> inputs;
vec<InputOutputInfo> outputs;
vec<memory> pools;
};

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// This is an autogenerated file, do not edit.
subdirs = [
"1.0",
]