Merge changes from topic "nnapi-cherrypick-from-master-and-pi-dev-to-aosp2" (1191f516) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h

+3 −1

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		@@ -34,9 +34,11 @@ namespace hardware {
		namespace neuralnetworks {
		namespace V1_1 {

		using V1_0::Request;
		using V1_0::DeviceStatus;
		using V1_0::ErrorStatus;
		using V1_0::Operand;
		using V1_0::OperandType;
		using V1_0::Request;

		namespace vts {
		namespace functional {

neuralnetworks/1.2/Android.bp

+2 −0

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		@@ -17,6 +17,8 @@ hidl_interface {
		],
		types: [
		"Model",
		"Operand",
		"OperandType",
		"Operation",
		"OperationType",
		],

neuralnetworks/1.2/IDevice.hal

+30 −0

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		@@ -25,6 +25,36 @@ import @1.1::IDevice;
		* This interface represents a device driver.
		*/
		interface IDevice extends @1.1::IDevice {
		/**
		* Get the version string of the driver implementation.
		*
		* The version string must be a unique token among the set of version strings of
		* drivers of a specific device. The token identifies the device driver's
		* implementation. The token must not be confused with the feature level which is solely
		* defined by the interface version. This API is opaque to the Android framework, but the
		* Android framework may use the information for debugging or to pass on to NNAPI applications.
		*
		* Application developers sometimes have specific requirements to ensure good user experiences,
		* and they need more information to make intelligent decisions when the Android framework cannot.
		* For example, combined with the device name and other information, the token can help
		* NNAPI applications filter devices based on their needs:
		* - An application demands a certain level of performance, but a specific version of
		* the driver cannot meet that requirement because of a performance regression.
		* The application can blacklist the driver based on the version provided.
		* - An application has a minimum precision requirement, but certain versions of
		* the driver cannot meet that requirement because of bugs or certain optimizations.
		* The application can filter out versions of these drivers.
		*
		* @return status Error status returned from querying the version string. Must be:
		* - NONE if the query was successful
		* - DEVICE_UNAVAILABLE if driver is offline or busy
		* - GENERAL_FAILURE if the query resulted in an
		* unspecified error
		* @return version The version string of the device implementation.
		* Must have nonzero length
		*/
		getVersionString() generates (ErrorStatus status, string version);

		/**
		* Gets the supported operations in a model.
		*

neuralnetworks/1.2/types.hal

+122 −1

Original line number	Diff line number	Diff line
		@@ -16,10 +16,36 @@

		package android.hardware.neuralnetworks@1.2;

		import @1.0::Operand;
		import @1.0::DataLocation;
		import @1.0::OperandLifeTime;
		import @1.0::OperandType;
		import @1.0::PerformanceInfo;
		import @1.1::OperationType;

		enum OperandType : @1.0::OperandType {
		/**
		* An 8 bit boolean scalar value.
		*
		* Values of this operand type are either true or false. A zero value
		* represents false; any other value represents true.
		*/
		BOOL = 6,
		/**
		* 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].
		*
		* The formula is:
		* realValue = (integerValue - zeroPoint) * scale.
		*/
		TENSOR_QUANT16_ASYMM = 7,
		/** A tensor of 16 bit floating point values. */
		TENSOR_FLOAT16 = 8,
		};

		/**
		* Operation types.
		*
		@@ -101,6 +127,101 @@ struct Operation {
		vec<uint32_t> outputs;
		};

		/**
		* Describes one operand of the model's graph.
		*/
		struct Operand {
		/**
		* Data type of the operand.
		*/
		OperandType type;

		/**
		* Dimensions of the operand.
		*
		* For a scalar operand, dimensions.size() must be 0.
		*
		* For a tensor operand, dimensions.size() must be at least 1;
		* however, any of the dimensions may be unspecified.
		*
		* A tensor operand with all dimensions specified has "fully
		* specified" dimensions. Whenever possible (i.e., whenever the
		* dimensions are known at model construction time), a tensor
		* operand should have (but is not required to have) fully
		* specified dimensions, in order to enable the best possible
		* performance.
		*
		* If a tensor operand's dimensions are not fully specified, the
		* dimensions of the operand are deduced from the operand
		* dimensions and values of the operation for which that operand
		* is an output.
		*
		* In the following situations, a tensor operand's dimensions must
		* be fully specified:
		*
		* . The operand has lifetime CONSTANT_COPY or
		* CONSTANT_REFERENCE.
		*
		* . The operand has lifetime MODEL_INPUT or MODEL_OUTPUT. Fully
		* specified dimensions must either be present in the
		* Operand or they must be provided in the corresponding
		* RequestArgument.
		* EXCEPTION: If the input or output is optional and omitted
		* (by setting the hasNoValue field of the corresponding
		* RequestArgument to true) then it need not have fully
		* specified dimensions.
		*
		* A tensor operand with some number of unspecified dimensions is
		* represented by setting each unspecified dimension to 0.
		*/
		vec<uint32_t> dimensions;

		/**
		* The number of times this operand appears as an operation input.
		*
		* (For example, if this operand appears once in one operation's
		* input list, and three times in another operation's input list,
		* then numberOfConsumers = 4.)
		*/
		uint32_t numberOfConsumers;

		/**
		* Quantized scale of the operand.
		*
		* Only applicable if the operand is of type TENSOR_QUANT8_ASYMM or
		* TENSOR_INT32.
		*/
		float scale;

		/**
		* Quantized zero-point offset of the operand.
		*
		* Only applicable if the operand is of type TENSOR_QUANT8_ASYMM.
		*/
		int32_t zeroPoint;

		/**
		* How the operand is used.
		*/
		OperandLifeTime lifetime;

		/**
		* Where to find the data for this operand.
		* If the lifetime is TEMPORARY_VARIABLE, MODEL_INPUT, MODEL_OUTPUT, or
		* NO_VALUE:
		* - All the fields must be 0.
		* If the lifetime is CONSTANT_COPY:
		* - location.poolIndex is 0.
		* - location.offset is the offset in bytes into Model.operandValues.
		* - location.length is set.
		* If the lifetime is CONSTANT_REFERENCE:
		* - location.poolIndex is set.
		* - location.offset is the offset in bytes into the specified pool.
		* - location.length is set.
		*/
		DataLocation location;
		};

		/**
		* A Neural Network Model.
		*

neuralnetworks/1.2/vts/functional/BasicTests.cpp

+8 −0

Original line number	Diff line number	Diff line
		@@ -37,6 +37,14 @@ TEST_F(NeuralnetworksHidlTest, StatusTest) {
		EXPECT_EQ(DeviceStatus::AVAILABLE, static_cast<DeviceStatus>(status));
		}

		// device version test
		TEST_F(NeuralnetworksHidlTest, GetDeviceVersionStringTest) {
		Return<void> ret = device->getVersionString([](ErrorStatus status, const hidl_string& version) {
		EXPECT_EQ(ErrorStatus::NONE, status);
		EXPECT_LT(0, version.size());
		});
		EXPECT_TRUE(ret.isOk());
		}
		} // namespace functional
		} // namespace vts
		} // namespace V1_2