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Commit 4b458caa authored by David Gross's avatar David Gross
Browse files

Add Capabilities::relaxedFloat32toFloat16Performance for 1.1. 

Test: VtsHalNeuralnetworksV1_0TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.0::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_0TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.0::IDevice/hvx
Test: VtsHalNeuralnetworksV1_1TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.1::IDevice/sample-all
Test: NeuralNetworksTest_static

Bug: 63911257

Change-Id: I040b68d84504180ba3039e4690d0cd43c2c2649f
parent 0dd5a587

neuralnetworks/1.1/IDevice.hal

+14 −0
Original line number Diff line number Diff line
@@ -24,6 +24,20 @@ import @1.0::IPreparedModelCallback; 
 * This interface represents a device driver.

 */

interface IDevice extends @1.0::IDevice {

    /**

     * Gets the capabilities of a driver.

     *

     * Note that @1.1::Capabilities provides performance information

     * on relaxed calculations, whereas @1.0::Capabilities does not.

     *

     * @return status Error status of the call, must be:

     *                - NONE if successful

     *                - DEVICE_UNAVAILABLE if driver is offline or busy

     *                - GENERAL_FAILURE if there is an unspecified error

     * @return capabilities Capabilities of the driver.

     */

    getCapabilities_1_1() generates (ErrorStatus status, Capabilities capabilities);



    /**

     * Gets the supported operations in a model.

     *

neuralnetworks/1.1/types.hal

+23 −0
Original line number Diff line number Diff line
@@ -18,6 +18,7 @@ package android.hardware.neuralnetworks@1.1; 


import @1.0::Operand;

import @1.0::OperationType;

import @1.0::PerformanceInfo;



/**

 * Operation types.
@@ -258,6 +259,28 @@ enum OperationType : @1.0::OperationType { 
    TRANSPOSE = 37,

};



/**

 * The capabilities of a driver.

 */

struct Capabilities {

    /**

     * Driver performance when operating on float32 data.

     */

    PerformanceInfo float32Performance;



    /**

     * Driver performance when operating on asymmetric 8-bit quantized data.

     */

    PerformanceInfo quantized8Performance;



    /**

     * Driver performance when operating on float32 data but performing

     * calculations with range and/or precision as low as that of the IEEE

     * 754 16-bit floating-point format.

     */

    PerformanceInfo relaxedFloat32toFloat16Performance;

};



/**

 * Describes one operation of the model's graph.

 */

neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworksV1_1BasicTest.cpp

+4 −2
Original line number Diff line number Diff line
@@ -29,7 +29,6 @@ 
#include <hidlmemory/mapping.h>



using ::android::hardware::neuralnetworks::V1_0::IPreparedModel;

using ::android::hardware::neuralnetworks::V1_0::Capabilities;

using ::android::hardware::neuralnetworks::V1_0::DeviceStatus;

using ::android::hardware::neuralnetworks::V1_0::ErrorStatus;

using ::android::hardware::neuralnetworks::V1_0::FusedActivationFunc;
@@ -37,6 +36,7 @@ using ::android::hardware::neuralnetworks::V1_0::Operand; 
using ::android::hardware::neuralnetworks::V1_0::OperandLifeTime;

using ::android::hardware::neuralnetworks::V1_0::OperandType;

using ::android::hardware::neuralnetworks::V1_0::Request;

using ::android::hardware::neuralnetworks::V1_1::Capabilities;

using ::android::hardware::neuralnetworks::V1_1::IDevice;

using ::android::hardware::neuralnetworks::V1_1::Model;

using ::android::hardware::neuralnetworks::V1_1::Operation;
@@ -95,12 +95,14 @@ TEST_F(NeuralnetworksHidlTest, StatusTest) { 
// initialization

TEST_F(NeuralnetworksHidlTest, GetCapabilitiesTest) {

    Return<void> ret =

        device->getCapabilities([](ErrorStatus status, const Capabilities& capabilities) {

        device->getCapabilities_1_1([](ErrorStatus status, const Capabilities& capabilities) {

            EXPECT_EQ(ErrorStatus::NONE, status);

            EXPECT_LT(0.0f, capabilities.float32Performance.execTime);

            EXPECT_LT(0.0f, capabilities.float32Performance.powerUsage);

            EXPECT_LT(0.0f, capabilities.quantized8Performance.execTime);

            EXPECT_LT(0.0f, capabilities.quantized8Performance.powerUsage);

            EXPECT_LT(0.0f, capabilities.relaxedFloat32toFloat16Performance.execTime);

            EXPECT_LT(0.0f, capabilities.relaxedFloat32toFloat16Performance.powerUsage);

        });

    EXPECT_TRUE(ret.isOk());

}