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Commit 503d8503 authored by Lev Proleev's avatar Lev Proleev Committed by Xusong Wang
Browse files

Add ELU and HARD_SWISH 

Bug: 147482068
Bug: 147481241
Test: NNTest_static and VtsHalNeuralnetworksV1_3TargetTest
Change-Id: Iab8da2a666ad9775dfb53d9297e94962fb651353
Merged-In: Iab8da2a666ad9775dfb53d9297e94962fb651353
(cherry picked from commit aee67f83)
parent e4f15833

current.txt

+1 −1
Original line number Diff line number Diff line
@@ -627,7 +627,7 @@ d1f382d14e1384b907d5bb5780df7f01934650d556fedbed2f15a90773c657d6 android.hardwar 
4167dc3ad35e9cd0d2057d4868c7675ae2c3c9d05bbd614c1f5dccfa5fd68797 android.hardware.neuralnetworks@1.3::IExecutionCallback

7d23020248194abbee8091cc624f39a5a6d7ccba338b172d5d2d3df0cceffbee android.hardware.neuralnetworks@1.3::IPreparedModel

0439a1fbbec7f16e5e4c653d85ac685d51bfafbae15b8f8cca530acdd7d6a8ce android.hardware.neuralnetworks@1.3::IPreparedModelCallback

162515505235bc770601f02c3537f9ccf11582583bf7b11dd2ec81fab6855333 android.hardware.neuralnetworks@1.3::types

26c643aedf4e28b8d82e517d9cd70601b37f881e1ea94f09808d9e233517e400 android.hardware.neuralnetworks@1.3::types

3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi

a64467bae843569f0d465c5be7f0c7a5b987985b55a3ef4794dd5afc68538650 android.hardware.wifi.supplicant@1.3::ISupplicant

44445b8a03d7b9e68b2fbd954672c18a8fce9e32851b0692f4f4ab3407f86ecb android.hardware.wifi.supplicant@1.3::ISupplicantStaIface

neuralnetworks/1.3/types.hal

+51 −1
Original line number Diff line number Diff line
@@ -4986,6 +4986,56 @@ enum OperationType : int32_t { 
     */

    WHILE = 97,



    /**

     * Computes exponential linear activation on the input tensor element-wise.

     *

     * The output is calculated using the following formula:

     *

     *     ELU(x) = max(0, x) + min(0, alpha * (exp(x) - 1))

     *

     * Supported tensor {@link OperandType}:

     * * {@link OperandType::TENSOR_FLOAT16}

     * * {@link OperandType::TENSOR_FLOAT32}

     *

     * Inputs:

     * * 0: A tensor, specifying the input. May be zero-sized.

     * * 1: A scalar, specifying the alpha parameter.

     *      For input tensor of {@link OperandType::TENSOR_FLOAT16},

     *      the alpha value must be of {@link OperandType::FLOAT16}.

     *      For input tensor of {@link OperandType::TENSOR_FLOAT32},

     *      the alpha value must be of {@link OperandType::FLOAT32}.

     *

     * Outputs:

     * * 0: The output tensor of same shape and type as input0.

     */

    ELU = 98,



    /**

     * Computes hard-swish activation on the input tensor element-wise.

     *

     * Hard swish activation is introduced in

     * https://arxiv.org/pdf/1905.02244.pdf

     *

     * The output is calculated using the following formula:

     *

     *     h-swish(x) = x * max(0, min(6, (x + 3))) / 6



     * Supported tensor {@link OperandType}:

     * * {@link OperandType::TENSOR_FLOAT16}

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}

     *

     * Inputs:

     * * 0: A tensor, specifying the input. May be zero-sized.

     *

     * Outputs:

     * * 0: The output tensor of same shape and type as input0.

     *      Scale and zero point of this tensor may be different from the input

     *      tensor's parameters.

     */

    HARD_SWISH = 99,



    /**

     * DEPRECATED. Since NNAPI 1.2, extensions are the preferred alternative to

     * OEM operation and data types.
@@ -5008,7 +5058,7 @@ enum OperationType : int32_t { 
enum OperationTypeRange : uint32_t {

    BASE_MIN        = 0,

    FUNDAMENTAL_MIN = 0,

    FUNDAMENTAL_MAX = 97,

    FUNDAMENTAL_MAX = 99,

    OEM_MIN         = 10000,

    OEM_MAX         = 10000,

    BASE_MAX        = 0xFFFF,