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Commit 17689aa6 authored by Lev Proleev's avatar Lev Proleev Committed by Slava Shklyaev
Browse files

NNAPI: Add state outputs for {UNI|BI}DIRECTIONAL_SEQUENCE_{RNN|LSTM} 

Fix: 138443991
Test: NNTest_static and VtsHalNeuralnetworksV1_3TargetTest
Change-Id: I0a3af22826d438f6f38de1f64042a50f98265e2d
Merged-In: I0a3af22826d438f6f38de1f64042a50f98265e2d
(cherry picked from commit 188a8f90)
parent 294cfe01

current.txt

+1 −1
Original line number Diff line number Diff line
@@ -630,7 +630,7 @@ ddcf89cd8ee2df0d32aee55050826446fb64f7aafde0a7cd946c64f61b1a364c android.hardwar 
2fa3679ad7c94b5e88724adcd560c561041068a4ca565c63830e68101988746a android.hardware.neuralnetworks@1.3::IFencedExecutionCallback

237b23b126a66f3432658020fed78cdd06ba6297459436fe6bae0ba753370833 android.hardware.neuralnetworks@1.3::IPreparedModel

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

abbc4e1a969881c9f8ab587add5b5e75b08df834c9c969c013ae38cb4bb16f6a android.hardware.neuralnetworks@1.3::types

2fabd246f985d94a0172dacefb0d6cf19e2aeb2d5f17752653988ef39570a52d 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

+49 −0
Original line number Diff line number Diff line
@@ -2556,6 +2556,30 @@ enum OperationType : int32_t { 
     *      A 3-D tensor of shape:

     *        If time-major: [max_time, batch_size, bw_output_size]

     *        If batch-major: [batch_size, max_time, bw_output_size]

     * * 2: The forward activation state output.

     *      A 2-D tensor of shape [batch_size, fw_output_size] containing an

     *      activation state from the last time step in the sequence. This

     *      output is optional and can be omitted. If this output is present

     *      then outputs 3-5 must be present as well.

     *      Available since HAL version 1.3.

     * * 3: The forward cell state output.

     *      A tensor of shape [batch_size, fw_cell_size] containing a cell state

     *      from the last time step in the sequence. This output is optional

     *      and can be omitted. If this output is present

     *      then outputs 2, 4, 5 must be present as well.

     *      Available since HAL version 1.3.

     * * 4: The backward activation state output.

     *      A 2-D tensor of shape [batch_size, bw_output_size] containing an

     *      activation state from the last time step in the sequence. This

     *      output is optional and can be omitted. If this output is present

     *      then outputs 2, 3, 5 must be present as well.

     *      Available since HAL version 1.3.

     * * 5: The backward cell state output.

     *      A tensor of shape [batch_size, bw_cell_size] containing a cell state

     *      from the last time step in the sequence. This output is optional

     *      and can be omitted. If this output is present

     *      then outputs 2-4 must be present as well.

     *      Available since HAL version 1.3.

     */

    BIDIRECTIONAL_SEQUENCE_LSTM = @1.2::OperationType:BIDIRECTIONAL_SEQUENCE_LSTM,
@@ -2673,6 +2697,18 @@ enum OperationType : int32_t { 
     *      (timeMajor). If it is set to true, then the shape is set to

     *      [maxTime, batchSize, bwNumUnits], otherwise the shape is set to

     *      [batchSize, maxTime, bwNumUnits].

     * * 2: The forward hidden state output.

     *      A 2-D tensor of shape [batchSize, fwNumUnits] containing a hidden

     *      state from the last time step in the sequence. This output is

     *      optional and can be omitted. If this output is present then output

     *      3 must be present as well.

     *      Available since HAL version 1.3.

     * * 3: The backward hidden state output.

     *      A 2-D tensor of shape [batchSize, bwNumUnits] containing a hidden

     *      state from the last time step in the sequence. This output is

     *      optional and can be omitted. If this output is present then output

     *      2 must be present as well.

     *      Available since HAL version 1.3.

     */

    BIDIRECTIONAL_SEQUENCE_RNN = @1.2::OperationType:BIDIRECTIONAL_SEQUENCE_RNN,
@@ -4656,6 +4692,15 @@ enum OperationType : int32_t { 
     *      A 3-D tensor of shape:

     *        If time-major: [max_time, batch_size, output_size]

     *        If batch-major: [batch_size, max_time, output_size]

     * * 1: A tensor of shape [batch_size, output_size] containing a hidden

     *      state from the last time step in the sequence. This output is

     *      optional and can be omitted. If this output is present then

     *      output #2 must be present as well.

     *      Available since HAL version 1.3.

     * * 2: A tensor of shape [batch_size, cell_size] containing a cell state

     *      from the last time step in the sequence. This output is optional

     *      and can be omitted.

     *      Available since HAL version 1.3.

     */

    UNIDIRECTIONAL_SEQUENCE_LSTM = @1.2::OperationType:UNIDIRECTIONAL_SEQUENCE_LSTM,
@@ -4711,6 +4756,10 @@ enum OperationType : int32_t { 
     *      it is set to 1, then the output has a shape [maxTime, batchSize,

     *      numUnits], otherwise the output has a shape [batchSize, maxTime,

     *      numUnits].

     * * 1: A tensor of shape [batchSize, numUnits] containing hidden state

     *      from the last time step in the sequence. This output is optional

     *      and can be omitted.

     *      Available since HAL version 1.3.

     */

    UNIDIRECTIONAL_SEQUENCE_RNN = @1.2::OperationType:UNIDIRECTIONAL_SEQUENCE_RNN,

neuralnetworks/1.3/vts/functional/ValidateModel.cpp

+9 −3
Original line number Diff line number Diff line
@@ -527,9 +527,15 @@ static bool removeOperandSkip(size_t operand, const Model& model) { 
                }

            }

        }

        // BIDIRECTIONAL_SEQUENCE_LSTM and BIDIRECTIONAL_SEQUENCE_RNN can have either one or two

        // outputs depending on their mergeOutputs parameter.

        if (operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_LSTM ||

        // BIDIRECTIONAL_SEQUENCE_LSTM and BIDIRECTIONAL_SEQUENCE_RNN can have

        // either one, two, three or four outputs depending on their

        // mergeOutputs parameter and if state outputs are provided.

        // UNIDIRECTIONAL_SEQUENCE_LSTM and UNIDIRECTIONAL_SEQUENCE_RNN can have

        // either one or three outputs depending on whether state outputs are

        // provided.

        if (operation.type == OperationType::UNIDIRECTIONAL_SEQUENCE_LSTM ||

            operation.type == OperationType::UNIDIRECTIONAL_SEQUENCE_RNN ||

            operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_LSTM ||

            operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_RNN) {

            for (const size_t outOprand : operation.outputs) {

                if (operand == outOprand) {