diff --git a/current.txt b/current.txt index 5eb7a6f146..d0666a860b 100644 --- a/current.txt +++ b/current.txt @@ -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 diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal index c5dc08c338..530f9849fa 100644 --- a/neuralnetworks/1.3/types.hal +++ b/neuralnetworks/1.3/types.hal @@ -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, diff --git a/neuralnetworks/1.3/vts/functional/ValidateModel.cpp b/neuralnetworks/1.3/vts/functional/ValidateModel.cpp index 0a35e2d233..b9ea430694 100644 --- a/neuralnetworks/1.3/vts/functional/ValidateModel.cpp +++ b/neuralnetworks/1.3/vts/functional/ValidateModel.cpp @@ -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) {