Add parallel linking support for BIDIRECTIONAL_SEQUENCE_{LSTM|RNN} (13c43c00) · Commits · e / os / android_hardware_interfaces

current.txt

+2 −2

Original line number	Diff line number	Diff line
		@@ -597,7 +597,7 @@ eb2fa0c883c2185d514be0b84c179b283753ef0c1b77b45b4f359bd23bba8b75 android.hardwar
		5f6d3097ba84cb63c430787123f4de1b31c11f90b531b98eae9a8623a5ae962a android.hardware.neuralnetworks@1.1::types
		fb382e986c10b8fbb797a8546e8f9ea6d1107bfe6f3fb7e57f6bbbf1f807a906 android.hardware.neuralnetworks@1.2::IDevice
		40e71cd693de5b832325c5d8f081f2ff20a7ba2b89d401cee5b4b3eb0e241681 android.hardware.neuralnetworks@1.2::IPreparedModel
		6c29d6fdd5445911df5456b3b84b949cdd59fca0c0b5507662f26a5cac0cf5e5 android.hardware.neuralnetworks@1.2::types
		00649d29680f2c47edf60000c3ae7ae906ba638f0616947147e3676a83cf36fa android.hardware.neuralnetworks@1.2::types
		a785a57447a81e9c130eef6904c3a5c256076c6a04588c40620ebd6fa2660d77 android.hardware.radio@1.2::types
		1a6e2bd289f22931c526b21916910f1d4c436b7acb9556e4243de4ce8e6cc2e4 android.hardware.soundtrigger@2.0::ISoundTriggerHwCallback
		fd65298e1e09e0e3c781ab18305920d757dbe55a3b459ce17814ec5cf6dfee99 android.hardware.wifi@1.0::IWifiP2pIface
		@@ -676,7 +676,7 @@ a3eddd9bbdc87e8c22764070037dd1154f1cf006e6fba93364c4f85d4c134a19 android.hardwar
		2fa3679ad7c94b5e88724adcd560c561041068a4ca565c63830e68101988746a android.hardware.neuralnetworks@1.3::IFencedExecutionCallback
		43088ffc71945b463a7279262cfe2e290f6ed2f15d3fd6032798a3be299fb08f android.hardware.neuralnetworks@1.3::IPreparedModel
		0439a1fbbec7f16e5e4c653d85ac685d51bfafbae15b8f8cca530acdd7d6a8ce android.hardware.neuralnetworks@1.3::IPreparedModelCallback
		306fda32ac969fd51d75d066352cadcb769944ec4823be4cdd3f86fdb9e97511 android.hardware.neuralnetworks@1.3::types
		dd39887aa4fb60ce60ea9cc043edeadbbae6e922d09d3946311b0b410024ae14 android.hardware.neuralnetworks@1.3::types
		3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi
		c67aaf26a7a40d14ea61e70e20afacbd0bb906df1704d585ac8599fbb69dd44b android.hardware.wifi.hostapd@1.2::IHostapd
		2b5a7ea572b736030c64a3b4043af244425477c4672301780fe15aba5ed393d9 android.hardware.wifi.hostapd@1.2::types

neuralnetworks/1.2/types.hal

+40 −9

Original line number	Diff line number	Diff line
		@@ -2314,7 +2314,38 @@ enum OperationType : int32_t {
		AXIS_ALIGNED_BBOX_TRANSFORM = 41,

		/**
		* Performs a forward LSTM on the input followed by a backward LSTM.
		* A recurrent neural network layer that applies an LSTM cell to a
		* sequence of inputs in forward and backward directions.
		*
		* The op supports cross-linking via an auxiliary input. Regular cell feeds
		* one input into the two RNN cells in the following way:
		*
		* INPUT (INPUT_REVERSED)
		* \| \|
		* ---------------------
		* \| FW_LSTM BW_LSTM \|
		* ---------------------
		* \| \|
		* FW_OUT BW_OUT
		*
		* An op with cross-linking takes two inputs and feeds them into the RNN
		* cells in the following way:
		*
		* AUX_INPUT (AUX_INPUT_REVERSED)
		* \| \|
		* INPUT \| (INPUT_R'D.)\|
		* \| \| \| \|
		* -----------------------
		* \| \ / \ / \|
		* \| FW_LSTM BW_LSTM \|
		* -----------------------
		* \| \|
		* FW_OUT BW_OUT
		*
		* The cross-linking mode is enabled iff auxiliary input and auxiliary
		* weights are present. While stacking this op on top of itself, this
		* allows to connect both forward and backward outputs from previous cell
		* to the next cell's input.
		*
		* Supported tensor {@link OperandType}:
		* * {@link OperandType::TENSOR_FLOAT16}
		@@ -2324,7 +2355,6 @@ enum OperationType : int32_t {
		*
		* All input and output tensors must be of the same type.
		*
		*
		* Inputs:
		* * 0: The input.
		* A 3-D tensor of shape:
		@@ -2533,8 +2563,8 @@ enum OperationType : int32_t {
		* * “activation” is the function passed as the “fused_activation_function”
		* argument (if not “NONE”).
		*
		* The op also supports an auxiliary input. Regular cell feeds one input
		* into the two RNN cells in the following way:
		* The op supports cross-linking via an auxiliary input. Regular cell feeds
		* one input into the two RNN cells in the following way:
		*
		* INPUT (INPUT_REVERSED)
		* \| \|
		@@ -2544,8 +2574,8 @@ enum OperationType : int32_t {
		* \| \|
		* FW_OUT BW_OUT
		*
		* An op with an auxiliary input takes two inputs and feeds them into the
		* RNN cells in the following way:
		* An op with cross-linking takes two inputs and feeds them into the RNN
		* cells in the following way:
		*
		* AUX_INPUT (AUX_INPUT_REVERSED)
		* \| \|
		@@ -2558,9 +2588,10 @@ enum OperationType : int32_t {
		* \| \|
		* FW_OUT BW_OUT
		*
		* While stacking this op on top of itself, this allows to connect both
		* forward and backward outputs from previous cell to the next cell's
		* inputs.
		* The cross-linking mode is enabled iff auxiliary input and auxiliary
		* weights are present. While stacking this op on top of itself, this
		* allows to connect both forward and backward outputs from previous cell
		* to the next cell's input.
		*
		* Supported tensor {@link OperandType}:
		* * {@link OperandType::TENSOR_FLOAT16}

neuralnetworks/1.3/types.hal

+107 −29

Original line number	Diff line number	Diff line
		@@ -2364,7 +2364,54 @@ enum OperationType : int32_t {
		AXIS_ALIGNED_BBOX_TRANSFORM = @1.2::OperationType:AXIS_ALIGNED_BBOX_TRANSFORM,

		/**
		* Performs a forward LSTM on the input followed by a backward LSTM.
		* A recurrent neural network layer that applies an LSTM cell to a
		* sequence of inputs in forward and backward directions.
		*
		* The op supports cross-linking via an auxiliary input. Regular cell feeds
		* one input into the two RNN cells in the following way:
		*
		* INPUT (INPUT_REVERSED)
		* \| \|
		* ---------------------
		* \| FW_LSTM BW_LSTM \|
		* ---------------------
		* \| \|
		* FW_OUT BW_OUT
		*
		* An op with cross-linking takes two inputs and feeds them into the RNN
		* cells in the following way:
		*
		* AUX_INPUT (AUX_INPUT_REVERSED)
		* \| \|
		* INPUT \| (INPUT_R'D.)\|
		* \| \| \| \|
		* -----------------------
		* \| \ / \ / \|
		* \| FW_LSTM BW_LSTM \|
		* -----------------------
		* \| \|
		* FW_OUT BW_OUT
		*
		* The cross-linking mode is enabled iff auxiliary input and auxiliary
		* weights are present. While stacking this op on top of itself, this
		* allows to connect both forward and backward outputs from previous cell
		* to the next cell's input.
		*
		* Since HAL version 1.3 parallel linking mode is supported. The mode is
		* enabled if auxiliary input is present but auxiliary weights are omitted.
		* In this case, the cell feeds inputs into the RNN in the following way:
		*
		* INPUT (AUX_INPUT_REVERSED)
		* \| \|
		* ---------------------
		* \| FW_LSTM BW_LSTM \|
		* ---------------------
		* \| \|
		* FW_OUT BW_OUT
		*
		* While stacking this op on top of itself, this allows to connect both
		* forward and backward outputs from previous cell to the next cell's
		* corresponding inputs.
		*
		* Supported tensor {@link OperandType}:
		* * {@link OperandType::TENSOR_FLOAT16}
		@@ -2374,7 +2421,6 @@ enum OperationType : int32_t {
		*
		* All input and output tensors must be of the same type.
		*
		*
		* Inputs:
		* * 0: The input.
		* A 3-D tensor of shape:
		@@ -2466,25 +2512,34 @@ enum OperationType : int32_t {
		* * 38: The backward input cell state.
		* A 2-D tensor of shape [batch_size, bw_num_units].
		* * 39: The auxiliary input. Optional.
		* A 3-D tensor of shape [max_time, batch_size, input_size], where “batch_size”
		* corresponds to the batching dimension, and “input_size” is the size
		* of the input.
		* * 40: The forward auxiliary input-to-input weights. Optional.
		* A 2-D tensor of shape [fw_num_units, input_size].
		* * 41: The forward auxiliary input-to-forget weights. Optional.
		* A 2-D tensor of shape [fw_num_units, input_size].
		* * 42: The forward auxiliary input-to-cell weights. Optional.
		* A 2-D tensor of shape [fw_num_units, input_size].
		* * 43: The forward auxiliary input-to-output weights. Optional.
		* A 2-D tensor of shape [fw_num_units, input_size].
		* * 44: The backward auxiliary input-to-input weights. Optional.
		* A 2-D tensor of shape [bw_num_units, input_size].
		* * 45: The backward auxiliary input-to-forget weights. Optional.
		* A 2-D tensor of shape [bw_num_units, input_size].
		* * 46: The backward auxiliary input-to-cell weights. Optional.
		* A 2-D tensor of shape [bw_num_units, input_size].
		* * 47: The backward auxiliary input-to-output weights. Optional.
		* A 2-D tensor of shape [bw_num_units, input_size].
		* A 3-D tensor of shape [max_time, batch_size, aux_input_size],
		* where “batch_size” corresponds to the batching dimension, and
		* “aux_input_size” is the size of the auxiliary input. Optional. See
		* the docs above for the usage modes explanation.
		* * 40: The forward auxiliary input-to-input weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [fw_num_units, aux_input_size].
		* * 41: The forward auxiliary input-to-forget weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [fw_num_units, aux_input_size].
		* * 42: The forward auxiliary input-to-cell weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [fw_num_units, aux_input_size].
		* * 43: The forward auxiliary input-to-output weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [fw_num_units, aux_input_size].
		* * 44: The backward auxiliary input-to-input weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [bw_num_units, aux_input_size].
		* * 45: The backward auxiliary input-to-forget weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [bw_num_units, aux_input_size].
		* * 46: The backward auxiliary input-to-cell weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [bw_num_units, aux_input_size].
		* * 47: The backward auxiliary input-to-output weights.
		* Optional. See the docs above for the usage modes explanation.
		* A 2-D tensor of shape [bw_num_units, aux_input_size].
		* * 48: The activation function.
		* A value indicating the activation function:
		* <ul>
		@@ -2607,8 +2662,8 @@ enum OperationType : int32_t {
		* * “activation” is the function passed as the “fused_activation_function”
		* argument (if not “NONE”).
		*
		* The op also supports an auxiliary input. Regular cell feeds one input
		* into the two RNN cells in the following way:
		* The op supports cross-linking via an auxiliary input. Regular cell feeds
		* one input into the two RNN cells in the following way:
		*
		* INPUT (INPUT_REVERSED)
		* \| \|
		@@ -2618,8 +2673,8 @@ enum OperationType : int32_t {
		* \| \|
		* FW_OUT BW_OUT
		*
		* An op with an auxiliary input takes two inputs and feeds them into the
		* RNN cells in the following way:
		* An op with cross-linking takes two inputs and feeds them into the RNN
		* cells in the following way:
		*
		* AUX_INPUT (AUX_INPUT_REVERSED)
		* \| \|
		@@ -2632,9 +2687,26 @@ enum OperationType : int32_t {
		* \| \|
		* FW_OUT BW_OUT
		*
		* The cross-linking mode is enabled iff auxiliary input and auxiliary
		* weights are present. While stacking this op on top of itself, this
		* allows to connect both forward and backward outputs from previous cell
		* to the next cell's input.
		*
		* Since HAL version 1.3 parallel linking mode is supported. The mode is
		* enabled if auxiliary input is present but auxiliary weights are omitted.
		* In this case, the cell feeds inputs into the RNN in the following way:
		*
		* INPUT (AUX_INPUT_REVERSED)
		* \| \|
		* ---------------------
		* \| FW_RNN BW_RNN \|
		* ---------------------
		* \| \|
		* FW_OUT BW_OUT
		*
		* While stacking this op on top of itself, this allows to connect both
		* forward and backward outputs from previous cell to the next cell's
		* inputs.
		* corresponding inputs.
		*
		* Supported tensor {@link OperandType}:
		* * {@link OperandType::TENSOR_FLOAT16}
		@@ -2667,11 +2739,17 @@ enum OperationType : int32_t {
		* A 2-D tensor of shape [batchSize, bwNumUnits]. Specifies a hidden
		* state input for the first time step of the computation.
		* * 9: auxInput.
		* A 3-D tensor. The shape is the same as of the input 0.
		* A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
		* it is set to true, then the input has a shape [maxTime, batchSize,
		* auxInputSize], otherwise the input has a shape [batchSize, maxTime,
		* auxInputSize]. Can be omitted. See the docs above for the usage
		* modes explanation.
		* * 10:fwAuxWeights.
		* A 2-D tensor of shape [fwNumUnits, inputSize].
		* A 2-D tensor of shape [fwNumUnits, auxInputSize]. Can be omitted.
		* See the docs above for the usage modes explanation.
		* * 11:bwAuxWeights.
		* A 2-D tensor of shape [bwNumUnits, inputSize].
		* A 2-D tensor of shape [bwNumUnits, auxInputSize]. Can be omitted.
		* See the docs above for the usage modes explanation.
		* * 12:fusedActivationFunction.
		* A {@link FusedActivationFunc} value indicating the activation function. If
		* “NONE” is specified then it results in a linear activation.