Functions
arm_cmsis_nn_status	arm_nn_lstm_calculate_gate_s16 (const int16_t data_in, const int16_t hidden_in, const cmsis_nn_lstm_gate gate, const cmsis_nn_lstm_params params, int16_t *output, const int32_t batch_offset)
	Updates a LSTM gate for an iteration step of LSTM function, int16x8_16 version.

arm_cmsis_nn_status	arm_nn_lstm_calculate_gate_s8_s16 (const int8_t data_in, const int8_t hidden_in, const cmsis_nn_lstm_gate gate, const cmsis_nn_lstm_params params, int16_t *output, const int32_t batch_offset)
	Updates a LSTM gate for an iteration step of LSTM function, int8x8_16 version.

arm_cmsis_nn_status	arm_nn_lstm_step_f16 (const float16_t data_in, const float16_t hidden_in, float16_t hidden_out, const cmsis_nn_lstm_params_f16 params, cmsis_nn_lstm_context_f16 *buffers, const int32_t batch_offset)
	Update LSTM function for an iteration step using float16 input, output and state.

arm_cmsis_nn_status	arm_nn_lstm_step_f32 (const float32_t data_in, const float32_t hidden_in, float32_t hidden_out, const cmsis_nn_lstm_params_f32 params, cmsis_nn_lstm_context_f32 *buffers, const int32_t batch_offset)
	Update LSTM function for an iteration step using float32 input, output and state.

arm_cmsis_nn_status	arm_nn_lstm_step_s16 (const int16_t data_in, const int16_t hidden_in, int16_t hidden_out, const cmsis_nn_lstm_params params, cmsis_nn_lstm_context *buffers, const int32_t batch_offset)
	Update LSTM function for an iteration step using s16 input and output, and s16 internally.

arm_cmsis_nn_status	arm_nn_lstm_step_s8 (const int8_t data_in, const int8_t hidden_in, int8_t hidden_out, const cmsis_nn_lstm_params params, cmsis_nn_lstm_context *buffers, const int32_t batch_offset)
	Update LSTM function for an iteration step using s8 input and output, and s16 internally.

arm_cmsis_nn_status	arm_nn_vec_mat_mul_result_acc_s8_s16 (const int8_t lhs, const int8_t rhs, const int32_t effective_bias, int16_t dst, const int32_t dst_multiplier, const int32_t dst_shift, const int32_t rhs_cols, const int32_t rhs_rows, const int32_t batches, const int32_t batch_offset)
	The result of the multiplication is accumulated to the passed result buffer. Multiplies a matrix by a "batched" vector (i.e. a matrix with a batch dimension composed by input vectors independent from each other).

Description

Support functions for LSTM

Function Documentation

◆ arm_nn_lstm_calculate_gate_s16()

arm_cmsis_nn_status arm_nn_lstm_calculate_gate_s16	(	const int16_t *	data_in,
		const int16_t *	hidden_in,
		const cmsis_nn_lstm_gate *	gate_data,
		const cmsis_nn_lstm_params *	params,
		int16_t *	output,
		const int32_t	batch_offset
	)

Updates a LSTM gate for an iteration step of LSTM function, int16x8_16 version.

Parameters

[in]	data_in	Data input pointer
[in]	hidden_in	Hidden state/ recurrent input pointer
[in]	gate_data	Struct containing all information about the gate caluclation, see arm_nn_types.
[in]	params	Struct containing all information about the lstm_operation, see arm_nn_types
[out]	output	Hidden state/ recurrent output pointer
[in]	batch_offset	Number of timesteps between consecutive batches, see arm_nn_lstm_step_s16.

Returns: The function returns ARM_CMSIS_NN_SUCCESS

◆ arm_nn_lstm_calculate_gate_s8_s16()

arm_cmsis_nn_status arm_nn_lstm_calculate_gate_s8_s16	(	const int8_t *	data_in,
		const int8_t *	hidden_in,
		const cmsis_nn_lstm_gate *	gate_data,
		const cmsis_nn_lstm_params *	params,
		int16_t *	output,
		const int32_t	batch_offset
	)

Updates a LSTM gate for an iteration step of LSTM function, int8x8_16 version.

Parameters

[in]	data_in	Data input pointer
[in]	hidden_in	Hidden state/ recurrent input pointer
[in]	gate_data	Struct containing all information about the gate caluclation, see arm_nn_types.
[in]	params	Struct containing all information about the lstm_operation, see arm_nn_types
[out]	output	Hidden state/ recurrent output pointer
[in]	batch_offset	Number of timesteps between consecutive batches, see arm_nn_lstm_step_s8.

Returns: The function returns ARM_CMSIS_NN_SUCCESS

◆ arm_nn_lstm_step_f16()

arm_cmsis_nn_status arm_nn_lstm_step_f16	(	const float16_t *	data_in,
		const float16_t *	hidden_in,
		float16_t *	hidden_out,
		const cmsis_nn_lstm_params_f16 *	params,
		cmsis_nn_lstm_context_f16 *	buffers,
		const int32_t	batch_offset
	)

Update LSTM function for an iteration step using float16 input, output and state.

Parameters

[in]	data_in	Data input pointer.
[in]	hidden_in	Hidden state / recurrent input pointer. May be NULL for the first step.
[out]	hidden_out	Hidden state / recurrent output pointer.
[in]	params	Struct containing all information about the LSTM operator.
[in]	buffers	Struct containing pointers to mutable cell-state storage.
[in]	batch_offset	Number of timesteps between consecutive batches.

Returns: The function returns ARM_CMSIS_NN_SUCCESS.

◆ arm_nn_lstm_step_f32()

arm_cmsis_nn_status arm_nn_lstm_step_f32	(	const float32_t *	data_in,
		const float32_t *	hidden_in,
		float32_t *	hidden_out,
		const cmsis_nn_lstm_params_f32 *	params,
		cmsis_nn_lstm_context_f32 *	buffers,
		const int32_t	batch_offset
	)

Update LSTM function for an iteration step using float32 input, output and state.

Parameters

[in]	data_in	Data input pointer.
[in]	hidden_in	Hidden state / recurrent input pointer. May be NULL for the first step.
[out]	hidden_out	Hidden state / recurrent output pointer.
[in]	params	Struct containing all information about the LSTM operator.
[in]	buffers	Struct containing pointers to mutable cell-state storage.
[in]	batch_offset	Number of timesteps between consecutive batches.

Returns: The function returns ARM_CMSIS_NN_SUCCESS.

◆ arm_nn_lstm_step_s16()

arm_cmsis_nn_status arm_nn_lstm_step_s16	(	const int16_t *	data_in,
		const int16_t *	hidden_in,
		int16_t *	hidden_out,
		const cmsis_nn_lstm_params *	params,
		cmsis_nn_lstm_context *	buffers,
		const int32_t	batch_offset
	)

Update LSTM function for an iteration step using s16 input and output, and s16 internally.

Parameters

[in]	data_in	Data input pointer
[in]	hidden_in	Hidden state/ recurrent input pointer
[out]	hidden_out	Hidden state/ recurrent output pointer
[in]	params	Struct containg all information about the lstm operator, see arm_nn_types.
[in]	buffers	Struct containg pointers to all temporary scratch buffers needed for the lstm operator, see arm_nn_types.
[in]	batch_offset	Number of timesteps between consecutive batches. E.g for params->timing_major = true, all batches for t=0 are stored sequentially, so batch offset = 1. For params->time major = false, all time steps are stored continously before the next batch, so batch offset = params->time_steps.

Returns: The function returns ARM_CMSIS_NN_SUCCESS

◆ arm_nn_lstm_step_s8()

arm_cmsis_nn_status arm_nn_lstm_step_s8	(	const int8_t *	data_in,
		const int8_t *	hidden_in,
		int8_t *	hidden_out,
		const cmsis_nn_lstm_params *	params,
		cmsis_nn_lstm_context *	buffers,
		const int32_t	batch_offset
	)

Update LSTM function for an iteration step using s8 input and output, and s16 internally.

Parameters

[in]	data_in	Data input pointer
[in]	hidden_in	Hidden state/ recurrent input pointer
[out]	hidden_out	Hidden state/ recurrent output pointer
[in]	params	Struct containg all information about the lstm operator, see arm_nn_types.
[in]	buffers	Struct containg pointers to all temporary scratch buffers needed for the lstm operator, see arm_nn_types.
[in]	batch_offset	Number of timesteps between consecutive batches. E.g for params->timing_major = true, all batches for t=0 are stored sequentially, so batch offset = 1. For params->time major = false, all time steps are stored continously before the next batch, so batch offset = params->time_steps.

Returns: The function returns ARM_CMSIS_NN_SUCCESS

◆ arm_nn_vec_mat_mul_result_acc_s8_s16()

arm_cmsis_nn_status arm_nn_vec_mat_mul_result_acc_s8_s16	(	const int8_t *	lhs,
		const int8_t *	rhs,
		const int32_t *	effective_bias,
		int16_t *	dst,
		const int32_t	dst_multiplier,
		const int32_t	dst_shift,
		const int32_t	rhs_cols,
		const int32_t	rhs_rows,
		const int32_t	batches,
		const int32_t	batch_offset
	)

The result of the multiplication is accumulated to the passed result buffer. Multiplies a matrix by a "batched" vector (i.e. a matrix with a batch dimension composed by input vectors independent from each other).

Parameters

[in]	lhs	Batched vector
[in]	rhs	Weights - input matrix (H(Rows)xW(Columns))
[in]	effective_bias	Bias + lhs_offset * kernel_sum term precalculated into a constant vector.
[out]	dst	Output
[in]	dst_multiplier	Multiplier for quantization
[in]	dst_shift	Shift for quantization
[in]	rhs_cols	Vector/matarix column length
[in]	rhs_rows	Row count of matrix
[in]	batches	Batch size
[in]	batch_offset	Number of timesteps between consecutive batches in input, see arm_nn_lstm_step_s8. Note that the output is always stored with sequential batches.

Returns: The function returns ARM_CMSIS_NN_SUCCESS

Functions

Description

Function Documentation

◆ arm_nn_lstm_calculate_gate_s16()

◆ arm_nn_lstm_calculate_gate_s8_s16()

◆ arm_nn_lstm_step_f16()

◆ arm_nn_lstm_step_f32()

◆ arm_nn_lstm_step_s16()

◆ arm_nn_lstm_step_s8()

◆ arm_nn_vec_mat_mul_result_acc_s8_s16()