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#include "edge-impulse-sdk/classifier/ei_classifier_config.h"
#if EI_CLASSIFIER_TFLITE_LOAD_CMSIS_NN_SOURCES
/*
 * Copyright (C) 2022 Arm Limited or its affiliates.
 *
 * SPDX-License-Identifier: Apache-2.0
 *
 * Licensed under the Apache License, Version 2.0 (the License); you may
 * not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an AS IS BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/* ----------------------------------------------------------------------
 * Project:      CMSIS NN Library
 * Title:        arm_elementwise_mul_s16
 * Description:  Element wise multiplication
 *
 * $Date:        10 May 2022
 * $Revision:    V.2.1.0
 *
 * Target Processor:  Cortex-M cores
 *
 * -------------------------------------------------------------------- */

#include "edge-impulse-sdk/CMSIS/NN/Include/arm_nnfunctions.h"
#include "edge-impulse-sdk/CMSIS/NN/Include/arm_nnsupportfunctions.h"

/**
 *  @ingroup groupNN
 */

/**
 * @addtogroup BasicMath
 * @{
 */

/**
 * @brief s16 element wise multiplication of two vectors
 *
 * @note   Refer header file for details.
 *
 */
arm_cmsis_nn_status arm_elementwise_mul_s16(const int16_t *input_1_vect,
                                            const int16_t *input_2_vect,
                                            const int32_t input_1_offset,
                                            const int32_t input_2_offset,
                                            int16_t *output,
                                            const int32_t out_offset,
                                            const int32_t out_mult,
                                            const int32_t out_shift,
                                            const int32_t out_activation_min,
                                            const int32_t out_activation_max,
                                            const int32_t block_size)
{
    (void)input_1_offset;
    (void)input_2_offset;
    (void)out_offset;
    int32_t input_1;
    int32_t input_2;
    int32_t mul_res;
    int32_t two_halfword_1, two_halfword_2;
    int16_t mul_1, mul_2;
    int32_t loop_count = block_size / 2;

    while (loop_count > 0)
    {
        two_halfword_1 = arm_nn_read_q15x2_ia(&input_1_vect);
        two_halfword_2 = arm_nn_read_q15x2_ia(&input_2_vect);

        input_1 = (int16_t)(two_halfword_1 & 0xFFFF);
        input_2 = (int16_t)(two_halfword_2 & 0xFFFF);
        mul_res = input_1 * input_2;
        mul_res = arm_nn_requantize(mul_res, out_mult, out_shift);
        mul_res = MAX(mul_res, out_activation_min);
        mul_res = MIN(mul_res, out_activation_max);
        mul_1 = (int16_t)mul_res;

        input_1 = (int16_t)(two_halfword_1 >> 16);
        input_2 = (int16_t)(two_halfword_2 >> 16);
        mul_res = input_1 * input_2;
        mul_res = arm_nn_requantize(mul_res, out_mult, out_shift);
        mul_res = MAX(mul_res, out_activation_min);
        mul_res = MIN(mul_res, out_activation_max);
        mul_2 = (int16_t)mul_res;

        arm_nn_write_q15x2_ia(&output, PACK_Q15x2_32x1(mul_1, mul_2));

        loop_count--;
    }
    loop_count = block_size & 0x1;

    while (loop_count > 0)
    {
        /* C = A * B */

        input_1 = *input_1_vect++;
        input_2 = *input_2_vect++;

        mul_res = input_1 * input_2;
        mul_res = arm_nn_requantize(mul_res, out_mult, out_shift);

        mul_res = MAX(mul_res, out_activation_min);
        mul_res = MIN(mul_res, out_activation_max);

        *output++ = (int16_t)mul_res;

        /* Decrement loop counter */
        loop_count--;
    }

    return ARM_CMSIS_NN_SUCCESS;
}

/**
 * @} end of BasicMath group
 */

#endif // EI_CLASSIFIER_TFLITE_LOAD_CMSIS_NN_SOURCES

	#include "edge-impulse-sdk/classifier/ei_classifier_config.h"
	#if EI_CLASSIFIER_TFLITE_LOAD_CMSIS_NN_SOURCES
	/*
	* Copyright (C) 2022 Arm Limited or its affiliates.
	*
	* SPDX-License-Identifier: Apache-2.0
	*
	* Licensed under the Apache License, Version 2.0 (the License); you may
	* not use this file except in compliance with the License.
	* You may obtain a copy of the License at
	*
	* www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing, software
	* distributed under the License is distributed on an AS IS BASIS, WITHOUT
	* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	* See the License for the specific language governing permissions and
	* limitations under the License.
	*/

	/* ----------------------------------------------------------------------
	* Project: CMSIS NN Library
	* Title: arm_elementwise_mul_s16
	* Description: Element wise multiplication
	*
	* $Date: 10 May 2022
	* $Revision: V.2.1.0
	*
	* Target Processor: Cortex-M cores
	*
	* -------------------------------------------------------------------- */

	#include "edge-impulse-sdk/CMSIS/NN/Include/arm_nnfunctions.h"
	#include "edge-impulse-sdk/CMSIS/NN/Include/arm_nnsupportfunctions.h"

	/**
	* @ingroup groupNN
	*/

	/**
	* @addtogroup BasicMath
	* @{
	*/

	/**
	* @brief s16 element wise multiplication of two vectors
	*
	* @note Refer header file for details.
	*
	*/
	arm_cmsis_nn_status arm_elementwise_mul_s16(const int16_t *input_1_vect,
	const int16_t *input_2_vect,
	const int32_t input_1_offset,
	const int32_t input_2_offset,
	int16_t *output,
	const int32_t out_offset,
	const int32_t out_mult,
	const int32_t out_shift,
	const int32_t out_activation_min,
	const int32_t out_activation_max,
	const int32_t block_size)
	{
	(void)input_1_offset;
	(void)input_2_offset;
	(void)out_offset;
	int32_t input_1;
	int32_t input_2;
	int32_t mul_res;
	int32_t two_halfword_1, two_halfword_2;
	int16_t mul_1, mul_2;
	int32_t loop_count = block_size / 2;

	while (loop_count > 0)
	{
	two_halfword_1 = arm_nn_read_q15x2_ia(&input_1_vect);
	two_halfword_2 = arm_nn_read_q15x2_ia(&input_2_vect);

	input_1 = (int16_t)(two_halfword_1 & 0xFFFF);
	input_2 = (int16_t)(two_halfword_2 & 0xFFFF);
	mul_res = input_1 * input_2;
	mul_res = arm_nn_requantize(mul_res, out_mult, out_shift);
	mul_res = MAX(mul_res, out_activation_min);
	mul_res = MIN(mul_res, out_activation_max);
	mul_1 = (int16_t)mul_res;

	input_1 = (int16_t)(two_halfword_1 >> 16);
	input_2 = (int16_t)(two_halfword_2 >> 16);
	mul_res = input_1 * input_2;
	mul_res = arm_nn_requantize(mul_res, out_mult, out_shift);
	mul_res = MAX(mul_res, out_activation_min);
	mul_res = MIN(mul_res, out_activation_max);
	mul_2 = (int16_t)mul_res;

	arm_nn_write_q15x2_ia(&output, PACK_Q15x2_32x1(mul_1, mul_2));

	loop_count--;
	}
	loop_count = block_size & 0x1;

	while (loop_count > 0)
	{
	/* C = A * B */

	input_1 = *input_1_vect++;
	input_2 = *input_2_vect++;

	mul_res = input_1 * input_2;
	mul_res = arm_nn_requantize(mul_res, out_mult, out_shift);

	mul_res = MAX(mul_res, out_activation_min);
	mul_res = MIN(mul_res, out_activation_max);

	*output++ = (int16_t)mul_res;

	/* Decrement loop counter */
	loop_count--;
	}

	return ARM_CMSIS_NN_SUCCESS;
	}

	/**
	* @} end of BasicMath group
	*/

	#endif // EI_CLASSIFIER_TFLITE_LOAD_CMSIS_NN_SOURCES