From aa38e5c1f48e31213ee349aa5cd6f06c85bda70d Mon Sep 17 00:00:00 2001
From: android <android@lingyun.com>
Date: Tue, 25 Jun 2024 21:49:39 +0800
Subject: [PATCH] Add GD32F103RCT6 ADC converter board SDK source code
---
mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c | 101 ++++++++++++++++++++++++++++++++++++++++++++++++++
1 files changed, 101 insertions(+), 0 deletions(-)
diff --git a/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c
new file mode 100644
index 0000000..fd447e5
--- /dev/null
+++ b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c
@@ -0,0 +1,101 @@
+/*
+ * Copyright (C) 2010-2018 Arm Limited or its affiliates. All rights reserved.
+ *
+ * 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_nn_activations_q15.c
+ * Description: Q15 neural network activation function using direct table look-up
+ *
+ * $Date: 17. January 2018
+ * $Revision: V.1.0.0
+ *
+ * Target Processor: Cortex-M cores
+ *
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_common_tables.h"
+#include "arm_nnfunctions.h"
+
+/**
+ * @ingroup groupNN
+ */
+
+/**
+ * @addtogroup Acti
+ * @{
+ */
+
+ /**
+ * @brief Q15 neural network activation function using direct table look-up
+ * @param[in,out] data pointer to input
+ * @param[in] size number of elements
+ * @param[in] int_width bit-width of the integer part, assume to be smaller than 3
+ * @param[in] type type of activation functions
+ * @return none.
+ *
+ * @details
+ *
+ * This is the direct table look-up approach.
+ *
+ * Assume here the integer part of the fixed-point is <= 3.
+ * More than 3 just not making much sense, makes no difference with
+ * saturation followed by any of these activation functions.
+ */
+
+void arm_nn_activations_direct_q15(q15_t * data, uint16_t size, uint16_t int_width, arm_nn_activation_type type)
+{
+ uint16_t i = size;
+ q15_t *pIn = data;
+ q15_t *pOut = data;
+ uint16_t shift_size = 8 + 3 - int_width;
+ uint32_t bit_mask = 0x7FF >> int_width;
+ uint32_t full_frac = bit_mask + 1;
+ const q15_t *lookup_table;
+
+ switch (type)
+ {
+ case ARM_SIGMOID:
+ lookup_table = sigmoidTable_q15;
+ break;
+ case ARM_TANH:
+ default:
+ lookup_table = tanhTable_q15;
+ break;
+ }
+
+ while (i)
+ {
+ q15_t out;
+ q15_t in = *pIn++;
+ q15_t frac = (uint32_t) in & bit_mask;
+ q15_t value = lookup_table[__USAT(in >> shift_size, 8)];
+ q15_t value2 = lookup_table[__USAT(1 + (in >> shift_size), 8)];
+
+ /* doing the interpolation here for better accuracy */
+ out = ((q31_t) (full_frac - frac) * value + (q31_t) value2 * frac) >> shift_size;
+
+ *pOut++ = out;
+ i--;
+ }
+
+}
+
+/**
+ * @} end of Acti group
+ */
--
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