From a81fc41c3eb99e8fc52aa734ee63e13c937aab81 Mon Sep 17 00:00:00 2001
From: JanHenrik <janhenrik@janhenrik.org>
Date: Sun, 19 Jan 2020 00:56:37 +0100
Subject: added blink example

---
 .../ActivationFunctions/arm_nn_activations_q15.c   | 101 +++++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 Blink/Drivers/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c

(limited to 'Blink/Drivers/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c')

diff --git a/Blink/Drivers/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c b/Blink/Drivers/CMSIS/NN/Source/ActivationFunctions/arm_nn_activations_q15.c
new file mode 100644
index 0000000..fd447e5
--- /dev/null
+++ b/Blink/Drivers/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
+ */
-- 
cgit