1 files changed, 0 insertions, 121 deletions
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c b/hid-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c
deleted file mode 100644
index 06a69e1..0000000
--- a/hid-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c
+++ /dev/null
@@ -1,121 +0,0 @@
-/*
- * 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_softmax_q7.c
- * Description:  Q7 softmax function
- *
- * $Date:        20. February 2018
- * $Revision:    V.1.0.0
- *
- * Target Processor:  Cortex-M cores
- *
- * -------------------------------------------------------------------- */
-
-#include "arm_math.h"
-#include "arm_nnfunctions.h"
-
-/**
- *  @ingroup groupNN
- */
-
-/**
- * @addtogroup Softmax
- * @{
- */
-
-  /**
-   * @brief Q7 softmax function
-   * @param[in]       vec_in      pointer to input vector
-   * @param[in]       dim_vec     input vector dimention
-   * @param[out]      p_out       pointer to output vector
-   * @return none.
-   *
-   * @details
-   *
-   *  Here, instead of typical natural logarithm e based softmax, we use
-   *  2-based softmax here, i.e.,:
-   * 
-   *  y_i = 2^(x_i) / sum(2^x_j)
-   *
-   *  The relative output will be different here.
-   *  But mathematically, the gradient will be the same
-   *  with a log(2) scaling factor.
-   *
-   */
-
-void arm_softmax_q7(const q7_t * vec_in, const uint16_t dim_vec, q7_t * p_out)
-{
-    q31_t     sum;
-    int16_t   i;
-    uint8_t   shift;
-    q15_t     base;
-    base = -257;
-
-    /* We first search for the maximum */
-    for (i = 0; i < dim_vec; i++)
-    {
-        if (vec_in[i] > base)
-        {
-            base = vec_in[i];
-        }
-    }
-
-    /* 
-     * So the base is set to max-8, meaning 
-     * that we ignore really small values. 
-     * anyway, they will be 0 after shrinking to q7_t.
-     */
-    base = base - 8;
-
-    sum = 0;
-
-    for (i = 0; i < dim_vec; i++)
-    {
-        if (vec_in[i] > base) 
-        {
-            shift = (uint8_t)__USAT(vec_in[i] - base, 5);
-            sum += 0x1 << shift;
-        }
-    }
-
-    /* This is effectively (0x1 << 20) / sum */
-    int output_base = 0x100000 / sum;
-
-    /* 
-     * Final confidence will be output_base >> ( 13 - (vec_in[i] - base) )
-     * so 128 (0x1<<7) -> 100% confidence when sum = 0x1 << 8, output_base = 0x1 << 12 
-     * and vec_in[i]-base = 8
-     */
-    for (i = 0; i < dim_vec; i++) 
-    {
-        if (vec_in[i] > base) 
-        {
-            /* Here minimum value of 13+base-vec_in[i] will be 5 */
-            shift = (uint8_t)__USAT(13+base-vec_in[i], 5);
-            p_out[i] = (q7_t) __SSAT((output_base >> shift), 8);
-        } else {
-            p_out[i] = 0;
-        }
-    }
-}
-
-/**
- * @} end of Softmax group
- */