Submodule-cache WIP

2 files changed, 0 insertions, 241 deletions

diff --git a/fw/midi-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c b/fw/midi-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c
deleted file mode 100644
index 22fa62b..0000000
--- a/fw/midi-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c
+++ /dev/null
@@ -1,120 +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_q15.c

- * Description:  Q15 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 Q15 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 e based softmax, we use

-   *  2-based softmax, 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_q15(const q15_t * vec_in, const uint16_t dim_vec, q15_t * p_out)

-{

-    q31_t     sum;

-    int16_t   i;

-    uint8_t   shift;

-    q31_t     base;

-    base = -1 * 0x100000;

-    for (i = 0; i < dim_vec; i++)

-    {

-        if (vec_in[i] > base)

-        {

-            base = vec_in[i];

-        }

-    }

-

-    /* we ignore really small values  

-     * anyway, they will be 0 after shrinking

-     * to q15_t

-     */

-    base = base - 16;

-

-    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 << 32) / sum */

-    int64_t div_base = 0x100000000LL;

-    int output_base = (int32_t)(div_base / sum);

-

-    /* Final confidence will be output_base >> ( 17 - (vec_in[i] - base) )

-     * so 32768 (0x1<<15) -> 100% confidence when sum = 0x1 << 16, output_base = 0x1 << 16

-     * and vec_in[i]-base = 16

-     */

-    for (i = 0; i < dim_vec; i++)

-    {

-        if (vec_in[i] > base) 

-        {

-            /* Here minimum value of 17+base-vec[i] will be 1 */

-            shift = (uint8_t)__USAT(17+base-vec_in[i], 5);

-            p_out[i] = (q15_t) __SSAT((output_base >> shift), 16);

-        } else

-        {

-            p_out[i] = 0;

-        }

-    }

-

-}

-

-/**

- * @} end of Softmax group

- */

diff --git a/fw/midi-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c b/fw/midi-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c
deleted file mode 100644
index 06a69e1..0000000
--- a/fw/midi-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

- */