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Change-Id: Ia026c3f0f0d016627a4fb5a9032852c33d24b4d3

6 files changed, 1809 insertions, 0 deletions

diff --git a/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15.c b/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15.c
new file mode 100644
index 0000000..2746967
--- /dev/null
+++ b/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15.c
@@ -0,0 +1,199 @@
+/*
+ * 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_fully_connected_mat_q7_vec_q15.c
+ * Description:  Mixed Q15-Q7 fully-connected layer function
+ *
+ * $Date:        17. January 2018
+ * $Revision:    V.1.0.0
+ *
+ * Target Processor:  Cortex-M cores
+ *
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_nnfunctions.h"
+
+/**
+ *  @ingroup groupNN
+ */
+
+/**
+ * @addtogroup FC
+ * @{
+ */
+
+  /**
+   * @brief Mixed Q15-Q7 fully-connected layer function
+   * @param[in]       pV          pointer to input vector
+   * @param[in]       pM          pointer to matrix weights
+   * @param[in]       dim_vec     length of the vector
+   * @param[in]       num_of_rows number of rows in weight matrix
+   * @param[in]       bias_shift  amount of left-shift for bias
+   * @param[in]       out_shift   amount of right-shift for output
+   * @param[in]       bias        pointer to bias
+   * @param[in,out]   pOut        pointer to output vector
+   * @param[in,out]   vec_buffer  pointer to buffer space for input
+   * @return     The function returns <code>ARM_MATH_SUCCESS</code>
+   *
+   * @details
+   *
+   * <b>Buffer size:</b>
+   *
+   * vec_buffer size: 0
+   *
+   *  Q7_Q15 version of the fully connected layer
+   *
+   *  Weights are in q7_t and Activations are in q15_t
+   *
+   */
+
+arm_status
+arm_fully_connected_mat_q7_vec_q15(const q15_t * pV,
+                                   const q7_t * pM,
+                                   const uint16_t dim_vec,
+                                   const uint16_t num_of_rows,
+                                   const uint16_t bias_shift,
+                                   const uint16_t out_shift, 
+                                   const q7_t * bias, 
+                                   q15_t * pOut, 
+                                   q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+    /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+    const q7_t *pB = pM;
+    const q7_t *pB2;
+    q15_t    *pO = pOut;
+    const q7_t *pBias = bias;
+    const q15_t *pA = pV;
+
+    uint16_t  rowCnt = num_of_rows >> 1;
+
+    while (rowCnt)
+    {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = pV;
+        pB2 = pB + dim_vec;
+
+        while (colCnt)
+        {
+            q31_t     inV, inM11, inM12, inM21, inM22;
+            pB = (q7_t *) read_and_pad((void *)pB, &inM11, &inM12);
+            pB2 = (q7_t *) read_and_pad((void *)pB2, &inM21, &inM22);
+
+            inV = *__SIMD32(pA)++;
+
+            sum = __SMLAD(inV, inM11, sum);
+            sum2 = __SMLAD(inV, inM21, sum2);
+
+            inV = *__SIMD32(pA)++;
+
+            sum = __SMLAD(inV, inM12, sum);
+            sum2 = __SMLAD(inV, inM22, sum2);
+
+            colCnt--;
+        }
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q7_t      inM = *pB++;
+            q7_t      inM2 = *pB2++;
+
+            sum += inV * inM;
+            sum2 += inV * inM2;
+            colCnt--;
+        }                       /* while over colCnt */
+        *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum2 >> out_shift), 16));
+
+        /*adjust the pointers and counters */
+        pB += dim_vec;
+        rowCnt--;
+    }
+
+    /* left-over part of the rows */
+    rowCnt = num_of_rows & 0x1;
+
+    while (rowCnt)
+    {
+        q31_t     sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = pV;
+
+        while (colCnt)
+        {
+            q31_t     inV1, inV2, inM11, inM12;
+
+            pB = (q7_t *) read_and_pad((void *)pB, &inM11, &inM12);
+
+            inV1 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV1, inM11, sum);
+
+            inV2 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV2, inM12, sum);
+
+            colCnt--;
+        }
+
+        /* left-over of the vector */
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q7_t      inM = *pB++;
+            sum += inV * inM;
+            colCnt--;
+        }
+
+        *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
+
+        rowCnt--;
+    }
+
+#else
+    int       i, j;
+    /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+    for (i = 0; i < num_of_rows; i++)
+    {
+        int       ip_out = ((q31_t)(bias[i]) << bias_shift) + NN_ROUND(out_shift);
+        for (j = 0; j < dim_vec; j++)
+        {
+            ip_out += pV[j] * pM[i * dim_vec + j];
+        }
+        pOut[i] = (q15_t) __SSAT((ip_out >> out_shift), 16);
+    }
+
+#endif                          /* ARM_MATH_DSP */
+
+    /* Return to ARM_MATH_SUCCESS */
+    return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
diff --git a/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15_opt.c b/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15_opt.c
new file mode 100644
index 0000000..7be156f
--- /dev/null
+++ b/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15_opt.c
@@ -0,0 +1,403 @@
+/*
+ * 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_fully_connected_mat_q7_vec_q15_opt.c
+ * Description:  Mixed Q15-Q7 opt fully-connected layer function
+ *
+ * $Date:        17. January 2018
+ * $Revision:    V.1.0.0
+ *
+ * Target Processor:  Cortex-M cores
+ *
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_nnfunctions.h"
+
+/**
+ *  @ingroup groupNN
+ */
+
+/**
+ * @addtogroup FC
+ * @{
+ */
+
+  /**
+   * @brief Mixed Q15-Q7 opt fully-connected layer function
+   * @param[in]       pV          pointer to input vector
+   * @param[in]       pM          pointer to matrix weights
+   * @param[in]       dim_vec     length of the vector
+   * @param[in]       num_of_rows number of rows in weight matrix
+   * @param[in]       bias_shift  amount of left-shift for bias
+   * @param[in]       out_shift   amount of right-shift for output
+   * @param[in]       bias        pointer to bias
+   * @param[in,out]   pOut        pointer to output vector
+   * @param[in,out]   vec_buffer  pointer to buffer space for input
+   * @return     The function returns <code>ARM_MATH_SUCCESS</code>
+   *
+   * @details
+   *
+   * <b>Buffer size:</b>
+   *
+   * vec_buffer size: 0
+   *
+   *  Q7_Q15 version of the fully connected layer
+   *
+   *  Weights are in q7_t and Activations are in q15_t
+   *
+   *  Limitation: x4 version requires weight reordering to work
+   *
+   *  Here we use only one pointer to read 4 rows in the weight
+   *  matrix. So if the original q7_t matrix looks like this:
+   *
+   *  | a11 | a12 | a13 | a14 | a15 | a16 | a17 |
+   *
+   *  | a21 | a22 | a23 | a24 | a25 | a26 | a27 |
+   *
+   *  | a31 | a32 | a33 | a34 | a35 | a36 | a37 |
+   *
+   *  | a41 | a42 | a43 | a44 | a45 | a46 | a47 |
+   *
+   *  | a51 | a52 | a53 | a54 | a55 | a56 | a57 |
+   *
+   *  | a61 | a62 | a63 | a64 | a65 | a66 | a67 |
+   *
+   *  We operates on multiple-of-4 rows, so the first four rows becomes
+   *
+   *  | a11 | a21 | a12 | a22 | a31 | a41 | a32 | a42 |
+   *
+   *  | a13 | a23 | a14 | a24 | a33 | a43 | a34 | a44 |
+   *
+   *  | a15 | a25 | a16 | a26 | a35 | a45 | a36 | a46 |
+   *
+   *  The column left over will be in-order.
+   *  which is:
+   *  | a17 | a27 | a37 | a47 |
+   *
+   *  For the left-over rows, we do 1x1 computation, so the data remains
+   *  as its original order. 
+   *
+   *  So the stored weight matrix looks like this:
+   *
+   *  | a11 | a21 | a12 | a22 | a31 | a41 |
+   *
+   *  | a32 | a42 | a13 | a23 | a14 | a24 |
+   *
+   *  | a33 | a43 | a34 | a44 | a15 | a25 |
+   *
+   *  | a16 | a26 | a35 | a45 | a36 | a46 |
+   *
+   *  | a17 | a27 | a37 | a47 | a51 | a52 |
+   *
+   *  | a53 | a54 | a55 | a56 | a57 | a61 |
+   *
+   *  | a62 | a63 | a64 | a65 | a66 | a67 |
+   *
+   */
+
+arm_status
+arm_fully_connected_mat_q7_vec_q15_opt(const q15_t * pV,
+                                       const q7_t * pM,
+                                       const uint16_t dim_vec,
+                                       const uint16_t num_of_rows,
+                                       const uint16_t bias_shift,
+                                       const uint16_t out_shift, const q7_t * bias, q15_t * pOut, q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+    /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+    const q7_t *pB = pM;
+    q15_t    *pO = pOut;
+    const q7_t *pBias = bias;
+    const q15_t *pA = pV;
+
+    uint16_t  rowCnt = num_of_rows >> 2;
+
+    while (rowCnt)
+    {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 1;
+
+        pA = pV;
+
+#ifdef USE_INTRINSIC
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        while (colCnt)
+        {
+            q31_t     inM11, inM12, inM13, inM14;
+            q31_t     inV;
+
+            inV = *__SIMD32(pA)++;
+            inM11 = *__SIMD32(pB)++;
+            inM12 = __SXTB16(__ROR(inM11, 8));
+            inM11 = __SXTB16(inM11);
+            sum = __SMLAD(inM11, inV, sum);
+            sum2 = __SMLAD(inM12, inV, sum2);
+            inM13 = *__SIMD32(pB)++;
+            inM14 = __SXTB16(__ROR(inM13, 8));
+            inM13 = __SXTB16(inM13);
+            sum3 = __SMLAD(inM13, inV, sum3);
+            sum4 = __SMLAD(inM14, inV, sum4);
+            colCnt--;
+        }
+
+#else
+
+        while (colCnt)
+        {
+            q31_t     inM11, inM12, inM13, inM14;
+            q31_t     inV;
+
+            inV = *__SIMD32(pA)++;
+            inM11 = *__SIMD32(pB)++;
+            inM12 = __SXTB16(__ROR(inM11, 8));
+            inM11 = __SXTB16(inM11);
+            sum = __SMLAD(inM12, inV, sum);
+            sum2 = __SMLAD(inM11, inV, sum2);
+            inM13 = *__SIMD32(pB)++;
+            inM14 = __SXTB16(__ROR(inM13, 8));
+            inM13 = __SXTB16(inM13);
+            sum3 = __SMLAD(inM14, inV, sum3);
+            sum4 = __SMLAD(inM13, inV, sum4);
+            colCnt--;
+        }
+
+#endif                          /* ARM_MATH_BIG_ENDIAN */
+
+#else
+
+        /*
+         * register needed:
+         * loop counter: colCnt
+         * accumulators: sum, sum2, sum3, sum4
+         * pointers: pB, pA
+         * weight data: inM11, inM12, inM13, inM14
+         * activation data: inV
+         */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+        asm volatile ("COL_LOOP_%=:\n"
+                      "ldr.w r4, [%[pA]], #4\n"
+                      "ldr.w r1, [%[pB]], #8\n"
+                      "mov.w r0, r1, ror #8\n"
+                      "sxtb16 r0, r0\n"
+                      "sxtb16 r1, r1\n"
+                      "smlad %[sum], r4, r1, %[sum]\n"
+                      "smlad %[sum2], r4, r0, %[sum2]\n"
+                      "ldr.w r3, [%[pB], #-4]\n"
+                      "mov.w r2, r3, ror #8\n"
+                      "sxtb16 r2, r2\n"
+                      "sxtb16 r3, r3\n"
+                      "smlad %[sum3], r4, r3, %[sum3]\n"
+                      "smlad %[sum4], r4, r2, %[sum4]\n"
+                      "subs %[colCnt], #1\n"
+                      "bne COL_LOOP_%=\n":[sum] "+r"(sum),
+                      [sum2] "+r"(sum2),[sum3] "+r"(sum3),
+                      [sum4] "+r"(sum4),[pB] "+r"(pB),[pA] "+r"(pA):[colCnt] "r"(colCnt):"r0", "r1", "r2", "r3", "r4");
+#else
+        asm volatile ("COL_LOOP_%=:\n"
+                      "ldr.w r4, [%[pA]], #4\n"
+                      "ldr.w r1, [%[pB]], #8\n"
+                      "mov.w r0, r1, ror #8\n"
+                      "sxtb16 r0, r0\n"
+                      "sxtb16 r1, r1\n"
+                      "smlad %[sum], r4, r0, %[sum]\n"
+                      "smlad %[sum2], r4, r1, %[sum2]\n"
+                      "ldr.w r3, [%[pB], #-4]\n"
+                      "mov.w r2, r3, ror #8\n"
+                      "sxtb16 r2, r2\n"
+                      "sxtb16 r3, r3\n"
+                      "smlad %[sum3], r4, r2, %[sum3]\n"
+                      "smlad %[sum4], r4, r3, %[sum4]\n"
+                      "subs %[colCnt], #1\n"
+                      "bne COL_LOOP_%=\n":[sum] "+r"(sum),
+                      [sum2] "+r"(sum2),[sum3] "+r"(sum3),
+                      [sum4] "+r"(sum4),[pB] "+r"(pB),[pA] "+r"(pA):[colCnt] "r"(colCnt):"r0", "r1", "r2", "r3", "r4");
+#endif                          /* ARM_MATH_BIG_ENDIAN */
+
+#endif                          /* USE_INTRINSIC */
+
+        colCnt = dim_vec & 0x1;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q7_t      inM = *pB++;
+            q7_t      inM2 = *pB++;
+            q7_t      inM3 = *pB++;
+            q7_t      inM4 = *pB++;
+
+            sum += inV * inM;
+            sum2 += inV * inM2;
+            sum3 += inV * inM3;
+            sum4 += inV * inM4;
+            colCnt--;
+        }                       /* while over colCnt */
+        *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum2 >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum3 >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum4 >> out_shift), 16));
+
+        /* adjust the pointers and counters */
+        rowCnt--;
+    }
+
+    /* left-over part of the rows */
+    rowCnt = num_of_rows & 0x3;
+
+    while (rowCnt)
+    {
+        q31_t     sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = pV;
+
+        while (colCnt)
+        {
+            q31_t     inV1, inV2, inM11, inM12;
+
+            pB = (q7_t *) read_and_pad((void *)pB, &inM11, &inM12);
+
+            inV1 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV1, inM11, sum);
+
+            inV2 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV2, inM12, sum);
+
+            colCnt--;
+        }
+
+        /* left-over of the vector */
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q7_t      inM = *pB++;
+            sum += inV * inM;
+            colCnt--;
+        }
+
+        *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
+
+        rowCnt--;
+    }
+
+#else
+    /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+    uint16_t  rowCnt = num_of_rows >> 2;
+    const q7_t *pB = pM;
+    const q15_t *pA;
+    q15_t    *pO = pOut;
+    const q7_t *pBias = bias;
+
+    while (rowCnt)
+    {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift); 
+        q31_t     sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift); 
+        uint16_t  colCnt = dim_vec >> 1;
+
+        pA = pV;
+
+        while (colCnt)
+        {
+            q15_t     inA1 = *pA++;
+            q15_t     inA2 = *pA++;
+
+            q7_t      inB1 = *pB++;
+            q7_t      inB3 = *pB++;
+            q7_t      inB2 = *pB++;
+            q7_t      inB4 = *pB++;
+
+            sum += inA1 * inB1 + inA2 * inB2;
+            sum2 += inA1 * inB3 + inA2 * inB4;
+
+            inB1 = *pB++;
+            inB3 = *pB++;
+            inB2 = *pB++;
+            inB4 = *pB++;
+
+            sum3 += inA1 * inB1 + inA2 * inB2;
+            sum4 += inA1 * inB3 + inA2 * inB4;
+
+            colCnt--;
+        }
+
+        colCnt = dim_vec & 0x1;
+        while (colCnt)
+        {
+            q15_t     inA = *pA++;
+            q7_t      inB = *pB++;
+            sum += inA * inB;
+            inB = *pB++;
+            sum2 += inA * inB;
+            inB = *pB++;
+            sum3 += inA * inB;
+            inB = *pB++;
+            sum4 += inA * inB;
+
+            colCnt--;
+        }
+        *pO++ = (q15_t) __SSAT((sum >> out_shift), 16);
+        *pO++ = (q15_t) __SSAT((sum2 >> out_shift), 16);
+        *pO++ = (q15_t) __SSAT((sum3 >> out_shift), 16);
+        *pO++ = (q15_t) __SSAT((sum4 >> out_shift), 16);
+
+        rowCnt--;
+    }
+
+    rowCnt = num_of_rows & 0x3;
+
+    while (rowCnt)
+    {
+        int       ip_out = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        int       j;
+
+        pA = pV;
+        for (j = 0; j < dim_vec; j++)
+        {
+            q15_t     inA = *pA++;
+            q7_t      inB = *pB++;
+            ip_out += inA * inB;
+        }
+        *pO++ = (q15_t) __SSAT((ip_out >> out_shift), 16);
+
+        rowCnt--;
+    }
+
+#endif                          /* ARM_MATH_DSP */
+
+    /* Return to ARM_MATH_SUCCESS */
+    return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
diff --git a/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c
new file mode 100644
index 0000000..c3e7cf2
--- /dev/null
+++ b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c
@@ -0,0 +1,193 @@
+/*
+ * 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_fully_connected_q15.c
+ * Description:  Q15 basic fully-connected layer function
+ *
+ * $Date:        17. January 2018
+ * $Revision:    V.1.0.0
+ *
+ * Target Processor:  Cortex-M cores
+ *
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_nnfunctions.h"
+
+/**
+ *  @ingroup groupNN
+ */
+
+/**
+ * @addtogroup FC
+ * @{
+ */
+
+  /**
+   * @brief Q15 opt fully-connected layer function
+   * @param[in]       pV          pointer to input vector
+   * @param[in]       pM          pointer to matrix weights
+   * @param[in]       dim_vec     length of the vector
+   * @param[in]       num_of_rows number of rows in weight matrix
+   * @param[in]       bias_shift  amount of left-shift for bias
+   * @param[in]       out_shift   amount of right-shift for output
+   * @param[in]       bias        pointer to bias
+   * @param[in,out]   pOut        pointer to output vector
+   * @param[in,out]   vec_buffer  pointer to buffer space for input
+   * @return     The function returns <code>ARM_MATH_SUCCESS</code>
+   *
+   *
+   * @details
+   *
+   * <b>Buffer size:</b>
+   *
+   * vec_buffer size: 0
+   *
+   */
+
+arm_status
+arm_fully_connected_q15(const q15_t * pV,
+                        const q15_t * pM,
+                        const uint16_t dim_vec,
+                        const uint16_t num_of_rows,
+                        const uint16_t bias_shift,
+                        const uint16_t out_shift, 
+                        const q15_t * bias, 
+                        q15_t * pOut,
+                        q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+    /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+    const q15_t *pB = pM;
+    const q15_t *pB2 = pB + dim_vec;
+    q15_t    *pO = pOut;
+    const q15_t    *pA;
+    const q15_t    *pBias = bias;
+    uint16_t rowCnt = num_of_rows >> 1;
+
+    /* this loop loops over different output */
+    while (rowCnt) {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = pV;
+        pB2 = pB + dim_vec;
+
+        while (colCnt)
+        {
+            q31_t     inV1, inM1, inM2;
+            inV1 = *__SIMD32(pA)++;
+            inM1 = *__SIMD32(pB)++;
+            sum = __SMLAD(inV1, inM1, sum);
+            inM2 = *__SIMD32(pB2)++;
+            sum2 = __SMLAD(inV1, inM2, sum2);
+
+            inV1 = *__SIMD32(pA)++;
+            inM1 = *__SIMD32(pB)++;
+            sum = __SMLAD(inV1, inM1, sum);
+            inM2 = *__SIMD32(pB2)++;
+            sum2 = __SMLAD(inV1, inM2, sum2);
+
+            colCnt--;
+        }
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q15_t     inM = *pB++;
+            q15_t     inM2 = *pB2++;
+
+            sum += inV * inM;
+            sum2 += inV * inM2;
+            colCnt--;
+        }                       /* while over colCnt */
+        *pO++ =  (q15_t) (__SSAT((sum >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum2>> out_shift), 16));
+		
+        /* adjust the pointers and counters */
+        pB = pB + dim_vec;
+        rowCnt --;
+    }
+
+    rowCnt = num_of_rows & 0x1;
+
+    while (rowCnt) {
+        q31_t     sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = pV;
+      
+        while (colCnt) {
+            q31_t     inV1, inM1;
+            inV1 = *__SIMD32(pA)++;
+            inM1 = *__SIMD32(pB)++;
+            sum = __SMLAD(inV1, inM1, sum);
+            
+            inV1 = *__SIMD32(pA)++;
+            inM1 = *__SIMD32(pB)++;
+            sum = __SMLAD(inV1, inM1, sum);
+				
+            colCnt--;
+	}
+			
+	/* left-over of the vector */
+	colCnt = dim_vec & 0x3;
+	while(colCnt) {
+            q15_t     inV = *pA++;
+            q15_t     inM = *pB++;
+
+            sum += inV * inM;
+
+            colCnt--;
+	}
+
+        *pO++ =  (q15_t) (__SSAT((sum >> out_shift), 16));
+			
+        rowCnt --;
+    }
+
+#else
+    int       i, j;
+    /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+    for (i = 0; i < num_of_rows; i++)
+    {
+        int       ip_out = ((q31_t)(bias[i]) << bias_shift) + NN_ROUND(out_shift);
+        for (j = 0; j < dim_vec; j++)
+        {
+            ip_out += pV[j] * pM[i * dim_vec + j];
+        }
+        pOut[i] = (q15_t) __SSAT((ip_out >> out_shift), 16);
+    }
+
+#endif                          /* ARM_MATH_DSP */
+
+    /* Return to application */
+    return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
diff --git a/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c
new file mode 100644
index 0000000..f7a3915
--- /dev/null
+++ b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c
@@ -0,0 +1,332 @@
+/*
+ * 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_fully_connected_q15_opt.c
+ * Description:  Q15 opt fully-connected layer function
+ *
+ * $Date:        17. January 2018
+ * $Revision:    V.1.0.0
+ *
+ * Target Processor:  Cortex-M cores
+ *
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_nnfunctions.h"
+
+/**
+ *  @ingroup groupNN
+ */
+
+/**
+ * @addtogroup FC
+ * @{
+ */
+
+  /**
+   * @brief Q15 opt fully-connected layer function
+   * @param[in]       pV          pointer to input vector
+   * @param[in]       pM          pointer to matrix weights
+   * @param[in]       dim_vec     length of the vector
+   * @param[in]       num_of_rows number of rows in weight matrix
+   * @param[in]       bias_shift  amount of left-shift for bias
+   * @param[in]       out_shift   amount of right-shift for output
+   * @param[in]       bias        pointer to bias
+   * @param[in,out]   pOut        pointer to output vector
+   * @param[in,out]   vec_buffer  pointer to buffer space for input
+   * @return     The function returns <code>ARM_MATH_SUCCESS</code>
+   *
+   *
+   * @details
+   *
+   * <b>Buffer size:</b>
+   *
+   * vec_buffer size: 0
+   *
+   *  Here we use only one pointer to read 4 rows in the weight
+   *  matrix. So if the original matrix looks like this:
+   *
+   *  | a11 | a12 | a13 |
+   *
+   *  | a21 | a22 | a23 |
+   *
+   *  | a31 | a32 | a33 |
+   *
+   *  | a41 | a42 | a43 |
+   *
+   *  | a51 | a52 | a53 |
+   *
+   *  | a61 | a62 | a63 |
+   *
+   *  We operates on multiple-of-4 rows, so the first four rows becomes
+   *
+   *  | a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
+   *
+   *  | a13 | a23 | a33 | a43 |
+   *
+   *  Remaining rows are kept the same original order.
+   *
+   *  So the stored weight matrix looks like this:
+   *
+   *
+   *  | a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
+   *
+   *  | a13 | a23 | a33 | a43 | a51 | a52 | a53 | a61 |
+   *
+   *  | a62 | a63 |
+   */
+
+arm_status
+arm_fully_connected_q15_opt(const q15_t * pV,
+                            const q15_t * pM,
+                            const uint16_t dim_vec,
+                            const uint16_t num_of_rows,
+                            const uint16_t bias_shift,
+                            const uint16_t out_shift, 
+                            const q15_t * bias, 
+                            q15_t * pOut, 
+                            q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+    /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+    const q15_t *pB = pM;
+    q15_t    *pO = pOut;
+    const q15_t *pBias = bias;
+    const q15_t *pA = pV;
+
+    uint16_t  rowCnt = num_of_rows >> 2;
+
+    while (rowCnt)
+    {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift); 
+        q31_t     sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift); 
+        q31_t     sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift); 
+
+        uint16_t  colCnt = dim_vec >> 1;
+
+        pA = pV;
+
+#ifdef USE_INTRINSIC
+
+        while (colCnt)
+        {
+            q31_t     inM11, inM12, inM13, inM14;
+            q31_t     inV;
+
+            inV = *__SIMD32(pA)++;
+            inM11 = *__SIMD32(pB)++;
+            sum = __SMLAD(inV, inM11, sum);
+            inM12 = *__SIMD32(pB)++;
+            sum2 = __SMLAD(inV, inM12, sum2);
+            inM13 = *__SIMD32(pB)++;
+            sum3 = __SMLAD(inV, inM13, sum3);
+            inM14 = *__SIMD32(pB)++;
+            sum4 = __SMLAD(inV, inM14, sum4);
+            colCnt--;
+        }
+
+#else
+
+        /*
+         * register needed:
+         * loop counter: colCnt
+         * accumulators: sum, sum2, sum3, sum4
+         * pointers: pB, pA
+         * weight data: inM11, inM12, inM13, inM14
+         * activation data: inV
+         */
+
+        asm volatile ("COL_LOOP_%=:\n"
+                      "ldr.w r4, [%[pA]], #4\n"
+                      "ldr.w r0, [%[pB]], #16\n"
+                      "smlad %[sum], r4, r0, %[sum]\n"
+                      "ldr.w r1, [%[pB] , #-12]\n"
+                      "smlad %[sum2], r4, r1, %[sum2]\n"
+                      "ldr.w r2, [%[pB] , #-8]\n"
+                      "smlad %[sum3], r4, r2, %[sum3]\n"
+                      "ldr.w r3, [%[pB] , #-4]\n"
+                      "smlad %[sum4], r4, r3, %[sum4]\n"
+                      "subs %[colCnt], #1\n"
+                      "bne COL_LOOP_%=\n":[sum] "+r"(sum),
+                      [sum2] "+r"(sum2),[sum3] "+r"(sum3),
+                      [sum4] "+r"(sum4),[pB] "+r"(pB),[pA] "+r"(pA):[colCnt] "r"(colCnt):"r0", "r1", "r2", "r3", "r4");
+
+#endif                          /* USE_INTRINSIC */
+
+        colCnt = dim_vec & 0x1;
+        while (colCnt)
+        {
+
+            q15_t     inV = *pA++;
+            q15_t     inM = *pB++;
+            q15_t     inM2 = *pB++;
+            q15_t     inM3 = *pB++;
+            q15_t     inM4 = *pB++;
+
+            sum += inV * inM;
+            sum2 += inV * inM2;
+            sum3 += inV * inM3;
+            sum4 += inV * inM4;
+            colCnt--;
+        }                       /* while over colCnt */
+        *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum2 >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum3 >> out_shift), 16));
+        *pO++ = (q15_t) (__SSAT((sum4 >> out_shift), 16));
+
+        /* adjust the pointers and counters */
+        rowCnt--;
+    }
+
+    /* left-over part of the rows */
+    rowCnt = num_of_rows & 0x3;
+
+    while (rowCnt)
+    {
+        q31_t     sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = pV;
+
+        while (colCnt)
+        {
+            q31_t     inV1, inV2, inM1, inM2;
+
+            inM1 = *__SIMD32(pB)++;
+            inV1 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV1, inM1, sum);
+
+            inM2 = *__SIMD32(pB)++;
+            inV2 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV2, inM2, sum);
+
+            colCnt--;
+        }
+
+        /* left-over of the vector */
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q15_t     inM = *pB++;
+            sum += inV * inM;
+            colCnt--;
+        }
+
+        *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
+
+        rowCnt--;
+    }
+
+#else
+    /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+    uint16_t  rowCnt = num_of_rows >> 2;
+    const q15_t *pB = pM;
+    const q15_t *pA;
+    q15_t    *pO = pOut;
+    const q15_t *pBias = bias;
+
+    while (rowCnt)
+    {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 1;
+
+        pA = pV;
+        while (colCnt)
+        {
+            q15_t     inA1 = *pA++;
+            q15_t     inA2 = *pA++;
+
+            q15_t     inB1 = *pB++;
+            q15_t     inB2 = *pB++;
+            sum += inA1 * inB1 + inA2 * inB2;
+
+            inB1 = *pB++;
+            inB2 = *pB++;
+            sum2 += inA1 * inB1 + inA2 * inB2;
+
+            inB1 = *pB++;
+            inB2 = *pB++;
+            sum3 += inA1 * inB1 + inA2 * inB2;
+
+            inB1 = *pB++;
+            inB2 = *pB++;
+            sum4 += inA1 * inB1 + inA2 * inB2;
+
+            colCnt--;
+        }
+        colCnt = dim_vec & 0x1;
+        while (colCnt)
+        {
+            q15_t     inA = *pA++;
+            q15_t     inB = *pB++;
+            sum += inA * inB;
+            inB = *pB++;
+            sum2 += inA * inB;
+            inB = *pB++;
+            sum3 += inA * inB;
+            inB = *pB++;
+            sum4 += inA * inB;
+            colCnt--;
+        }
+        *pO++ = (q15_t) __SSAT((sum >> out_shift), 16);
+        *pO++ = (q15_t) __SSAT((sum2 >> out_shift), 16);
+        *pO++ = (q15_t) __SSAT((sum3 >> out_shift), 16);
+        *pO++ = (q15_t) __SSAT((sum4 >> out_shift), 16);
+
+        rowCnt--;
+    }
+    rowCnt = num_of_rows & 0x3;
+
+    while (rowCnt)
+    {
+        int       ip_out = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        int       j;
+
+        pA = pV;
+        for (j = 0; j < dim_vec; j++)
+        {
+            q15_t     inA = *pA++;
+            q15_t     inB = *pB++;
+            ip_out += inA * inB;
+        }
+        *pO++ = (q15_t) __SSAT((ip_out >> out_shift), 16);
+
+        rowCnt--;
+    }
+
+#endif                          /* ARM_MATH_DSP */
+
+    /* Return to ARM_MATH_SUCCESS */
+    return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
diff --git a/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7.c b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7.c
new file mode 100644
index 0000000..d8efc04
--- /dev/null
+++ b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7.c
@@ -0,0 +1,198 @@
+/*
+ * 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_fully_connected_q7.c
+ * Description:  Q7 basic fully-connected layer function
+ *
+ * $Date:        17. January 2018
+ * $Revision:    V.1.0.0
+ *
+ * Target Processor:  Cortex-M cores
+ *
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_nnfunctions.h"
+
+/**
+ *  @ingroup groupNN
+ */
+
+/**
+ * @addtogroup FC
+ * @{
+ */
+
+  /**
+   * @brief Q7 basic fully-connected layer function
+   * @param[in]       pV          pointer to input vector
+   * @param[in]       pM          pointer to matrix weights
+   * @param[in]       dim_vec     length of the vector
+   * @param[in]       num_of_rows number of rows in weight matrix
+   * @param[in]       bias_shift  amount of left-shift for bias
+   * @param[in]       out_shift   amount of right-shift for output
+   * @param[in]       bias        pointer to bias
+   * @param[in,out]   pOut        pointer to output vector
+   * @param[in,out]   vec_buffer  pointer to buffer space for input
+   * @return     The function returns <code>ARM_MATH_SUCCESS</code>
+   *
+   * @details
+   *
+   * <b>Buffer size:</b>
+   *
+   * vec_buffer size: dim_vec
+   *
+   * This basic function is designed to work with regular weight
+   * matrix without interleaving.
+   *
+   */
+
+arm_status
+arm_fully_connected_q7(const q7_t * pV,
+                       const q7_t * pM,
+                       const uint16_t dim_vec,
+                       const uint16_t num_of_rows,
+                       const uint16_t bias_shift,
+                       const uint16_t out_shift, const q7_t * bias, q7_t * pOut, q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+    /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+    const q7_t *pB = pM;
+    const q7_t *pB2;
+    q7_t     *pO = pOut;
+    const q7_t *pBias = bias;
+    q15_t    *pA;
+    uint16_t  rowCnt = num_of_rows >> 1;
+
+    /* expand the vector into the buffer */
+    arm_q7_to_q15_reordered_no_shift(pV, vec_buffer, dim_vec);
+
+    while (rowCnt)
+    {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = vec_buffer;
+        pB2 = pB + dim_vec;
+
+        while (colCnt)
+        {
+            q31_t     inV, inM11, inM12, inM21, inM22;
+            pB = (q7_t *) read_and_pad_reordered((void *)pB, &inM11, &inM12);
+            pB2 = (q7_t *) read_and_pad_reordered((void *)pB2, &inM21, &inM22);
+
+            inV = *__SIMD32(pA)++;
+
+            sum = __SMLAD(inV, inM11, sum);
+            sum2 = __SMLAD(inV, inM21, sum2);
+
+            inV = *__SIMD32(pA)++;
+
+            sum = __SMLAD(inV, inM12, sum);
+            sum2 = __SMLAD(inV, inM22, sum2);
+
+            colCnt--;
+        }
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q7_t      inV = *pA++;
+            q15_t     inM = *pB++;
+            q15_t     inM2 = *pB2++;
+
+            sum += inV * inM;
+            sum2 += inV * inM2;
+            colCnt--;
+        }                       /* while over colCnt */
+        *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+        *pO++ = (q7_t) (__SSAT((sum2 >> out_shift), 8));
+
+        /* adjust the pointers and counters */
+        pB += dim_vec;
+        rowCnt--;
+    }
+
+    /* left-over part of the rows */
+    rowCnt = num_of_rows & 0x1;
+
+    while (rowCnt)
+    {
+        uint16_t  colCnt = dim_vec >> 2;
+        q31_t     sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        pA = vec_buffer;
+
+        while (colCnt)
+        {
+            q31_t     inV1, inV2, inM11, inM12;
+
+            pB = (q7_t *) read_and_pad_reordered((void *)pB, &inM11, &inM12);
+
+            inV1 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV1, inM11, sum);
+
+            inV2 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV2, inM12, sum);
+
+            colCnt--;
+        }
+
+        /* left-over of the vector */
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q7_t      inV = *pA++;
+            q15_t     inM = *pB++;
+            sum += inV * inM;
+            colCnt--;
+        }
+
+        *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+
+        rowCnt--;
+    }
+
+#else
+    int       i, j;
+
+    /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+    for (i = 0; i < num_of_rows; i++)
+    {
+        int       ip_out = ((q31_t)(bias[i]) << bias_shift) + NN_ROUND(out_shift);
+        for (j = 0; j < dim_vec; j++)
+        {
+            ip_out += pV[j] * pM[i * dim_vec + j];
+        }
+        pOut[i] = (q7_t) __SSAT((ip_out >> out_shift), 8);
+    }
+
+#endif                          /* ARM_MATH_DSP */
+
+    /* Return to ARM_MATH_SUCCESS */
+    return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
diff --git a/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7_opt.c b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7_opt.c
new file mode 100644
index 0000000..e3d0874
--- /dev/null
+++ b/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7_opt.c
@@ -0,0 +1,484 @@
+/*
+ * 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_fully_connected_q7_opt.c
+ * Description:  Q7 basic fully-connected layer function
+ *
+ * $Date:        17. January 2018
+ * $Revision:    V.1.0.0
+ *
+ * Target Processor:  Cortex-M cores
+ *
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_nnfunctions.h"
+
+/**
+ *  @ingroup groupNN
+ */
+
+/**
+ * @addtogroup FC
+ * @{
+ */
+
+  /**
+   * @brief Q7 opt fully-connected layer function
+   * @param[in]       pV          pointer to input vector
+   * @param[in]       pM          pointer to matrix weights
+   * @param[in]       dim_vec     length of the vector
+   * @param[in]       num_of_rows number of rows in weight matrix
+   * @param[in]       bias_shift  amount of left-shift for bias
+   * @param[in]       out_shift   amount of right-shift for output
+   * @param[in]       bias        pointer to bias
+   * @param[in,out]   pOut        pointer to output vector
+   * @param[in,out]   vec_buffer  pointer to buffer space for input
+   * @return     The function returns <code>ARM_MATH_SUCCESS</code>
+   *
+   * @details
+   *
+   * <b>Buffer size:</b>
+   *
+   * vec_buffer size: dim_vec
+   *
+   * This opt function is designed to work with interleaved weight
+   * matrix. The vector input is assumed in q7_t format, we call
+   *  arm_q7_to_q15_no_shift_shuffle function to expand into
+   *  q15_t format with certain weight re-ordering, refer to the function
+   *  comments for more details.
+   *  Here we use only one pointer to read 4 rows in the weight
+   *  matrix. So if the original q7_t matrix looks like this:
+   *
+   *  | a11 | a12 | a13 | a14 | a15 | a16 | a17 |
+   *
+   *  | a21 | a22 | a23 | a24 | a25 | a26 | a27 |
+   *
+   *  | a31 | a32 | a33 | a34 | a35 | a36 | a37 |
+   *
+   *  | a41 | a42 | a43 | a44 | a45 | a46 | a47 |
+   *
+   *  | a51 | a52 | a53 | a54 | a55 | a56 | a57 |
+   *
+   *  | a61 | a62 | a63 | a64 | a65 | a66 | a67 |
+   *
+   *
+   *  We operates on multiple-of-4 rows, so the first four rows becomes
+   *
+   *  | a11 | a21 | a13 | a23 | a31 | a41 | a33 | a43 |
+   *
+   *  | a12 | a22 | a14 | a24 | a32 | a42 | a34 | a44 |
+   *
+   *  | a15 | a25 | a35 | a45 | a16 | a26 | a36 | a46 |
+   *
+   *  So within the kernel, we first read the re-ordered vector in as:
+   *
+   *  | b1  | b3  | and | b2  | b4  |
+   *
+   *  the four q31_t weights will look like
+   *
+   *  | a11 | a13 |, | a21 | a23 |, | a31 | a33 |, | a41 | a43 |
+   *
+   *  | a12 | a14 |, | a22 | a24 |, | a32 | a34 |, | a42 | a44 |
+   *
+   *  The column left over will be in-order.
+   *  which is:
+   *
+   *  | a17 | a27 | a37 | a47 |
+   *
+   *  For the left-over rows, we do 1x1 computation, so the data remains
+   *  as its original order. 
+   *
+   *  So the stored weight matrix looks like this:
+   *
+   *  | a11 | a21 | a13 | a23 | a31 | a41 |
+   *
+   *  | a33 | a43 | a12 | a22 | a14 | a24 |
+   *
+   *  | a32 | a42 | a34 | a44 | a15 | a25 |
+   *
+   *  | a35 | a45 | a16 | a26 | a36 | a46 |
+   *
+   *  | a17 | a27 | a37 | a47 | a51 | a52 |
+   *
+   *  | a53 | a54 | a55 | a56 | a57 | a61 |
+   *
+   *  | a62 | a63 | a64 | a65 | a66 | a67 |
+   *
+   *
+   */
+
+arm_status
+arm_fully_connected_q7_opt(const q7_t * pV,
+                           const q7_t * pM,
+                           const uint16_t dim_vec,
+                           const uint16_t num_of_rows,
+                           const uint16_t bias_shift,
+                           const uint16_t out_shift, 
+                           const q7_t * bias, 
+                           q7_t * pOut, 
+                           q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+    /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+    const q7_t *pB = pM;
+    q7_t     *pO = pOut;
+    const q7_t *pBias = bias;
+    q15_t    *pA;
+    uint16_t  rowCnt = num_of_rows >> 2;
+
+    arm_q7_to_q15_reordered_no_shift(pV, vec_buffer, dim_vec);
+
+    while (rowCnt)
+    {
+
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = vec_buffer;
+
+#ifdef USE_INTRINSIC
+
+#ifndef ARM_MATH_BIG_ENDIAN
+        while (colCnt)
+        {
+            q31_t     inM11, inM12, inM13, inM14;
+            q31_t     inV;
+
+            inV = *__SIMD32(pA)++;
+            inM11 = *__SIMD32(pB)++;
+            inM12 = __SXTB16(__ROR(inM11, 8));
+            inM11 = __SXTB16(inM11);
+            sum = __SMLAD(inM11, inV, sum);
+            sum2 = __SMLAD(inM12, inV, sum2);
+            inM13 = *__SIMD32(pB)++;
+            inM14 = __SXTB16(__ROR(inM13, 8));
+            inM13 = __SXTB16(inM13);
+            sum3 = __SMLAD(inM13, inV, sum3);
+            sum4 = __SMLAD(inM14, inV, sum4);
+
+            inV = *__SIMD32(pA)++;
+            inM11 = *__SIMD32(pB)++;
+            inM12 = __SXTB16(__ROR(inM11, 8));
+            inM11 = __SXTB16(inM11);
+            sum = __SMLAD(inM11, inV, sum);
+            sum2 = __SMLAD(inM12, inV, sum2);
+            inM13 = *__SIMD32(pB)++;
+            inM14 = __SXTB16(__ROR(inM13, 8));
+            inM13 = __SXTB16(inM13);
+            sum3 = __SMLAD(inM13, inV, sum3);
+            sum4 = __SMLAD(inM14, inV, sum4);
+            colCnt--;
+        }
+#else
+        while (colCnt)
+        {
+            q31_t     inM11, inM12, inM13, inM14;
+            q31_t     inV;
+
+            inV = *__SIMD32(pA)++;
+            inM11 = *__SIMD32(pB)++;
+            inM12 = __SXTB16(__ROR(inM11, 8));
+            inM11 = __SXTB16(inM11);
+            sum = __SMLAD(inM12, inV, sum);
+            sum2 = __SMLAD(inM11, inV, sum2);
+            inM13 = *__SIMD32(pB)++;
+            inM14 = __SXTB16(__ROR(inM13, 8));
+            inM13 = __SXTB16(inM13);
+            sum3 = __SMLAD(inM14, inV, sum3);
+            sum4 = __SMLAD(inM13, inV, sum4);
+
+            inV = *__SIMD32(pA)++;
+            inM11 = *__SIMD32(pB)++;
+            inM12 = __SXTB16(__ROR(inM11, 8));
+            inM11 = __SXTB16(inM11);
+            sum = __SMLAD(inM12, inV, sum);
+            sum2 = __SMLAD(inM11, inV, sum2);
+            inM13 = *__SIMD32(pB)++;
+            inM14 = __SXTB16(__ROR(inM13, 8));
+            inM13 = __SXTB16(inM13);
+            sum3 = __SMLAD(inM14, inV, sum3);
+            sum4 = __SMLAD(inM13, inV, sum4);
+            colCnt--;
+        }
+#endif                          /* ARM_MATH_BIG_ENDIAN */
+
+#else
+
+        /*
+         * register needed:
+         * loop counter: colCnt
+         * accumulators: sum, sum2, sum3, sum4
+         * pointers: pB, pA
+         * weight data: inM11, inM12, inM13, inM14
+         * activation data: inV
+         */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+        asm volatile ("COL_LOOP_%=:\n"
+                      "ldr.w r4, [%[pA]], #8\n"
+                      "ldr.w r1, [%[pB]], #16\n"
+                      "mov.w r0, r1, ror #8\n"
+                      "sxtb16 r0, r0\n"
+                      "sxtb16 r1, r1\n"
+                      "smlad %[sum], r4, r1, %[sum]\n"
+                      "smlad %[sum2], r4, r0, %[sum2]\n"
+                      "ldr.w r3, [%[pB], #-12]\n"
+                      "mov.w r2, r3, ror #8\n"
+                      "sxtb16 r2, r2\n"
+                      "sxtb16 r3, r3\n"
+                      "smlad %[sum3], r4, r3, %[sum3]\n"
+                      "smlad %[sum4], r4, r2, %[sum4]\n"
+                      "ldr.w r4, [%[pA], #-4]\n"
+                      "ldr.w r1, [%[pB], #-8]\n"
+                      "mov.w r0, r1, ror #8\n"
+                      "sxtb16 r0, r0\n"
+                      "sxtb16 r1, r1\n"
+                      "smlad %[sum], r4, r1, %[sum]\n"
+                      "smlad %[sum2], r4, r0, %[sum2]\n"
+                      "ldr.w r3, [%[pB], #-4]\n"
+                      "mov.w r2, r3, ror #8\n"
+                      "sxtb16 r2, r2\n"
+                      "sxtb16 r3, r3\n"
+                      "smlad %[sum3], r4, r3, %[sum3]\n"
+                      "smlad %[sum4], r4, r2, %[sum4]\n"
+                      "subs %[colCnt], #1\n"
+                      "bne COL_LOOP_%=\n":[sum] "+r"(sum),
+                      [sum2] "+r"(sum2),[sum3] "+r"(sum3),
+                      [sum4] "+r"(sum4),[pB] "+r"(pB),[pA] "+r"(pA):[colCnt] "r"(colCnt):"r0", "r1", "r2", "r3", "r4");
+#else
+        asm volatile ("COL_LOOP_%=:\n"
+                      "ldr.w r4, [%[pA]], #8\n"
+                      "ldr.w r1, [%[pB]], #16\n"
+                      "mov.w r0, r1, ror #8\n"
+                      "sxtb16 r0, r0\n"
+                      "sxtb16 r1, r1\n"
+                      "smlad %[sum], r4, r0, %[sum]\n"
+                      "smlad %[sum2], r4, r1, %[sum2]\n"
+                      "ldr.w r3, [%[pB], #-12]\n"
+                      "mov.w r2, r3, ror #8\n"
+                      "sxtb16 r2, r2\n"
+                      "sxtb16 r3, r3\n"
+                      "smlad %[sum3], r4, r2, %[sum3]\n"
+                      "smlad %[sum4], r4, r3, %[sum4]\n"
+                      "ldr.w r4, [%[pA], #-4]\n"
+                      "ldr.w r1, [%[pB], #-8]\n"
+                      "mov.w r0, r1, ror #8\n"
+                      "sxtb16 r0, r0\n"
+                      "sxtb16 r1, r1\n"
+                      "smlad %[sum], r4, r0, %[sum]\n"
+                      "smlad %[sum2], r4, r1, %[sum2]\n"
+                      "ldr.w r3, [%[pB], #-4]\n"
+                      "mov.w r2, r3, ror #8\n"
+                      "sxtb16 r2, r2\n"
+                      "sxtb16 r3, r3\n"
+                      "smlad %[sum3], r4, r2, %[sum3]\n"
+                      "smlad %[sum4], r4, r3, %[sum4]\n"
+                      "subs %[colCnt], #1\n"
+                      "bne COL_LOOP_%=\n":[sum] "+r"(sum),
+                      [sum2] "+r"(sum2),[sum3] "+r"(sum3),
+                      [sum4] "+r"(sum4),[pB] "+r"(pB),[pA] "+r"(pA):[colCnt] "r"(colCnt):"r0", "r1", "r2", "r3", "r4");
+#endif                          /* ARM_MATH_BIG_ENDIAN */
+
+#endif                          /* USE_INTRINSIC */
+
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q7_t      inM = *pB++;
+            q7_t      inM2 = *pB++;
+            q7_t      inM3 = *pB++;
+            q7_t      inM4 = *pB++;
+
+            sum += inV * inM;
+            sum2 += inV * inM2;
+            sum3 += inV * inM3;
+            sum4 += inV * inM4;
+            colCnt--;
+        }                       /* while over colCnt */
+        *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+        *pO++ = (q7_t) (__SSAT((sum2 >> out_shift), 8));
+        *pO++ = (q7_t) (__SSAT((sum3 >> out_shift), 8));
+        *pO++ = (q7_t) (__SSAT((sum4 >> out_shift), 8));
+
+        /* adjust the pointers and counters */
+        rowCnt--;
+    }
+
+    /* left-over part of the rows */
+    rowCnt = num_of_rows & 0x3;
+
+    while (rowCnt)
+    {
+        q31_t     sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = vec_buffer;
+
+        while (colCnt)
+        {
+            q31_t     inV1, inV2, inM11, inM12;
+
+            pB = (q7_t *) read_and_pad_reordered((void *)pB, &inM11, &inM12);
+
+            inV1 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV1, inM11, sum);
+
+            inV2 = *__SIMD32(pA)++;
+            sum = __SMLAD(inV2, inM12, sum);
+
+            colCnt--;
+        }
+
+        /* left-over of the vector */
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q15_t     inV = *pA++;
+            q7_t      inM = *pB++;
+            sum += inV * inM;
+            colCnt--;
+        }
+
+        *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+
+        rowCnt--;
+    }
+
+#else
+    /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+    uint16_t  rowCnt = num_of_rows >> 2;
+    const q7_t *pB = pM;
+    const q7_t *pA;
+    q7_t     *pO = pOut;
+    const q7_t *pBias = bias;
+
+    while (rowCnt)
+    {
+        q31_t     sum =  ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+        q31_t     sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        uint16_t  colCnt = dim_vec >> 2;
+
+        pA = pV;
+
+        while (colCnt)
+        {
+            q7_t      inA1 = *pA++;
+            q7_t      inA3 = *pA++;
+            q7_t      inA2 = *pA++;
+            q7_t      inA4 = *pA++;
+
+            q7_t      inB1 = *pB++;
+            q7_t      inB3 = *pB++;
+            q7_t      inB2 = *pB++;
+            q7_t      inB4 = *pB++;
+
+            sum += inA1 * inB1 + inA2 * inB2;
+            sum2 += inA1 * inB3 + inA2 * inB4;
+
+            inB1 = *pB++;
+            inB3 = *pB++;
+            inB2 = *pB++;
+            inB4 = *pB++;
+
+            sum3 += inA1 * inB1 + inA2 * inB2;
+            sum4 += inA1 * inB3 + inA2 * inB4;
+
+            inB1 = *pB++;
+            inB3 = *pB++;
+            inB2 = *pB++;
+            inB4 = *pB++;
+
+            sum += inA3 * inB1 + inA4 * inB2;
+            sum2 += inA3 * inB3 + inA4 * inB4;
+
+            inB1 = *pB++;
+            inB3 = *pB++;
+            inB2 = *pB++;
+            inB4 = *pB++;
+
+            sum3 += inA3 * inB1 + inA4 * inB2;
+            sum4 += inA3 * inB3 + inA4 * inB4;
+
+            colCnt--;
+        }
+        colCnt = dim_vec & 0x3;
+        while (colCnt)
+        {
+            q7_t      inA = *pA++;
+            q7_t      inB = *pB++;
+            sum += inA * inB;
+            inB = *pB++;
+            sum2 += inA * inB;
+            inB = *pB++;
+            sum3 += inA * inB;
+            inB = *pB++;
+            sum4 += inA * inB;
+
+            colCnt--;
+        }
+        *pO++ = (q7_t) __SSAT((sum >> out_shift), 8);
+        *pO++ = (q7_t) __SSAT((sum2 >> out_shift), 8);
+        *pO++ = (q7_t) __SSAT((sum3 >> out_shift), 8);
+        *pO++ = (q7_t) __SSAT((sum4 >> out_shift), 8);
+
+        rowCnt--;
+    }
+
+    rowCnt = num_of_rows & 0x3;
+
+    while (rowCnt)
+    {
+        int       ip_out = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+        int       j;
+
+        pA = pV;
+        for (j = 0; j < dim_vec; j++)
+        {
+            q7_t      inA = *pA++;
+            q7_t      inB = *pB++;
+            ip_out += inA * inB;
+        }
+        *pO++ = (q7_t) __SSAT((ip_out >> out_shift), 8);
+
+        rowCnt--;
+    }
+
+#endif                          /* ARM_MATH_DSP */
+
+    /* Return to ARM_MATH_SUCCESS */
+    return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */