1 /*
2 * SPDX-FileCopyrightText: Copyright 2010-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
3 *
4 * SPDX-License-Identifier: Apache-2.0
5 *
6 * Licensed under the Apache License, Version 2.0 (the License); you may
7 * not use this file except in compliance with the License.
8 * You may obtain a copy of the License at
9 *
10 * www.apache.org/licenses/LICENSE-2.0
11 *
12 * Unless required by applicable law or agreed to in writing, software
13 * distributed under the License is distributed on an AS IS BASIS, WITHOUT
14 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
15 * See the License for the specific language governing permissions and
16 * limitations under the License.
17 */
18
19 /* ----------------------------------------------------------------------
20 * Project: CMSIS NN Library
21 * Title: arm_convolve_1x1_s8_fast.c
22 * Description: Fast s8 version of 1x1 convolution (non-square shape)
23 *
24 * $Date: 30 January 2023
25 * $Revision: V.3.1.0
26 *
27 * Target : Arm(R) M-Profile Architecture
28 *
29 * -------------------------------------------------------------------- */
30
31 #include "arm_nnfunctions.h"
32 #include "arm_nnsupportfunctions.h"
33
34 /**
35 * @ingroup Public
36 */
37
38 /**
39 * @addtogroup NNConv
40 * @{
41 */
42
43 /*
44 * Fast s8 version for 1x1 convolution (non-square shape)
45 *
46 * Refer header file for details.
47 *
48 */
49
arm_convolve_1x1_s8_fast(const cmsis_nn_context * ctx,const cmsis_nn_conv_params * conv_params,const cmsis_nn_per_channel_quant_params * quant_params,const cmsis_nn_dims * input_dims,const int8_t * input_data,const cmsis_nn_dims * filter_dims,const int8_t * filter_data,const cmsis_nn_dims * bias_dims,const int32_t * bias_data,const cmsis_nn_dims * output_dims,int8_t * output_data)50 arm_cmsis_nn_status arm_convolve_1x1_s8_fast(const cmsis_nn_context *ctx,
51 const cmsis_nn_conv_params *conv_params,
52 const cmsis_nn_per_channel_quant_params *quant_params,
53 const cmsis_nn_dims *input_dims,
54 const int8_t *input_data,
55 const cmsis_nn_dims *filter_dims,
56 const int8_t *filter_data,
57 const cmsis_nn_dims *bias_dims,
58 const int32_t *bias_data,
59 const cmsis_nn_dims *output_dims,
60 int8_t *output_data)
61 {
62 if (conv_params->padding.w != 0 || conv_params->padding.h != 0 || conv_params->stride.w != 1 ||
63 conv_params->stride.h != 1)
64 {
65 return ARM_CMSIS_NN_ARG_ERROR;
66 }
67
68 (void)ctx;
69 (void)filter_dims;
70 (void)bias_dims;
71
72 const int32_t lhs_rows = input_dims->w * input_dims->h * input_dims->n;
73 const int32_t rhs_rows = output_dims->c;
74 const int32_t rhs_cols = input_dims->c;
75
76 arm_nn_mat_mult_nt_t_s8(input_data,
77 filter_data,
78 bias_data,
79 output_data,
80 quant_params->multiplier,
81 quant_params->shift,
82 lhs_rows,
83 rhs_rows,
84 rhs_cols,
85 conv_params->input_offset,
86 conv_params->output_offset,
87 conv_params->activation.min,
88 conv_params->activation.max,
89 rhs_cols);
90
91 /* Return to application */
92 return ARM_CMSIS_NN_SUCCESS;
93 }
94
95 /**
96 * @} end of NNConv group
97 */
98
