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1 /*
2  * Copyright (c) 2020
3  *
4  * This file is part of FFmpeg.
5  *
6  * FFmpeg is free software; you can redistribute it and/or
7  * modify it under the terms of the GNU Lesser General Public
8  * License as published by the Free Software Foundation; either
9  * version 2.1 of the License, or (at your option) any later version.
10  *
11  * FFmpeg is distributed in the hope that it will be useful,
12  * but WITHOUT ANY WARRANTY; without even the implied warranty of
13  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
14  * Lesser General Public License for more details.
15  *
16  * You should have received a copy of the GNU Lesser General Public
17  * License along with FFmpeg; if not, write to the Free Software
18  * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
19  */
20 
21 /**
22  * @file
23  * DNN native backend implementation.
24  */
25 
26 #include "dnn_backend_native.h"
27 #include "dnn_backend_native_layer_mathbinary.h"
28 
29 typedef float (*FunType)(float src0, float src1);
30 
sub(float src0,float src1)31 static float sub(float src0, float src1)
32 {
33     return src0 - src1;
34 }
add(float src0,float src1)35 static float add(float src0, float src1)
36 {
37     return src0 + src1;
38 }
mul(float src0,float src1)39 static float mul(float src0, float src1)
40 {
41     return src0 * src1;
42 }
realdiv(float src0,float src1)43 static float realdiv(float src0, float src1)
44 {
45     return src0 / src1;
46 }
minimum(float src0,float src1)47 static float minimum(float src0, float src1)
48 {
49     return FFMIN(src0, src1);
50 }
floormod(float src0,float src1)51 static float floormod(float src0, float src1)
52 {
53     return (float)((int)(src0) % (int)(src1));
54 }
55 
math_binary_commutative(FunType pfun,const DnnLayerMathBinaryParams * params,const DnnOperand * input,DnnOperand * output,DnnOperand * operands,const int32_t * input_operand_indexes)56 static void math_binary_commutative(FunType pfun, const DnnLayerMathBinaryParams *params, const DnnOperand *input, DnnOperand *output, DnnOperand *operands, const int32_t *input_operand_indexes)
57 {
58     int dims_count;
59     const float *src;
60     float *dst;
61     dims_count = ff_calculate_operand_dims_count(output);
62     src = input->data;
63     dst = output->data;
64     if (params->input0_broadcast || params->input1_broadcast) {
65         for (int i = 0; i < dims_count; ++i) {
66             dst[i] = pfun(params->v, src[i]);
67         }
68     } else {
69         const DnnOperand *input1 = &operands[input_operand_indexes[1]];
70         const float *src1 = input1->data;
71         for (int i = 0; i < dims_count; ++i) {
72             dst[i] = pfun(src[i], src1[i]);
73         }
74     }
75 }
math_binary_not_commutative(FunType pfun,const DnnLayerMathBinaryParams * params,const DnnOperand * input,DnnOperand * output,DnnOperand * operands,const int32_t * input_operand_indexes)76 static void math_binary_not_commutative(FunType pfun, const DnnLayerMathBinaryParams *params, const DnnOperand *input, DnnOperand *output, DnnOperand *operands, const int32_t *input_operand_indexes)
77 {
78     int dims_count;
79     const float *src;
80     float *dst;
81     dims_count = ff_calculate_operand_dims_count(output);
82     src = input->data;
83     dst = output->data;
84     if (params->input0_broadcast) {
85         for (int i = 0; i < dims_count; ++i) {
86             dst[i] = pfun(params->v, src[i]);
87         }
88     } else if (params->input1_broadcast) {
89         for (int i = 0; i < dims_count; ++i) {
90             dst[i] = pfun(src[i], params->v);
91         }
92     } else {
93         const DnnOperand *input1 = &operands[input_operand_indexes[1]];
94         const float *src1 = input1->data;
95         for (int i = 0; i < dims_count; ++i) {
96             dst[i] = pfun(src[i], src1[i]);
97         }
98     }
99 }
ff_dnn_load_layer_math_binary(Layer * layer,AVIOContext * model_file_context,int file_size,int operands_num)100 int ff_dnn_load_layer_math_binary(Layer *layer, AVIOContext *model_file_context, int file_size, int operands_num)
101 {
102     DnnLayerMathBinaryParams params = { 0 };
103     int dnn_size = 0;
104     int input_index = 0;
105 
106     params.bin_op = (int32_t)avio_rl32(model_file_context);
107     dnn_size += 4;
108 
109     params.input0_broadcast = (int32_t)avio_rl32(model_file_context);
110     dnn_size += 4;
111     if (params.input0_broadcast) {
112         params.v = av_int2float(avio_rl32(model_file_context));
113     } else {
114         layer->input_operand_indexes[input_index] = (int32_t)avio_rl32(model_file_context);
115         if (layer->input_operand_indexes[input_index] >= operands_num) {
116             return 0;
117         }
118         input_index++;
119     }
120     dnn_size += 4;
121 
122     params.input1_broadcast = (int32_t)avio_rl32(model_file_context);
123     dnn_size += 4;
124     if (params.input1_broadcast) {
125         params.v = av_int2float(avio_rl32(model_file_context));
126     } else {
127         layer->input_operand_indexes[input_index] = (int32_t)avio_rl32(model_file_context);
128         if (layer->input_operand_indexes[input_index] >= operands_num) {
129             return 0;
130         }
131         input_index++;
132     }
133     dnn_size += 4;
134 
135     layer->output_operand_index = (int32_t)avio_rl32(model_file_context);
136     dnn_size += 4;
137 
138     if (layer->output_operand_index >= operands_num) {
139         return 0;
140     }
141     layer->params = av_memdup(&params, sizeof(params));
142     if (!layer->params)
143         return 0;
144 
145     return dnn_size;
146 }
147 
ff_dnn_execute_layer_math_binary(DnnOperand * operands,const int32_t * input_operand_indexes,int32_t output_operand_index,const void * parameters,NativeContext * ctx)148 int ff_dnn_execute_layer_math_binary(DnnOperand *operands, const int32_t *input_operand_indexes,
149                                      int32_t output_operand_index, const void *parameters, NativeContext *ctx)
150 {
151     const DnnOperand *input = &operands[input_operand_indexes[0]];
152     DnnOperand *output = &operands[output_operand_index];
153     const DnnLayerMathBinaryParams *params = parameters;
154 
155     for (int i = 0; i < 4; ++i)
156         output->dims[i] = input->dims[i];
157 
158     output->data_type = input->data_type;
159     output->length = ff_calculate_operand_data_length(output);
160     if (output->length <= 0) {
161         av_log(ctx, AV_LOG_ERROR, "The output data length overflow\n");
162         return AVERROR(EINVAL);
163     }
164     output->data = av_realloc(output->data, output->length);
165     if (!output->data) {
166         av_log(ctx, AV_LOG_ERROR, "Failed to reallocate memory for output\n");
167         return AVERROR(ENOMEM);
168     }
169 
170     switch (params->bin_op) {
171     case DMBO_SUB:
172         math_binary_not_commutative(sub, params, input, output, operands, input_operand_indexes);
173         return 0;
174     case DMBO_ADD:
175         math_binary_commutative(add, params, input, output, operands, input_operand_indexes);
176         return 0;
177     case DMBO_MUL:
178         math_binary_commutative(mul, params, input, output, operands, input_operand_indexes);
179         return 0;
180     case DMBO_REALDIV:
181         math_binary_not_commutative(realdiv, params, input, output, operands, input_operand_indexes);
182         return 0;
183     case DMBO_MINIMUM:
184         math_binary_commutative(minimum, params, input, output, operands, input_operand_indexes);
185         return 0;
186     case DMBO_FLOORMOD:
187         math_binary_not_commutative(floormod, params, input, output, operands, input_operand_indexes);
188         return 0;
189     default:
190         av_log(ctx, AV_LOG_ERROR, "Unmatch math binary operator\n");
191         return AVERROR(EINVAL);
192     }
193 }
194