Job_SignsPads/STM32/Code/STM32F405/nnom_src/layers/nnom_matrix.c

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/*
* Copyright (c) 2018-2020
* Jianjia Ma
* majianjia@live.com
*
* SPDX-License-Identifier: Apache-2.0
*
* Change Logs:
* Date Author Notes
* 2019-07-23 Jianjia Ma The first version
*/
#include <stdint.h>
#include <string.h>
#include <stdbool.h>
#include "nnom.h"
#include "nnom_local.h"
#include "nnom_layers.h"
#include "layers/nnom_matrix.h"
// TODO, completely change this file to local version
#ifdef NNOM_USING_CMSIS_NN
#include "arm_math.h"
#include "arm_nnfunctions.h"
#endif
nnom_status_t matrix_build(nnom_layer_t *layer);
nnom_layer_t *add_s(const nnom_matrix_config_t * config)
{
nnom_matrix_layer_t *cl = (nnom_matrix_layer_t *) Add(config->output_shift);
if(cl)
cl->super.config = (void*) config;
return (nnom_layer_t *)cl;
}
nnom_layer_t *sub_s(const nnom_matrix_config_t * config)
{
nnom_matrix_layer_t *cl = (nnom_matrix_layer_t *) Sub(config->output_shift);
if(cl)
cl->super.config = (void*) config;
return (nnom_layer_t *)cl;
}
nnom_layer_t *mult_s(const nnom_matrix_config_t * config)
{
nnom_matrix_layer_t *cl = (nnom_matrix_layer_t *) Mult(config->output_shift);
if(cl)
cl->super.config = (void*) config;
return (nnom_layer_t *)cl;
}
nnom_layer_t *Add(int16_t oshift)
{
nnom_matrix_layer_t *cl = (nnom_matrix_layer_t *)_same_shape_matrix_layer();
if (cl == NULL)
return NULL;
// set type in layer parent
cl->super.type = NNOM_ADD;
cl->super.run = add_run;
cl->oshift = oshift;
return (nnom_layer_t *)cl;
}
nnom_layer_t *Sub(int16_t oshift)
{
nnom_matrix_layer_t *cl = (nnom_matrix_layer_t *)_same_shape_matrix_layer();
if (cl == NULL)
return NULL;
// set type in layer parent
cl->super.type = NNOM_SUB;
cl->super.run = sub_run;
cl->oshift = oshift;
return (nnom_layer_t *)cl;
}
nnom_layer_t *Mult(int16_t oshift)
{
nnom_matrix_layer_t *cl = (nnom_matrix_layer_t *)_same_shape_matrix_layer();
if (cl == NULL)
return NULL;
// set type in layer parent
cl->super.type = NNOM_MULT;
cl->super.run = mult_run;
cl->oshift = oshift;
return (nnom_layer_t *)cl;
}
// init a base layer instance with same shape 1 in 1 out. More IO can be added later
// mainly used by matrix calculation (add, mult, sub)
nnom_layer_t *_same_shape_matrix_layer()
{
nnom_matrix_layer_t *layer;
nnom_layer_io_t *in, *out;
//nnom_buf_t *comp;
size_t mem_size;
// apply a block memory for all the sub handles.
mem_size = sizeof(nnom_matrix_layer_t) + sizeof(nnom_layer_io_t) * 2;
layer = nnom_mem(mem_size);
if (layer == NULL)
return NULL;
// distribut the memory to sub handles.
in = (void *)((uint8_t*)layer + sizeof(nnom_matrix_layer_t));
out = (void *)((uint8_t*)in + sizeof(nnom_layer_io_t));
//comp = (void *)((uint8_t*)out + sizeof(nnom_layer_io_t));
// set type in layer parent
layer->super.build = matrix_build;
// set buf state
in->type = NNOM_TENSOR_BUF_TEMP;
out->type = NNOM_TENSOR_BUF_TEMP;
//comp->type = NNOM_TENSOR_BUF_TEMP;
// put in & out on the layer.
layer->super.in = io_init(layer, in);
layer->super.out = io_init(layer, out);
//layer->super.comp = comp;
return (nnom_layer_t*)layer;
}
nnom_status_t matrix_build(nnom_layer_t *layer)
{
// get the last layer's output as input shape (if more than one)
nnom_layer_io_t *in = layer->in;
while(in)
{
in->tensor = in->hook.io->tensor;
in = in->aux;
}
// output tensor
layer->out->tensor = new_tensor(NNOM_QTYPE_PER_TENSOR,layer->in->tensor->num_dim, tensor_get_num_channel(layer->in->tensor));
tensor_cpy_attr(layer->out->tensor, layer->in->tensor);
// see if the activation will change the q format
if(layer->actail)
layer->out->tensor->q_dec[0] = act_get_dec_bit(layer->actail->type, layer->out->tensor->q_dec[0]);
// now this build has passed the input tensors (shapes, formats) to the new tensors.
return NN_SUCCESS;
}
nnom_status_t add_run(nnom_layer_t *layer)
{
nnom_matrix_layer_t* cl = (nnom_matrix_layer_t*)layer;
nnom_layer_io_t *in = layer->in;;
size_t t_size = tensor_size(layer->out->tensor);
int32_t oshift = cl->oshift;
size_t num_input = nnom_io_length(layer->in);
q7_t *input_mem_blk[MAX_INPUT_LAYER];
// if there is only 2 matrix
if(num_input == 2)
{
#ifdef NNOM_USING_CMSIS_NN
if(oshift == 0)
arm_add_q7(layer->in->tensor->p_data, layer->in->aux->tensor->p_data, layer->out->tensor->p_data, t_size);
else
#endif
local_add_q7(layer->in->tensor->p_data, layer->in->aux->tensor->p_data, layer->out->tensor->p_data, oshift, t_size);
}
else
{
for(int i = 0; i < num_input; i++)
{
input_mem_blk[i] = in->tensor->p_data;
in = in->aux;
}
local_multiple_add_q7(layer->out->tensor->p_data, oshift, t_size, num_input, input_mem_blk);
}
return NN_SUCCESS;
}
nnom_status_t sub_run(nnom_layer_t *layer)
{
nnom_matrix_layer_t* cl = (nnom_matrix_layer_t*)layer;
nnom_layer_io_t *in = layer->in;
size_t t_size = tensor_size(layer->out->tensor);
int32_t oshift = cl->oshift;
size_t num_input = nnom_io_length(layer->in);
q7_t *input_mem_blk[MAX_INPUT_LAYER];
// if there is only 2 matrix
if(num_input == 2)
{
// the first 2 matrix
#ifdef NNOM_USING_CMSIS_NN
if(oshift == 0)
arm_sub_q7(layer->in->tensor->p_data, layer->in->aux->tensor->p_data, layer->out->tensor->p_data, t_size);
else
#endif
local_sub_q7(layer->in->tensor->p_data, layer->in->aux->tensor->p_data, layer->out->tensor->p_data, oshift, t_size);
}
else
{
for(int i = 0; i < num_input; i++)
{
input_mem_blk[i] = in->tensor->p_data;
in = in->aux;
}
local_multiple_sub_q7(layer->out->tensor->p_data, oshift, t_size, num_input, input_mem_blk);
}
return NN_SUCCESS;
}
nnom_status_t mult_run(nnom_layer_t *layer)
{
nnom_matrix_layer_t* cl = (nnom_matrix_layer_t*)layer;
nnom_layer_io_t *in = layer->in;
size_t t_size = tensor_size(layer->out->tensor);
int32_t oshift = cl->oshift;
size_t num_input = nnom_io_length(layer->in);
q7_t *input_mem_blk[MAX_INPUT_LAYER];
// if there is only 2 matrix
if(num_input == 2)
{
// the first 2 matrix
#ifdef NNOM_USING_CMSIS_NN
if(oshift == 0)
arm_mult_q7(layer->in->tensor->p_data, layer->in->aux->tensor->p_data, layer->out->tensor->p_data, t_size);
else
#endif
local_mult_q7(layer->in->tensor->p_data, layer->in->aux->tensor->p_data, layer->out->tensor->p_data, oshift, t_size);
}
else
{
for(int i = 0; i < num_input; i++)
{
input_mem_blk[i] = in->tensor->p_data;
in = in->aux;
}
local_multiple_mult_q7(layer->out->tensor->p_data, oshift, t_size, num_input, input_mem_blk);
}
return NN_SUCCESS;
}