87 lines
2.2 KiB
C
87 lines
2.2 KiB
C
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/*
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* Copyright (c) 2018-2020
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* Jianjia Ma
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* majianjia@live.com
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*
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* SPDX-License-Identifier: Apache-2.0
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*
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* Change Logs:
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* Date Author Notes
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* 2019-07-23 Jianjia Ma The first version
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*/
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#include <stdint.h>
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#include <string.h>
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#include <stdbool.h>
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#include "nnom.h"
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#include "nnom_local.h"
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#include "nnom_layers.h"
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#include "layers/nnom_softmax.h"
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#ifdef NNOM_USING_CMSIS_NN
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#include "arm_math.h"
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#include "arm_nnfunctions.h"
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#endif
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nnom_layer_t *softmax_s(const nnom_softmax_config_t * config)
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{
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nnom_layer_t * layer = Softmax();
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if(layer)
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layer->config = (void*) config;
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return layer;
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}
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nnom_layer_t *Softmax(void)
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{
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nnom_layer_t *layer;
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nnom_layer_io_t *in, *out;
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// apply a block memory for all the sub handles.
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size_t mem_size = sizeof(nnom_layer_t) + sizeof(nnom_layer_io_t) * 2;
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layer = nnom_mem(mem_size);
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if (layer == NULL)
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return NULL;
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// distribut the memory to sub handles.
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in = (void *)((uint8_t*)layer + sizeof(nnom_layer_t));
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out = (void *)((uint8_t*)in + sizeof(nnom_layer_io_t));
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// set type in layer parent
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layer->type = NNOM_SOFTMAX;
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layer->run = softmax_run;
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layer->build = softmax_build;
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// set buf state
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in->type = NNOM_TENSOR_BUF_TEMP;
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out->type = NNOM_TENSOR_BUF_TEMP;
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// put in & out on the layer.
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layer->in = io_init(layer, in);
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layer->out = io_init(layer, out);
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return layer;
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}
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nnom_status_t softmax_build(nnom_layer_t *layer)
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{
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// get the last layer's output as input shape
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layer->in->tensor = layer->in->hook.io->tensor;
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// output tensor
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layer->out->tensor = new_tensor(NNOM_QTYPE_PER_TENSOR, layer->in->tensor->num_dim, tensor_get_num_channel(layer->in->tensor));
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tensor_cpy_attr(layer->out->tensor, layer->in->tensor);
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// softmax has fixed output dec bit
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layer->out->tensor->q_dec[0] = 7;
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return NN_SUCCESS;
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}
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nnom_status_t softmax_run(nnom_layer_t *layer)
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{
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// looks like the new version cause accuracy drop quite a lot.
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// #ifdef NNOM_USING_CMSIS_NN
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// // temporary fixed for mutiple dimension input.
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// arm_softmax_q7(layer->in->tensor->p_data, tensor_size(layer->out->tensor), layer->out->tensor->p_data);
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// #else
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local_softmax_q7(layer->in->tensor->p_data, tensor_size(layer->out->tensor), layer->out->tensor->p_data);
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//#endif
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return NN_SUCCESS;
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}
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