From 516f019ba6fb88de7218dd3b4eaeadb1cf676518 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 11 May 2015 20:46:49 +0000
Subject: [PATCH] route handles input images well....ish
---
src/network_kernels.cu | 235 +++++++++++++++++-----------------------------------------
1 files changed, 68 insertions(+), 167 deletions(-)
diff --git a/src/network_kernels.cu b/src/network_kernels.cu
index 7ff5d15..da21d63 100644
--- a/src/network_kernels.cu
+++ b/src/network_kernels.cu
@@ -15,7 +15,6 @@
#include "deconvolutional_layer.h"
#include "maxpool_layer.h"
#include "cost_layer.h"
-#include "normalization_layer.h"
#include "softmax_layer.h"
#include "dropout_layer.h"
#include "route_layer.h"
@@ -29,37 +28,29 @@
{
int i;
for(i = 0; i < net.n; ++i){
- if(net.types[i] == CONVOLUTIONAL){
- forward_convolutional_layer_gpu(*(convolutional_layer *)net.layers[i], state);
+ layer l = net.layers[i];
+ if(l.type == CONVOLUTIONAL){
+ forward_convolutional_layer_gpu(l, state);
+ } else if(l.type == DECONVOLUTIONAL){
+ forward_deconvolutional_layer_gpu(l, state);
+ } else if(l.type == DETECTION){
+ forward_detection_layer_gpu(l, state);
+ } else if(l.type == CONNECTED){
+ forward_connected_layer_gpu(l, state);
+ } else if(l.type == CROP){
+ forward_crop_layer_gpu(l, state);
+ } else if(l.type == COST){
+ forward_cost_layer_gpu(l, state);
+ } else if(l.type == SOFTMAX){
+ forward_softmax_layer_gpu(l, state);
+ } else if(l.type == MAXPOOL){
+ forward_maxpool_layer_gpu(l, state);
+ } else if(l.type == DROPOUT){
+ forward_dropout_layer_gpu(l, state);
+ } else if(l.type == ROUTE){
+ forward_route_layer_gpu(l, net);
}
- else if(net.types[i] == DECONVOLUTIONAL){
- forward_deconvolutional_layer_gpu(*(deconvolutional_layer *)net.layers[i], state);
- }
- else if(net.types[i] == COST){
- forward_cost_layer_gpu(*(cost_layer *)net.layers[i], state);
- }
- else if(net.types[i] == CONNECTED){
- forward_connected_layer_gpu(*(connected_layer *)net.layers[i], state);
- }
- else if(net.types[i] == DETECTION){
- forward_detection_layer_gpu(*(detection_layer *)net.layers[i], state);
- }
- else if(net.types[i] == MAXPOOL){
- forward_maxpool_layer_gpu(*(maxpool_layer *)net.layers[i], state);
- }
- else if(net.types[i] == SOFTMAX){
- forward_softmax_layer_gpu(*(softmax_layer *)net.layers[i], state);
- }
- else if(net.types[i] == DROPOUT){
- forward_dropout_layer_gpu(*(dropout_layer *)net.layers[i], state);
- }
- else if(net.types[i] == CROP){
- forward_crop_layer_gpu(*(crop_layer *)net.layers[i], state);
- }
- else if(net.types[i] == ROUTE){
- forward_route_layer_gpu(*(route_layer *)net.layers[i], net);
- }
- state.input = get_network_output_gpu_layer(net, i);
+ state.input = l.output_gpu;
}
}
@@ -68,40 +59,33 @@
int i;
float * original_input = state.input;
for(i = net.n-1; i >= 0; --i){
+ layer l = net.layers[i];
if(i == 0){
state.input = original_input;
state.delta = 0;
}else{
- state.input = get_network_output_gpu_layer(net, i-1);
- state.delta = get_network_delta_gpu_layer(net, i-1);
+ layer prev = net.layers[i-1];
+ state.input = prev.output_gpu;
+ state.delta = prev.delta_gpu;
}
-
- if(net.types[i] == CONVOLUTIONAL){
- backward_convolutional_layer_gpu(*(convolutional_layer *)net.layers[i], state);
- }
- else if(net.types[i] == DECONVOLUTIONAL){
- backward_deconvolutional_layer_gpu(*(deconvolutional_layer *)net.layers[i], state);
- }
- else if(net.types[i] == COST){
- backward_cost_layer_gpu(*(cost_layer *)net.layers[i], state);
- }
- else if(net.types[i] == CONNECTED){
- backward_connected_layer_gpu(*(connected_layer *)net.layers[i], state);
- }
- else if(net.types[i] == DETECTION){
- backward_detection_layer_gpu(*(detection_layer *)net.layers[i], state);
- }
- else if(net.types[i] == MAXPOOL){
- backward_maxpool_layer_gpu(*(maxpool_layer *)net.layers[i], state);
- }
- else if(net.types[i] == DROPOUT){
- backward_dropout_layer_gpu(*(dropout_layer *)net.layers[i], state);
- }
- else if(net.types[i] == SOFTMAX){
- backward_softmax_layer_gpu(*(softmax_layer *)net.layers[i], state);
- }
- else if(net.types[i] == ROUTE){
- backward_route_layer_gpu(*(route_layer *)net.layers[i], net);
+ if(l.type == CONVOLUTIONAL){
+ backward_convolutional_layer_gpu(l, state);
+ } else if(l.type == DECONVOLUTIONAL){
+ backward_deconvolutional_layer_gpu(l, state);
+ } else if(l.type == MAXPOOL){
+ if(i != 0) backward_maxpool_layer_gpu(l, state);
+ } else if(l.type == DROPOUT){
+ backward_dropout_layer_gpu(l, state);
+ } else if(l.type == DETECTION){
+ backward_detection_layer_gpu(l, state);
+ } else if(l.type == SOFTMAX){
+ if(i != 0) backward_softmax_layer_gpu(l, state);
+ } else if(l.type == CONNECTED){
+ backward_connected_layer_gpu(l, state);
+ } else if(l.type == COST){
+ backward_cost_layer_gpu(l, state);
+ } else if(l.type == ROUTE){
+ backward_route_layer_gpu(l, net);
}
}
}
@@ -111,89 +95,17 @@
int i;
int update_batch = net.batch*net.subdivisions;
for(i = 0; i < net.n; ++i){
- if(net.types[i] == CONVOLUTIONAL){
- convolutional_layer layer = *(convolutional_layer *)net.layers[i];
- update_convolutional_layer_gpu(layer, update_batch, net.learning_rate, net.momentum, net.decay);
- }
- else if(net.types[i] == DECONVOLUTIONAL){
- deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
- update_deconvolutional_layer_gpu(layer, net.learning_rate, net.momentum, net.decay);
- }
- else if(net.types[i] == CONNECTED){
- connected_layer layer = *(connected_layer *)net.layers[i];
- update_connected_layer_gpu(layer, update_batch, net.learning_rate, net.momentum, net.decay);
+ layer l = net.layers[i];
+ if(l.type == CONVOLUTIONAL){
+ update_convolutional_layer_gpu(l, update_batch, net.learning_rate, net.momentum, net.decay);
+ } else if(l.type == DECONVOLUTIONAL){
+ update_deconvolutional_layer_gpu(l, net.learning_rate, net.momentum, net.decay);
+ } else if(l.type == CONNECTED){
+ update_connected_layer_gpu(l, update_batch, net.learning_rate, net.momentum, net.decay);
}
}
}
-float * get_network_output_gpu_layer(network net, int i)
-{
- if(net.types[i] == CONVOLUTIONAL){
- return ((convolutional_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == DECONVOLUTIONAL){
- return ((deconvolutional_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == DETECTION){
- return ((detection_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == CONNECTED){
- return ((connected_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == MAXPOOL){
- return ((maxpool_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == CROP){
- return ((crop_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == SOFTMAX){
- return ((softmax_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == ROUTE){
- return ((route_layer *)net.layers[i]) -> output_gpu;
- }
- else if(net.types[i] == DROPOUT){
- return get_network_output_gpu_layer(net, i-1);
- }
- return 0;
-}
-
-float * get_network_delta_gpu_layer(network net, int i)
-{
- if(net.types[i] == CONVOLUTIONAL){
- convolutional_layer layer = *(convolutional_layer *)net.layers[i];
- return layer.delta_gpu;
- }
- else if(net.types[i] == DETECTION){
- detection_layer layer = *(detection_layer *)net.layers[i];
- return layer.delta_gpu;
- }
- else if(net.types[i] == DECONVOLUTIONAL){
- deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
- return layer.delta_gpu;
- }
- else if(net.types[i] == CONNECTED){
- connected_layer layer = *(connected_layer *)net.layers[i];
- return layer.delta_gpu;
- }
- else if(net.types[i] == MAXPOOL){
- maxpool_layer layer = *(maxpool_layer *)net.layers[i];
- return layer.delta_gpu;
- }
- else if(net.types[i] == ROUTE){
- route_layer layer = *(route_layer *)net.layers[i];
- return layer.delta_gpu;
- }
- else if(net.types[i] == SOFTMAX){
- softmax_layer layer = *(softmax_layer *)net.layers[i];
- return layer.delta_gpu;
- } else if(net.types[i] == DROPOUT){
- if(i == 0) return 0;
- return get_network_delta_gpu_layer(net, i-1);
- }
- return 0;
-}
-
float train_network_datum_gpu(network net, float *x, float *y)
{
network_state state;
@@ -219,33 +131,22 @@
float *get_network_output_layer_gpu(network net, int i)
{
- if(net.types[i] == CONVOLUTIONAL){
- convolutional_layer layer = *(convolutional_layer *)net.layers[i];
- return layer.output;
- }
- else if(net.types[i] == DECONVOLUTIONAL){
- deconvolutional_layer layer = *(deconvolutional_layer *)net.layers[i];
- return layer.output;
- }
- else if(net.types[i] == CONNECTED){
- connected_layer layer = *(connected_layer *)net.layers[i];
- cuda_pull_array(layer.output_gpu, layer.output, layer.outputs*layer.batch);
- return layer.output;
- }
- else if(net.types[i] == DETECTION){
- detection_layer layer = *(detection_layer *)net.layers[i];
- int outputs = get_detection_layer_output_size(layer);
- cuda_pull_array(layer.output_gpu, layer.output, outputs*layer.batch);
- return layer.output;
- }
- else if(net.types[i] == MAXPOOL){
- maxpool_layer layer = *(maxpool_layer *)net.layers[i];
- return layer.output;
- }
- else if(net.types[i] == SOFTMAX){
- softmax_layer layer = *(softmax_layer *)net.layers[i];
- pull_softmax_layer_output(layer);
- return layer.output;
+ layer l = net.layers[i];
+ if(l.type == CONVOLUTIONAL){
+ return l.output;
+ } else if(l.type == DECONVOLUTIONAL){
+ return l.output;
+ } else if(l.type == CONNECTED){
+ cuda_pull_array(l.output_gpu, l.output, l.outputs*l.batch);
+ return l.output;
+ } else if(l.type == DETECTION){
+ cuda_pull_array(l.output_gpu, l.output, l.outputs*l.batch);
+ return l.output;
+ } else if(l.type == MAXPOOL){
+ return l.output;
+ } else if(l.type == SOFTMAX){
+ pull_softmax_layer_output(l);
+ return l.output;
}
return 0;
}
@@ -253,7 +154,7 @@
float *get_network_output_gpu(network net)
{
int i;
- for(i = net.n-1; i > 0; --i) if(net.types[i] != COST) break;
+ for(i = net.n-1; i > 0; --i) if(net.layers[i].type != COST) break;
return get_network_output_layer_gpu(net, i);
}
--
Gitblit v1.10.0