From dcb000b553d051429a49c8729dc5b1af632e8532 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Thu, 12 Mar 2015 05:20:15 +0000
Subject: [PATCH] refactoring and added DARK ZONE
---
src/convolutional_kernels.cu | 33 +++++++++++++--------------------
1 files changed, 13 insertions(+), 20 deletions(-)
diff --git a/src/convolutional_kernels.cu b/src/convolutional_kernels.cu
index bcf307f..77304aa 100644
--- a/src/convolutional_kernels.cu
+++ b/src/convolutional_kernels.cu
@@ -54,7 +54,7 @@
check_error(cudaPeekAtLastError());
}
-extern "C" void forward_convolutional_layer_gpu(convolutional_layer layer, float *in)
+extern "C" void forward_convolutional_layer_gpu(convolutional_layer layer, network_state state)
{
int i;
int m = layer.n;
@@ -65,7 +65,7 @@
bias_output_gpu(layer.output_gpu, layer.biases_gpu, layer.batch, layer.n, n);
for(i = 0; i < layer.batch; ++i){
- im2col_ongpu(in + i*layer.c*layer.h*layer.w, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, layer.col_image_gpu);
+ im2col_ongpu(state.input + i*layer.c*layer.h*layer.w, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, layer.col_image_gpu);
float * a = layer.filters_gpu;
float * b = layer.col_image_gpu;
float * c = layer.output_gpu;
@@ -74,7 +74,7 @@
activate_array_ongpu(layer.output_gpu, m*n*layer.batch, layer.activation);
}
-extern "C" void backward_convolutional_layer_gpu(convolutional_layer layer, float *in, float *delta_gpu)
+extern "C" void backward_convolutional_layer_gpu(convolutional_layer layer, network_state state)
{
float alpha = 1./layer.batch;
int i;
@@ -86,17 +86,17 @@
gradient_array_ongpu(layer.output_gpu, m*k*layer.batch, layer.activation, layer.delta_gpu);
backward_bias_gpu(layer.bias_updates_gpu, layer.delta_gpu, layer.batch, layer.n, k);
- if(delta_gpu) scal_ongpu(layer.batch*layer.h*layer.w*layer.c, 0, delta_gpu, 1);
+ if(state.delta) scal_ongpu(layer.batch*layer.h*layer.w*layer.c, 0, state.delta, 1);
for(i = 0; i < layer.batch; ++i){
float * a = layer.delta_gpu;
float * b = layer.col_image_gpu;
float * c = layer.filter_updates_gpu;
- im2col_ongpu(in + i*layer.c*layer.h*layer.w, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, layer.col_image_gpu);
+ im2col_ongpu(state.input + i*layer.c*layer.h*layer.w, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, layer.col_image_gpu);
gemm_ongpu(0,1,m,n,k,alpha,a + i*m*k,k,b,k,1,c,n);
- if(delta_gpu){
+ if(state.delta){
float * a = layer.filters_gpu;
float * b = layer.delta_gpu;
@@ -104,7 +104,7 @@
gemm_ongpu(1,0,n,k,m,1,a,n,b + i*k*m,k,0,c,k);
- col2im_ongpu(layer.col_image_gpu, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, delta_gpu + i*layer.c*layer.h*layer.w);
+ col2im_ongpu(layer.col_image_gpu, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, state.delta + i*layer.c*layer.h*layer.w);
}
}
}
@@ -125,22 +125,15 @@
cuda_push_array(layer.bias_updates_gpu, layer.bias_updates, layer.n);
}
-extern "C" void update_convolutional_layer_gpu(convolutional_layer layer)
+extern "C" void update_convolutional_layer_gpu(convolutional_layer layer, float learning_rate, float momentum, float decay)
{
int size = layer.size*layer.size*layer.c*layer.n;
-/*
- cuda_pull_array(layer.filter_updates_gpu, layer.filter_updates, size);
- cuda_pull_array(layer.filters_gpu, layer.filters, size);
- printf("Filter: %f updates: %f\n", mag_array(layer.filters, size), layer.learning_rate*mag_array(layer.filter_updates, size));
- */
+ axpy_ongpu(layer.n, learning_rate, layer.bias_updates_gpu, 1, layer.biases_gpu, 1);
+ scal_ongpu(layer.n, momentum, layer.bias_updates_gpu, 1);
- axpy_ongpu(layer.n, layer.learning_rate, layer.bias_updates_gpu, 1, layer.biases_gpu, 1);
- scal_ongpu(layer.n,layer.momentum, layer.bias_updates_gpu, 1);
-
- axpy_ongpu(size, -layer.decay, layer.filters_gpu, 1, layer.filter_updates_gpu, 1);
- axpy_ongpu(size, layer.learning_rate, layer.filter_updates_gpu, 1, layer.filters_gpu, 1);
- scal_ongpu(size, layer.momentum, layer.filter_updates_gpu, 1);
- //pull_convolutional_layer(layer);
+ axpy_ongpu(size, -decay, layer.filters_gpu, 1, layer.filter_updates_gpu, 1);
+ axpy_ongpu(size, learning_rate, layer.filter_updates_gpu, 1, layer.filters_gpu, 1);
+ scal_ongpu(size, momentum, layer.filter_updates_gpu, 1);
}
--
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