From cd8a3dcb4ca42f22ad8f46a95e00977c92be6bbd Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Thu, 08 Feb 2018 23:22:42 +0000
Subject: [PATCH] Compile fixes
---
src/deconvolutional_kernels.cu | 47 ++++++++++++++++++++++++++---------------------
1 files changed, 26 insertions(+), 21 deletions(-)
diff --git a/src/deconvolutional_kernels.cu b/src/deconvolutional_kernels.cu
index 1d05a80..d6259fb 100644
--- a/src/deconvolutional_kernels.cu
+++ b/src/deconvolutional_kernels.cu
@@ -1,3 +1,7 @@
+#include "cuda_runtime.h"
+#include "curand.h"
+#include "cublas_v2.h"
+
extern "C" {
#include "convolutional_layer.h"
#include "deconvolutional_layer.h"
@@ -9,7 +13,7 @@
#include "cuda.h"
}
-extern "C" void forward_deconvolutional_layer_gpu(deconvolutional_layer layer, float *in)
+extern "C" void forward_deconvolutional_layer_gpu(deconvolutional_layer layer, network_state state)
{
int i;
int out_h = deconvolutional_out_height(layer);
@@ -20,21 +24,22 @@
int n = layer.h*layer.w;
int k = layer.c;
- bias_output_gpu(layer.output_gpu, layer.biases_gpu, layer.batch, layer.n, size);
+ fill_ongpu(layer.outputs*layer.batch, 0, layer.output_gpu, 1);
for(i = 0; i < layer.batch; ++i){
- float *a = layer.filters_gpu;
- float *b = in + i*layer.c*layer.h*layer.w;
+ float *a = layer.weights_gpu;
+ float *b = state.input + i*layer.c*layer.h*layer.w;
float *c = layer.col_image_gpu;
gemm_ongpu(1,0,m,n,k,1,a,m,b,n,0,c,n);
col2im_ongpu(c, layer.n, out_h, out_w, layer.size, layer.stride, 0, layer.output_gpu+i*layer.n*size);
}
+ add_bias_gpu(layer.output_gpu, layer.biases_gpu, layer.batch, layer.n, size);
activate_array(layer.output_gpu, layer.batch*layer.n*size, layer.activation);
}
-extern "C" void backward_deconvolutional_layer_gpu(deconvolutional_layer layer, float *in, float *delta_gpu)
+extern "C" void backward_deconvolutional_layer_gpu(deconvolutional_layer layer, network_state state)
{
float alpha = 1./layer.batch;
int out_h = deconvolutional_out_height(layer);
@@ -45,29 +50,29 @@
gradient_array(layer.output_gpu, size*layer.n*layer.batch, layer.activation, layer.delta_gpu);
backward_bias(layer.bias_updates_gpu, layer.delta, layer.batch, layer.n, size);
- if(delta_gpu) memset(delta_gpu, 0, layer.batch*layer.h*layer.w*layer.c*sizeof(float));
+ if(state.delta) memset(state.delta, 0, layer.batch*layer.h*layer.w*layer.c*sizeof(float));
for(i = 0; i < layer.batch; ++i){
int m = layer.c;
int n = layer.size*layer.size*layer.n;
int k = layer.h*layer.w;
- float *a = in + i*m*n;
+ float *a = state.input + i*m*n;
float *b = layer.col_image_gpu;
- float *c = layer.filter_updates_gpu;
+ float *c = layer.weight_updates_gpu;
im2col_ongpu(layer.delta_gpu + i*layer.n*size, layer.n, out_h, out_w,
layer.size, layer.stride, 0, b);
gemm_ongpu(0,1,m,n,k,alpha,a,k,b,k,1,c,n);
- if(delta_gpu){
+ if(state.delta){
int m = layer.c;
int n = layer.h*layer.w;
int k = layer.size*layer.size*layer.n;
- float *a = layer.filters_gpu;
+ float *a = layer.weights_gpu;
float *b = layer.col_image_gpu;
- float *c = delta_gpu + i*n*m;
+ float *c = state.delta + i*n*m;
gemm(0,0,m,n,k,1,a,k,b,n,1,c,n);
}
@@ -76,29 +81,29 @@
extern "C" void pull_deconvolutional_layer(deconvolutional_layer layer)
{
- cuda_pull_array(layer.filters_gpu, layer.filters, layer.c*layer.n*layer.size*layer.size);
+ cuda_pull_array(layer.weights_gpu, layer.weights, layer.c*layer.n*layer.size*layer.size);
cuda_pull_array(layer.biases_gpu, layer.biases, layer.n);
- cuda_pull_array(layer.filter_updates_gpu, layer.filter_updates, layer.c*layer.n*layer.size*layer.size);
+ cuda_pull_array(layer.weight_updates_gpu, layer.weight_updates, layer.c*layer.n*layer.size*layer.size);
cuda_pull_array(layer.bias_updates_gpu, layer.bias_updates, layer.n);
}
extern "C" void push_deconvolutional_layer(deconvolutional_layer layer)
{
- cuda_push_array(layer.filters_gpu, layer.filters, layer.c*layer.n*layer.size*layer.size);
+ cuda_push_array(layer.weights_gpu, layer.weights, layer.c*layer.n*layer.size*layer.size);
cuda_push_array(layer.biases_gpu, layer.biases, layer.n);
- cuda_push_array(layer.filter_updates_gpu, layer.filter_updates, layer.c*layer.n*layer.size*layer.size);
+ cuda_push_array(layer.weight_updates_gpu, layer.weight_updates, layer.c*layer.n*layer.size*layer.size);
cuda_push_array(layer.bias_updates_gpu, layer.bias_updates, layer.n);
}
-extern "C" void update_deconvolutional_layer_gpu(deconvolutional_layer layer)
+extern "C" void update_deconvolutional_layer_gpu(deconvolutional_layer layer, float learning_rate, float momentum, float decay)
{
int size = layer.size*layer.size*layer.c*layer.n;
- 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(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(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);
+ axpy_ongpu(size, -decay, layer.weights_gpu, 1, layer.weight_updates_gpu, 1);
+ axpy_ongpu(size, learning_rate, layer.weight_updates_gpu, 1, layer.weights_gpu, 1);
+ scal_ongpu(size, momentum, layer.weight_updates_gpu, 1);
}
--
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