From 913d355ec1cf34aad71fdd75202fc3b0309e63a0 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Thu, 28 Jan 2016 20:30:38 +0000
Subject: [PATCH] lots of stuff
---
src/convolutional_kernels.cu | 42 ++++++++++++++++++++++++++++++++++++------
1 files changed, 36 insertions(+), 6 deletions(-)
diff --git a/src/convolutional_kernels.cu b/src/convolutional_kernels.cu
index a64a499..4fdc1a1 100644
--- a/src/convolutional_kernels.cu
+++ b/src/convolutional_kernels.cu
@@ -12,6 +12,21 @@
#include "cuda.h"
}
+__global__ void binarize_filters_kernel(float *filters, int n, int size, float *binary)
+{
+ int f = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
+ if (f >= n) return;
+ int i = 0;
+ float mean = 0;
+ for(i = 0; i < size; ++i){
+ mean += abs(filters[f*size + i]);
+ }
+ mean = mean / size;
+ for(i = 0; i < size; ++i){
+ binary[f*size + i] = (filters[f*size + i] > 0) ? mean : -mean;
+ }
+}
+
__global__ void scale_bias_kernel(float *output, float *biases, int n, int size)
{
int offset = blockIdx.x * blockDim.x + threadIdx.x;
@@ -50,6 +65,12 @@
}
}
+void binarize_filters_gpu(float *filters, int n, int size, float *mean)
+{
+ binarize_filters_kernel<<<cuda_gridsize(n), BLOCK>>>(filters, n, size, mean);
+ check_error(cudaPeekAtLastError());
+}
+
void backward_scale_gpu(float *x_norm, float *delta, int batch, int n, int size, float *scale_updates)
{
backward_scale_kernel<<<n, BLOCK>>>(x_norm, delta, batch, n, size, scale_updates);
@@ -100,6 +121,13 @@
check_error(cudaPeekAtLastError());
}
+void swap_binary(convolutional_layer l)
+{
+ float *swap = l.filters_gpu;
+ l.filters_gpu = l.binary_filters_gpu;
+ l.binary_filters_gpu = swap;
+}
+
void forward_convolutional_layer_gpu(convolutional_layer l, network_state state)
{
int i;
@@ -109,6 +137,11 @@
convolutional_out_width(l);
fill_ongpu(l.outputs*l.batch, 0, l.output_gpu, 1);
+ if(l.binary){
+ binarize_filters_gpu(l.filters_gpu, l.n, l.c*l.size*l.size, l.binary_filters_gpu);
+ swap_binary(l);
+ }
+
for(i = 0; i < l.batch; ++i){
im2col_ongpu(state.input + i*l.c*l.h*l.w, l.c, l.h, l.w, l.size, l.stride, l.pad, l.col_image_gpu);
float * a = l.filters_gpu;
@@ -122,12 +155,6 @@
fast_mean_gpu(l.output_gpu, l.batch, l.n, l.out_h*l.out_w, l.mean_gpu);
fast_variance_gpu(l.output_gpu, l.mean_gpu, l.batch, l.n, l.out_h*l.out_w, l.variance_gpu);
- /*
- cuda_pull_array(l.variance_gpu, l.mean, 1);
- printf("%f\n", l.mean[0]);
- */
-
-
scal_ongpu(l.n, .95, l.rolling_mean_gpu, 1);
axpy_ongpu(l.n, .05, l.mean_gpu, 1, l.rolling_mean_gpu, 1);
scal_ongpu(l.n, .95, l.rolling_variance_gpu, 1);
@@ -145,6 +172,7 @@
add_bias_gpu(l.output_gpu, l.biases_gpu, l.batch, l.n, n);
activate_array_ongpu(l.output_gpu, m*n*l.batch, l.activation);
+ if(l.binary) swap_binary(l);
}
void backward_convolutional_layer_gpu(convolutional_layer l, network_state state)
@@ -178,6 +206,7 @@
gemm_ongpu(0,1,m,n,k,1,a + i*m*k,k,b,k,1,c,n);
if(state.delta){
+ if(l.binary) swap_binary(l);
float * a = l.filters_gpu;
float * b = l.delta_gpu;
float * c = l.col_image_gpu;
@@ -185,6 +214,7 @@
gemm_ongpu(1,0,n,k,m,1,a,n,b + i*k*m,k,0,c,k);
col2im_ongpu(l.col_image_gpu, l.c, l.h, l.w, l.size, l.stride, l.pad, state.delta + i*l.c*l.h*l.w);
+ if(l.binary) swap_binary(l);
}
}
}
--
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