From 68213b835b9f15cb449ad2037a8b51c17a3de07b Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 14 Mar 2016 22:10:14 +0000
Subject: [PATCH] Makefile
---
src/blas_kernels.cu | 49 ++++++++++++++++++++++++++++++++++++-------------
1 files changed, 36 insertions(+), 13 deletions(-)
diff --git a/src/blas_kernels.cu b/src/blas_kernels.cu
index 61db29f..98366f8 100644
--- a/src/blas_kernels.cu
+++ b/src/blas_kernels.cu
@@ -15,7 +15,7 @@
if (index >= N) return;
int f = (index/spatial)%filters;
- x[index] = (x[index] - mean[f])/(sqrt(variance[f]) + .00001f);
+ x[index] = (x[index] - mean[f])/(sqrt(variance[f]) + .000001f);
}
__global__ void normalize_delta_kernel(int N, float *x, float *mean, float *variance, float *mean_delta, float *variance_delta, int batch, int filters, int spatial, float *delta)
@@ -24,7 +24,7 @@
if (index >= N) return;
int f = (index/spatial)%filters;
- delta[index] = delta[index] * 1./(sqrt(variance[f]) + .00001f) + variance_delta[f] * 2. * (x[index] - mean[f]) / (spatial * batch) + mean_delta[f]/(spatial*batch);
+ delta[index] = delta[index] * 1./(sqrt(variance[f]) + .000001f) + variance_delta[f] * 2. * (x[index] - mean[f]) / (spatial * batch) + mean_delta[f]/(spatial*batch);
}
extern "C" void normalize_delta_gpu(float *x, float *mean, float *variance, float *mean_delta, float *variance_delta, int batch, int filters, int spatial, float *delta)
@@ -46,7 +46,7 @@
variance_delta[i] += delta[index]*(x[index] - mean[i]);
}
}
- variance_delta[i] *= -.5 * pow(variance[i] + .00001f, (float)(-3./2.));
+ variance_delta[i] *= -.5 * pow(variance[i] + .000001f, (float)(-3./2.));
}
__global__ void accumulate_kernel(float *x, int n, int groups, float *sum)
@@ -83,7 +83,7 @@
for(i = 0; i < threads; ++i){
mean_delta[filter] += local[i];
}
- mean_delta[filter] *= (-1./sqrt(variance[filter] + .00001f));
+ mean_delta[filter] *= (-1./sqrt(variance[filter] + .000001f));
}
}
@@ -111,7 +111,7 @@
for(i = 0; i < threads; ++i){
variance_delta[filter] += local[i];
}
- variance_delta[filter] *= -.5 * pow(variance[filter] + .00001f, (float)(-3./2.));
+ variance_delta[filter] *= -.5 * pow(variance[filter] + .000001f, (float)(-3./2.));
}
}
@@ -128,7 +128,7 @@
mean_delta[i] += delta[index];
}
}
- mean_delta[i] *= (-1./sqrt(variance[i] + .00001f));
+ mean_delta[i] *= (-1./sqrt(variance[i] + .000001f));
}
extern "C" void mean_delta_gpu(float *delta, float *variance, int batch, int filters, int spatial, float *mean_delta)
@@ -167,7 +167,7 @@
__global__ void variance_kernel(float *x, float *mean, int batch, int filters, int spatial, float *variance)
{
- float scale = 1./(batch * spatial);
+ float scale = 1./(batch * spatial - 1);
int j,k;
int i = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
if (i >= filters) return;
@@ -288,7 +288,7 @@
for(i = 0; i < threads; ++i){
variance[filter] += local[i];
}
- variance[filter] /= spatial * batch;
+ variance[filter] /= (spatial * batch - 1);
}
}
@@ -410,18 +410,41 @@
check_error(cudaPeekAtLastError());
}
-__global__ void smooth_l1_kernel(int n, float *pred, float *truth, float *delta)
+__global__ void smooth_l1_kernel(int n, float *pred, float *truth, float *delta, float *error)
{
int i = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
if(i < n){
float diff = truth[i] - pred[i];
- if(abs(diff) > 1) delta[i] = diff;
- else delta[i] = (diff > 0) ? 1 : -1;
+ float abs_val = abs(diff);
+ if(abs_val < 1) {
+ error[i] = diff * diff;
+ delta[i] = diff;
+ }
+ else {
+ error[i] = 2*abs_val - 1;
+ delta[i] = (diff < 0) ? -1 : 1;
+ }
}
}
-extern "C" void smooth_l1_gpu(int n, float *pred, float *truth, float *delta)
+extern "C" void smooth_l1_gpu(int n, float *pred, float *truth, float *delta, float *error)
{
- smooth_l1_kernel<<<cuda_gridsize(n), BLOCK>>>(n, pred, truth, delta);
+ smooth_l1_kernel<<<cuda_gridsize(n), BLOCK>>>(n, pred, truth, delta, error);
+ check_error(cudaPeekAtLastError());
+}
+
+__global__ void l2_kernel(int n, float *pred, float *truth, float *delta, float *error)
+{
+ int i = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;
+ if(i < n){
+ float diff = truth[i] - pred[i];
+ error[i] = diff * diff; //I know this is technically wrong, deal with it.
+ delta[i] = diff;
+ }
+}
+
+extern "C" void l2_gpu(int n, float *pred, float *truth, float *delta, float *error)
+{
+ l2_kernel<<<cuda_gridsize(n), BLOCK>>>(n, pred, truth, delta, error);
check_error(cudaPeekAtLastError());
}
--
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