From 336a19f14550ab1adbb0d9599284ac525fb6a5e0 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Thu, 08 Sep 2016 05:44:41 +0000
Subject: [PATCH] slight changes to default demo settings

---
 src/convolutional_layer.c |  149 ++++++++++++++++++++++++-------------------------
 1 files changed, 74 insertions(+), 75 deletions(-)

diff --git a/src/convolutional_layer.c b/src/convolutional_layer.c
index 4014a24..ad2d8a5 100644
--- a/src/convolutional_layer.c
+++ b/src/convolutional_layer.c
@@ -70,18 +70,12 @@
 
 int convolutional_out_height(convolutional_layer l)
 {
-    int h = l.h;
-    if (!l.pad) h -= l.size;
-    else h -= 1;
-    return h/l.stride + 1;
+    return (l.h + 2*l.pad - l.size) / l.stride + 1;
 }
 
 int convolutional_out_width(convolutional_layer l)
 {
-    int w = l.w;
-    if (!l.pad) w -= l.size;
-    else w -= 1;
-    return w/l.stride + 1;
+    return (l.w + 2*l.pad - l.size) / l.stride + 1;
 }
 
 image get_convolutional_image(convolutional_layer l)
@@ -104,36 +98,37 @@
 
 size_t get_workspace_size(layer l){
 #ifdef CUDNN
-    size_t most = 0;
-    size_t s = 0;
-    cudnnGetConvolutionForwardWorkspaceSize(cudnn_handle(),
-            l.srcTensorDesc,
-            l.filterDesc,
-            l.convDesc,
-            l.dstTensorDesc,
-            l.fw_algo,
-            &s);
-    if (s > most) most = s;
-    cudnnGetConvolutionBackwardFilterWorkspaceSize(cudnn_handle(),
-            l.srcTensorDesc,
-            l.ddstTensorDesc,
-            l.convDesc,
-            l.dfilterDesc,
-            l.bf_algo,
-            &s);
-    if (s > most) most = s;
-    cudnnGetConvolutionBackwardDataWorkspaceSize(cudnn_handle(),
-            l.filterDesc,
-            l.ddstTensorDesc,
-            l.convDesc,
-            l.dsrcTensorDesc,
-            l.bd_algo,
-            &s);
-    if (s > most) most = s;
-    return most;
-#else
+    if(gpu_index >= 0){
+        size_t most = 0;
+        size_t s = 0;
+        cudnnGetConvolutionForwardWorkspaceSize(cudnn_handle(),
+                l.srcTensorDesc,
+                l.filterDesc,
+                l.convDesc,
+                l.dstTensorDesc,
+                l.fw_algo,
+                &s);
+        if (s > most) most = s;
+        cudnnGetConvolutionBackwardFilterWorkspaceSize(cudnn_handle(),
+                l.srcTensorDesc,
+                l.ddstTensorDesc,
+                l.convDesc,
+                l.dfilterDesc,
+                l.bf_algo,
+                &s);
+        if (s > most) most = s;
+        cudnnGetConvolutionBackwardDataWorkspaceSize(cudnn_handle(),
+                l.filterDesc,
+                l.ddstTensorDesc,
+                l.convDesc,
+                l.dsrcTensorDesc,
+                l.bd_algo,
+                &s);
+        if (s > most) most = s;
+        return most;
+    }
+    #endif
     return (size_t)l.out_h*l.out_w*l.size*l.size*l.c*sizeof(float);
-#endif
 }
 
 #ifdef GPU
@@ -147,8 +142,7 @@
     cudnnSetTensor4dDescriptor(l->srcTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, l->batch, l->c, l->h, l->w); 
     cudnnSetTensor4dDescriptor(l->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, l->batch, l->out_c, l->out_h, l->out_w); 
     cudnnSetFilter4dDescriptor(l->filterDesc, CUDNN_DATA_FLOAT, CUDNN_TENSOR_NCHW, l->n, l->c, l->size, l->size); 
-    int padding = l->pad ? l->size/2 : 0;
-    cudnnSetConvolution2dDescriptor(l->convDesc, padding, padding, l->stride, l->stride, 1, 1, CUDNN_CROSS_CORRELATION);
+    cudnnSetConvolution2dDescriptor(l->convDesc, l->pad, l->pad, l->stride, l->stride, 1, 1, CUDNN_CROSS_CORRELATION);
     cudnnGetConvolutionForwardAlgorithm(cudnn_handle(),
             l->srcTensorDesc,
             l->filterDesc,
@@ -177,7 +171,7 @@
 #endif
 #endif
 
-convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int pad, ACTIVATION activation, int batch_normalize, int binary, int xnor)
+convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int padding, ACTIVATION activation, int batch_normalize, int binary, int xnor)
 {
     int i;
     convolutional_layer l = {0};
@@ -192,7 +186,7 @@
     l.batch = batch;
     l.stride = stride;
     l.size = size;
-    l.pad = pad;
+    l.pad = padding;
     l.batch_normalize = batch_normalize;
 
     l.filters = calloc(c*n*size*size, sizeof(float));
@@ -240,49 +234,51 @@
     }
 
 #ifdef GPU
-    l.filters_gpu = cuda_make_array(l.filters, c*n*size*size);
-    l.filter_updates_gpu = cuda_make_array(l.filter_updates, c*n*size*size);
+    if(gpu_index >= 0){
+        l.filters_gpu = cuda_make_array(l.filters, c*n*size*size);
+        l.filter_updates_gpu = cuda_make_array(l.filter_updates, c*n*size*size);
 
-    l.biases_gpu = cuda_make_array(l.biases, n);
-    l.bias_updates_gpu = cuda_make_array(l.bias_updates, n);
+        l.biases_gpu = cuda_make_array(l.biases, n);
+        l.bias_updates_gpu = cuda_make_array(l.bias_updates, n);
 
-    l.scales_gpu = cuda_make_array(l.scales, n);
-    l.scale_updates_gpu = cuda_make_array(l.scale_updates, n);
+        l.scales_gpu = cuda_make_array(l.scales, n);
+        l.scale_updates_gpu = cuda_make_array(l.scale_updates, n);
 
-    l.delta_gpu = cuda_make_array(l.delta, l.batch*out_h*out_w*n);
-    l.output_gpu = cuda_make_array(l.output, l.batch*out_h*out_w*n);
+        l.delta_gpu = cuda_make_array(l.delta, l.batch*out_h*out_w*n);
+        l.output_gpu = cuda_make_array(l.output, l.batch*out_h*out_w*n);
 
-    if(binary){
-        l.binary_filters_gpu = cuda_make_array(l.filters, c*n*size*size);
-    }
-    if(xnor){
-        l.binary_filters_gpu = cuda_make_array(l.filters, c*n*size*size);
-        l.binary_input_gpu = cuda_make_array(0, l.inputs*l.batch);
-    }
+        if(binary){
+            l.binary_filters_gpu = cuda_make_array(l.filters, c*n*size*size);
+        }
+        if(xnor){
+            l.binary_filters_gpu = cuda_make_array(l.filters, c*n*size*size);
+            l.binary_input_gpu = cuda_make_array(0, l.inputs*l.batch);
+        }
 
-    if(batch_normalize){
-        l.mean_gpu = cuda_make_array(l.mean, n);
-        l.variance_gpu = cuda_make_array(l.variance, n);
+        if(batch_normalize){
+            l.mean_gpu = cuda_make_array(l.mean, n);
+            l.variance_gpu = cuda_make_array(l.variance, n);
 
-        l.rolling_mean_gpu = cuda_make_array(l.mean, n);
-        l.rolling_variance_gpu = cuda_make_array(l.variance, n);
+            l.rolling_mean_gpu = cuda_make_array(l.mean, n);
+            l.rolling_variance_gpu = cuda_make_array(l.variance, n);
 
-        l.mean_delta_gpu = cuda_make_array(l.mean, n);
-        l.variance_delta_gpu = cuda_make_array(l.variance, n);
+            l.mean_delta_gpu = cuda_make_array(l.mean, n);
+            l.variance_delta_gpu = cuda_make_array(l.variance, n);
 
-        l.x_gpu = cuda_make_array(l.output, l.batch*out_h*out_w*n);
-        l.x_norm_gpu = cuda_make_array(l.output, l.batch*out_h*out_w*n);
-    }
+            l.x_gpu = cuda_make_array(l.output, l.batch*out_h*out_w*n);
+            l.x_norm_gpu = cuda_make_array(l.output, l.batch*out_h*out_w*n);
+        }
 #ifdef CUDNN
-    cudnnCreateTensorDescriptor(&l.srcTensorDesc);
-    cudnnCreateTensorDescriptor(&l.dstTensorDesc);
-    cudnnCreateFilterDescriptor(&l.filterDesc);
-    cudnnCreateTensorDescriptor(&l.dsrcTensorDesc);
-    cudnnCreateTensorDescriptor(&l.ddstTensorDesc);
-    cudnnCreateFilterDescriptor(&l.dfilterDesc);
-    cudnnCreateConvolutionDescriptor(&l.convDesc);
-    cudnn_convolutional_setup(&l);
+        cudnnCreateTensorDescriptor(&l.srcTensorDesc);
+        cudnnCreateTensorDescriptor(&l.dstTensorDesc);
+        cudnnCreateFilterDescriptor(&l.filterDesc);
+        cudnnCreateTensorDescriptor(&l.dsrcTensorDesc);
+        cudnnCreateTensorDescriptor(&l.ddstTensorDesc);
+        cudnnCreateFilterDescriptor(&l.dfilterDesc);
+        cudnnCreateConvolutionDescriptor(&l.convDesc);
+        cudnn_convolutional_setup(&l);
 #endif
+    }
 #endif
     l.workspace_size = get_workspace_size(l);
     l.activation = activation;
@@ -301,6 +297,9 @@
             l.filters[i*l.c*l.size*l.size + j] *= scale;
         }
         l.biases[i] -= l.rolling_mean[i] * scale;
+        l.scales[i] = 1;
+        l.rolling_mean[i] = 0;
+        l.rolling_variance[i] = 1;
     }
 }
 
@@ -434,7 +433,7 @@
        }
      */
 
-    if(l.xnor ){
+    if(l.xnor){
         binarize_filters(l.filters, l.n, l.c*l.size*l.size, l.binary_filters);
         swap_binary(&l);
         binarize_cpu(state.input, l.c*l.h*l.w*l.batch, l.binary_input);

--
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