im trying

cnn.c

@@ -0,0 +1,85 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+
+typedef enum {
+  input,
+  conv,
+  max_pool,
+  fully_connected,
+  output
+} ltype;
+
+typedef enum {
+  relu,
+  softmax,
+  sigmoid,
+  tanh
+} activation;
+
+typedef struct {
+  int filters;
+  int filter_h;
+  int filter_w;
+  int stride;
+  int zeropadding; // amount of zeropadding (1 = one layer... etc.)
+} convparams;
+
+typedef struct {
+  int pool_height; // height and width of the pooling window
+  int pool_width;
+} poolparams;
+
+typedef struct {
+  ltype type;
+  activation atype;
+  
+  int input_height;
+  int input_width;
+  int input_channels;
+
+  int output_height;
+  int output_width;
+  int output_channels;
+
+  union {
+    convparams layerconv;
+    poolparams layerpool;
+  } params;  
+
+  float* weights;
+  float* biases;
+} Layer;
+
+Layer* createlayer(ltype type, int height, int width, int channels, void* params) {
+  Layer* layer = (Layer*)malloc(sizeof(Layer));
+  layer->type = type;
+  layer->input_height = height;
+  layer->input_width = width;
+  layer->input_channels = channels;
+
+  layer->weights = NULL;
+  layer->biases = NULL;
+
+  switch(type) {
+    case input: {
+      layer->output_height = input_height;
+      layer->output_width = input_width;
+      layer->output_channels = input_channels;
+      layer->activation = relu;
+      break;
+    }
+    case conv: {
+      convparams* cparams = (convparams*)params;
+      layer->params.layerconv = *cparams;
+      layer->activation = relu;
+
+      // https://cs231n.github.io/convolutional-networks/#pool - formula to find dimensions
+      layer->output_height = ((input_height + 2*conv_params->zero_padding - conv_params->filter_height) / conv_params->stride_height) + 1;
+      layer->output_width = ((input_width + 2*conv_params->zero_padding - conv_params->filter_width) / conv_params->stride_width) + 1;
+
+      layer->output_channels = convparams->filters;
+      
+
+    }
+}