triple dense example

tests/test.cpp

@@ -1,24 +1,40 @@
 #include<iostream>
 #include "Layer.h"
 
+const char *input_bin   = "../tests/input.bin";
+const char *d0_bin      = "../tests/dense0.bin";
+const char *d0_bias_bin = "../tests/dense0.bias.bin";
+const char *d1_bin      = "../tests/dense1.bin";
+const char *d1_bias_bin = "../tests/dense1.bias.bin";
+const char *d2_bin      = "../tests/dense2.bin";
+const char *d2_bias_bin = "../tests/dense2.bias.bin";
+
 int main() {
 
+    // Network layout
     tkDNN::Network net;
-    tkDNN::dataDim_t dim(1, 8, 1, 1);
-    tkDNN::Dense      d(&net, dim, 2, "../tests/dense.bin", "../tests/dense.bias.bin");
-    tkDNN::Activation a(&net, d.output_dim, tkDNN::ACTIVATION_ELU);
-
+    tkDNN::dataDim_t dim(1, 512, 1, 1);
+    tkDNN::Dense      d0 (&net, dim,           256, d0_bin, d0_bias_bin);
+    tkDNN::Activation a0 (&net, d0.output_dim, tkDNN::ACTIVATION_ELU);
+    tkDNN::Dense      d1 (&net, a0.output_dim, 32,  d1_bin, d1_bias_bin);
+    tkDNN::Activation a1 (&net, d1.output_dim, tkDNN::ACTIVATION_ELU);
+    tkDNN::Dense      d2 (&net, a1.output_dim, 2,   d2_bin, d2_bias_bin);
+    
+    // Load input
     value_type *data;
     value_type *input_h;
-    readBinaryFile("../tests/input.bin", 8, &input_h, &data);
-
-    dim.print();
-    data = d.infer(dim, data);
-    dim.print();
-    data = a.infer(dim, data);
-    dim.print();
+    readBinaryFile(input_bin, dim.tot(), &input_h, &data);
 
+    dim.print(); //print initial dimension
+    
+    // Inference
+    data = d0.infer(dim, data); dim.print();
+    data = a0.infer(dim, data); dim.print();
+    data = d1.infer(dim, data); dim.print();
+    data = a1.infer(dim, data); dim.print();
+    data = d2.infer(dim, data); dim.print();
+  
+    // Print result
     printDeviceVector(dim.tot(), data);
-
     return 0;
 }