From: Brendan Hansen <brendan.f.hansen@gmail.com>
Date: Sat, 23 Jan 2021 16:33:10 +0000 (-0600)
Subject: using new binary reader implementation
X-Git-Url: https://git.brendanfh.com/?a=commitdiff_plain;h=a28adee100e5bfab41db3f473417ec9cb59f9962;p=onyx-mnist.git

using new binary reader implementation
---

diff --git a/src/mnist.onyx b/src/mnist.onyx
index 8e7d6a1..be8522d 100644
--- a/src/mnist.onyx
+++ b/src/mnist.onyx
@@ -100,7 +100,7 @@ main :: (args: [] cstr) {
     // main_allocator := context.allocator;
     // context.allocator = alloc.log.logging_allocator(^main_allocator);
 
-    nn := neural_net_load("data/dummy.nn");
+    nn := neural_net_load("data/test_1.nn");
     // nn := make_neural_net(28 * 28, 512, 256, 100, 10);
     defer neural_net_free(^nn);
 
diff --git a/src/neuralnet.onyx b/src/neuralnet.onyx
index 89dd30b..c427793 100644
--- a/src/neuralnet.onyx
+++ b/src/neuralnet.onyx
@@ -201,13 +201,13 @@ neural_net_save :: (use nn: ^NeuralNet, filename: str) {
     writer := io.binary_writer_make(^output_file);
 
     // Magic string
-    io.binary_write_i32(^writer, Onyx_NN_Magic_Number);
+    io.binary_write(^writer, i32, Onyx_NN_Magic_Number);
 
     // Number of layers
-    io.binary_write_i32(^writer, layers.count);
+    io.binary_write(^writer, i32, layers.count);
 
     for ^layer: layers {
-        io.binary_write_i32(^writer, layer.neurons.count);
+        io.binary_write(^writer, i32, layer.neurons.count);
 
         io.binary_write_byte(^writer, cast(u8) layer.is_input);
         if layer.is_input do continue;
@@ -232,10 +232,10 @@ neural_net_load :: (filename: str) -> NeuralNet {
 
     reader := io.binary_reader_make(^input_file);
 
-    magic_number := io.binary_read_i32(^reader);
+    magic_number := io.binary_read(^reader, i32);
     assert(magic_number == Onyx_NN_Magic_Number, "Magic number did not match!");
 
-    num_layers := io.binary_read_i32(^reader);
+    num_layers := io.binary_read(^reader, i32);
 
     nn : NeuralNet;
     neural_net_init(^nn, num_layers);
@@ -244,7 +244,7 @@ neural_net_load :: (filename: str) -> NeuralNet {
     prev_layer_size := 0;
 
     for l: num_layers {
-        layer_size := io.binary_read_i32(^reader);
+        layer_size := io.binary_read(^reader, i32);
         is_input   := cast(bool) io.binary_read_byte(^reader);
 
         layer_init(^nn.layers[l], layer_size, prev_layer_size, allocator = layer_allocator, allocate_weights_and_biases = false);