Implement pytorch weights export

tools/export_model_weights.py

@@ -0,0 +1,28 @@
+import torch
+import struct
+
+def export_model_weights(model: torch.nn.Module, filename):
+    with open(filename, 'wb') as f:
+
+        header = ""
+        offset = 0
+
+
+        for name, param in model.named_parameters():
+            if 'weight' not in name and 'bias' not in name:
+                continue
+
+            tensor_values = param.flatten().tolist()
+            tensor_bytes = struct.pack('f' * len(tensor_values), *tensor_values)
+
+            tensor_size = param.numel()
+
+            header += f"{name},{tensor_size},{offset}\n"
+            
+            offset += len(tensor_bytes)
+
+            f.write(tensor_bytes)
+
+        f.seek(0)
+        f.write(struct.pack('q', len(header)))            
+        f.write(header.encode('utf-8'))

tools/model_test.py

@@ -1,6 +1,8 @@
 import torch
 import utils
 
+from export_model_weights import export_model_weights
+
 class TestModel(torch.nn.Module):
 
     def __init__(self, *args, **kwargs) -> None:
@@ -121,3 +123,5 @@ if __name__ == "__main__":
     ]).reshape(2, 6, 6)
     out = model(input)
     utils.print_cpp_vector(out)
+
+    export_model_weights(model, "test/resources/model.bin")