From d4d1f19975eb5789125e43abbd53ed1f73791ae9 Mon Sep 17 00:00:00 2001
From: 1-Ops <2448540804@qq.com>
Date: Sun, 20 Oct 2024 22:03:44 +0800
Subject: [PATCH] Update submission_template01.py

---
 Deep Learning/submission_template01.py | 33 ++++++++++++++++++++++++++
 1 file changed, 33 insertions(+)

diff --git a/Deep Learning/submission_template01.py b/Deep Learning/submission_template01.py
index 1a8ded3..8f9b377 100644
--- a/Deep Learning/submission_template01.py	
+++ b/Deep Learning/submission_template01.py	
@@ -3,12 +3,45 @@
 from torch import nn
 
 def create_model():
+    # submission_template01.py
+import torch.nn as nn
+
+def create_model():
+    model = nn.Sequential(
+        nn.Linear(784, 256),
+        nn.ReLU(),
+        nn.Linear(256, 16),
+        nn.ReLU(),
+        nn.Linear(16, 10)
+    )
+    return model
     # your code here
     # return model instance (None is just a placeholder)
 
     return None
 
 def count_parameters(model):
+    # submission_template01.py
+import torch
+
+def create_model():
+    model = torch.nn.Sequential(
+        torch.nn.Linear(784, 256),
+        torch.nn.ReLU(),
+        torch.nn.Linear(256, 16),
+        torch.nn.ReLU(),
+        torch.nn.Linear(16, 10)
+    )
+    return model
+
+def count_parameters(model):
+    """
+    Подсчет общего количества параметров в модели.
+    
+    :param model:torch.nn.Module - модель, для которой нужно подсчитать параметры
+    :return: int - общее количество параметров в модели
+    """
+    return sum(p.numel() for p in model.parameters() if p.requires_grad)
     # your code here
     # return integer number (None is just a placeholder)