added real test cases

.github/workflows/unit-test.yaml

@@ -0,0 +1,27 @@
+name: Unit Tests
+
+on:
+  push:
+    branches:
+      - "main"
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Setup Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.x
+
+      - name: Install dependencies
+        run: |
+          pip install -r ./requirements.txt
+
+      - name: Run tests
+        run: |
+          python -m unittest ./tests

setup.py

@@ -1,26 +1,21 @@
 from setuptools import setup, find_packages
 
-with open('requirements.txt') as f:
+with open("requirements.txt") as f:
     requirements = f.read().splitlines()
 
 setup(
-    name='yume',
-    version='0.1',
+    name="yume",
+    version="0.1",
     packages=find_packages(),
     install_requires=requirements,
-    entry_points={
-        'console_scripts': [
-            
-        ],
-    },
-    author='Zai',
-    author_email='zaiyellyintaung@gmail.com', 
-    description='Diffusion model implementation with PyTorch',
-    long_description='Detailed description of your project',
-    url='https://github.com/zaibutcooler/yume',
-    classifiers=[
-        'Programming Language :: Python :: 3',
-        'License :: OSI Approved :: MIT License',
-        'Operating System :: OS Independent',
-    ],
+    author="Zai",
+    author_email="zaiyellyintaung@gmail.com",
+    description="LLM trained with Animanga dataset",
+    long_description="Inspired by Andrej Karpathy trained with japanese animanga dataset",
+    url="https://github.com/zaibutcooler/yume",
+    # classifiers=[
+    #     'Programming Language :: Python :: 3',
+    #     'License :: OSI Approved :: MIT License',
+    #     'Operating System :: OS Independent',
+    # ],
 )

tests/test_datasets.py

@@ -0,0 +1,7 @@
+import unittest
+
+class TestDatasets(unittest.TestCase):
+    pass
+
+if __name__ == '__main__':
+    unittest.main()

tests/test_demo.py

@@ -1,25 +0,0 @@
-# test_demo.py
-import unittest
-
-def add_numbers(a, b):
-    return a + b
-
-def multiply_numbers(a, b):
-    return a * b
-
-
-
-class TestDemoFunctions(unittest.TestCase):
-
-    def test_add_numbers(self):
-        self.assertEqual(add_numbers(2, 3), 5)
-        self.assertEqual(add_numbers(-1, 1), 0)
-        # Add more test cases as needed
-
-    def test_multiply_numbers(self):
-        self.assertEqual(multiply_numbers(2, 3), 6)
-        self.assertEqual(multiply_numbers(-1, 1), -1)
-        # Add more test cases as needed
-
-if __name__ == '__main__':
-    unittest.main()

tests/test_pretrained.py

@@ -0,0 +1,11 @@
+import unittest
+
+class TestPretrained(unittest.TestCase):
+    def test_download():
+        pass
+    
+    def test_generation():
+        pass
+
+if __name__ == '__main__':
+    unittest.main()

tests/test_tokenizer.py

@@ -0,0 +1,15 @@
+import unittest
+
+class TestTokenizer(unittest.TestCase):
+    def test_encode():
+        pass
+    
+    def test_decode():
+        pass
+    
+    def test_equal_result():
+        pass
+    
+    
+if __name__ == '__main__':
+    unittest.main()

tests/test_transformer.py

@@ -0,0 +1,12 @@
+import unittest
+
+class TestTransformer(unittest.TestCase):
+    def test_loading_model():
+        pass
+    
+    def test_parameters():
+        pass
+    
+
+if __name__ == '__main__':
+    unittest.main()

yume/__init__.py

@@ -1 +1 @@
-from yume import Yume
+from yume import Yume

yume/config.py

@@ -1,5 +1,23 @@
+
 class Config:
-    def __init__(self) -> None:
-        pass
+    def __init__(self,num_epoch:int,
+                     block_sized = 1024,
+    vocab_sized = 50304,
+    n_layer = 12,
+    n_head = 12,
+    n_embd = 768,
+    dropout = 0.0,
+    bias = True,
+                 
+                 ) -> None:
+        self.num_epoch = num_epoch
+        self.block_sized = 1024
+        self.vocab_sized = 50304 
+        self.n_layerd = 12
+        self.n_headd = 12
+        self.n_embdd = 768
+        self.dropout = 0.0
+        self.bias = True
+        
 
 config = Config()

yume/models.py

@@ -2,7 +2,29 @@ import torch
 from torch import nn
 import torch.nn.functional as F
 
-class Yume(nn.Module):
+class SelfAttention(nn.Module):
+    def __init__(self, ) -> None:
+        super().__init__()
+        
+    def forward(self):
+        pass
+
+class MLP(nn.Module):
+    def __init__(self, ) -> None:
+        super().__init__()
+        
+    def forward(self):
+        pass
+
+class Block(nn.Module):
+    def __init__(self, ) -> None:
+        super().__init__()
+        
+    def forward(self):
+        pass
+    
+
+class GPT(nn.Module):
     def __init__(self, config):
         super().__init__()
 

yume/tokenizer.py

@@ -1,3 +1,5 @@
 class Tokenizer:
     def __init__(self):
-        pass
+        pass
+    
+    

yume/utils.py

@@ -1,2 +1,8 @@
-def log(text):
-    pass
+def encode(text):
+    pass
+
+def decode(text):
+    pass
+
+def transform_data(data):
+    pass

yume/yume.py

@@ -2,12 +2,14 @@ import torch
 from torch import nn
 import torch.nn.functional as F
 from config import Config
+from .models import GPT
 
 config = Config()
 
 class Yume:
     def __init__(self, config):
         super().__init__()
+        self.model = GPT(config=config)
 
     def train(self):
         pass