Make tests pass

Configuring VS Code for Python is well explained...

in the extension documentation. I should have read that first

Author: stephenjfox

.gitignore

@@ -52,17 +52,6 @@ coverage.xml
 *.mo
 *.pot
 
-# Django stuff:
-*.log
-local_settings.py
-db.sqlite3
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
 
 # Sphinx documentation
 docs/_build/
@@ -80,12 +69,6 @@ ipython_config.py
 # pyenv
 .python-version
 
-# celery beat schedule file
-celerybeat-schedule
-
-# SageMath parsed files
-*.sage.py
-
 # Environments
 .env
 .venv
@@ -95,13 +78,6 @@ ENV/
 env.bak/
 venv.bak/
 
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
 # mkdocs documentation
 /site
 
@@ -111,3 +87,4 @@ venv.bak/
 dmypy.json
 
 *~demo.*
+.vscode/**

demo.py

@@ -13,6 +13,8 @@ def main():
     # do one pass through the algorithm
     modified = morph.once(my_model)
 
+    print(modified) # proof that the thing wasn't tampered with
+
     my_dataloader = DataLoader(TensorDataset(torch.randn(2, 28, 28)))
 
     # get back the class that will do work

morph/.vscode/settings.json

@@ -9,6 +9,8 @@ def make_children_list(children_or_named_children):
     """
     return [c for c in children_or_named_children]
 
+#################### NEW LAYERS ####################
+
 def new_layer(base_layer: nn.Module, type_name: str, in_dim: int, out_dim: int) -> nn.Module:
 
     has_bias = layer_has_bias(base_layer)

morph/nn/utils.py

@@ -1,8 +1,7 @@
 import torch.nn as nn
 import unittest
 
-from utils import new_input_layer, new_output_layer
-
+from .utils import new_input_layer, new_output_layer
 
 class TestLayer(unittest.TestCase):
     def test_new_input_layer_only_touches_output_Linear(self):

morph/nn/utils_test.py

@@ -14,7 +14,6 @@
     author_email='stevethecoder34@gmail.com',  # Type in your E-Mail
     # Provide either the link to your github or to your website
     url='https://github.com/stephenjfox/Morph.py',
-    # I explain this later on
     download_url='https://github.com/stephenjfox/Morph.py/archive/v0.0.6.tar.gz',
     keywords=[
         'machine learning', 'deep learning', 'nas', 'architecture',