cleaned up autogen code so also runs in notebook

app.py

@@ -1,28 +1,31 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../02_production.ipynb.
 
 # %% auto 0
-__all__ = ['categories', 'learn', 'image', 'label', 'file_list', 'stem', 'examples', 'intf', 'classify_image']
+__all__ = ['categories', 'model', 'stem', 'learn', 'image', 'label', 'file_list', 'examples', 'intf', 'classify_image']
 
-# %% ../02_production.ipynb 53
+# %% ../02_production.ipynb 52
 from fastai.vision.all import *
 import gradio as gr
 
-# %% ../02_production.ipynb 55
+# %% ../02_production.ipynb 54
 categories = ('black','grizzly','teddy')
 
-# %% ../02_production.ipynb 56
+# %% ../02_production.ipynb 57
 def classify_image(img):
     pred,idx, probs = learn.predict(img)
     return dict(zip(categories, map(float,probs)))
 
-# %% ../02_production.ipynb 58
-learn = load_learner('model.pkl')
+# %% ../02_production.ipynb 59
+model = 'model.pkl'
+stem = 'examples/'
 
+# %% ../02_production.ipynb 61
+learn = load_learner(model)
 image = gr.components.Image(width=224, height=224)
 label = gr.components.Label()
 
 file_list = ['grizzly.jpg', 'black.jpg', 'teddy.jpg']
-stem = 'examples/'
+
 examples = list(map(lambda x: stem + x, file_list))
 
 intf = gr.Interface(fn=classify_image, inputs=image, outputs=label,examples=examples)