added example to the readme

Author: Duncan Blythe

README.md

@@ -1,2 +1,92 @@
 # torchapply
-Apply a torch model to some datapoints
+Apply a torch model to some datapoints. 
+
+Here's an example:
+
+```python
+import torch
+from torch import tensor
+
+
+class Main(torch.nn.Module):
+    def __init__(self, model_0, model_1):
+        super().__init__()
+        self.model_0 = model_0
+        self.model_1 = model_1
+        self.dictionary = {'apple': 0, 'orange': 1, 'pear': 2}
+
+    def preprocess(self, arg):
+        return [
+            {
+                'a': {'b': self.dictionary[arg[0]['a']['b']]},
+                'c': self.dictionary[arg[0]['c']]
+            },
+            torch.tensor([self.dictionary[x] for x in arg[1]])
+        ]
+
+    def forward(self, args):
+        return self.model_0(args[0]), self.model_1(args[1])
+      
+    def postprocess(self, arg):
+        total = [arg[0]['a']['b'].sum(), arg[0]['c'].sum(), arg[1].sum()]
+        return {'score': sum(total), 'decision': sum(total) > 0}
+        
+
+class ModelA(torch.nn.Module):
+    def forward(self, args):
+        return {'b': torch.randn(args['b'].shape[0], 10)}
+
+
+class ModelC(torch.nn.Module):
+    def forward(self, args):
+        return torch.randn(args.shape[0], 10)
+
+
+class Model1(torch.nn.Module):
+    def forward(self, args):
+        return torch.randn(args.shape[0], 10)
+
+
+class Model0(torch.nn.Module):
+    def __init__(self, model_a, model_c):
+        super().__init__()
+        self.model_a = model_a
+        self.model_c = model_c
+
+    def forward(self, args):
+        return {'a': self.model_a(args['a']), 'c': self.model_c(args['c'])}
+
+
+model = Main(
+    model_0=Model0(
+        model_a=ModelA(),
+        model_c=ModelC()
+    ),
+    model_1=Model1()
+)
+```
+
+Apply to a single datapoint:
+
+```python
+from torchapply import apply_model
+
+apply_model(
+   model, 
+   ({'a': {'b': 'orange'}, 'c': 'pear'}, ('apple', 'apple')),
+   single=True
+)
+```
+
+Apply to multiple datapoints:
+
+```python
+from torchapply import apply_model
+
+apply_model(
+    model,
+    [({'a': {'b': 'orange'}, 'c': 'pear'}, ('apple', 'apple')) for _ in range(10)],
+    single=False
+)
+```
+

torchapply/version.py

@@ -1 +1 @@
-__version__ = "0.0.2"
+__version__ = "0.0.3"