small example (#490)

Author: bhushan23

examples/small_example.py

@@ -0,0 +1,28 @@
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from onnx_coreml import convert
+
+# Step 0 - (a) Define ML Model
+class small_model(nn.Module):
+    def __init__(self):
+        super(small_model, self).__init__()
+        self.fc1 = nn.Linear(768, 256)
+        self.fc2 = nn.Linear(256, 10)
+
+    def forward(self, x):
+        y = F.relu(self.fc1(x))
+        y = F.softmax(self.fc2(y))
+        return y
+
+# Step 0 - (b) Create model or Load from distk
+model = small_model()
+dummy_input = torch.randn(768)
+
+# Step 1 - PyTorch to ONNX model
+torch.onnx.export(model, dummy_input, './small_model.onnx')
+
+# Step 2 - ONNX to CoreML model
+mlmodel = convert(model='./small_model.onnx', target_ios='13')
+# Save converted CoreML model
+mlmodel.save('small_model.mlmodel')