add a working toy csgld notebook

README.md

@@ -20,7 +20,29 @@ pip install git+https://github.com/activatedgeek/torch-sgld.git
 
 ## Usage
 
+The general idea is to modify the usual gradient-based update loops
+in PyTorch with the `SGLD` optimizer.
 
+```python
+from torch_sgld import SGLD
+
+f = module()  ## construct PyTorch nn.Module.
+
+sgld = SGLD(f.parameters(), lr=lr, momentum=.9)  ## Add momentum to make it SG-HMC.
+sgld_scheduler = ## Optionally add a step-size scheduler.
+
+for _ in range(num_steps):
+    energy = f()
+    energy.backward()
+
+    sgld.step()
+
+    sgld_scheduler.step()  ## Optional scheduler step.
+```
+
+`cSGLD` can be implemented by using a cyclical learning rate schedule.
+See the [toy_csgld.ipynb](./notebooks/toy_csgld.ipynb) notebook for a
+complete example.
 
 ## License