Implement SampleRNN

1 files changed, 21 insertions, 0 deletions

diff --git a/optim.py b/optim.py
new file mode 100644
index 0000000..95f9df2
--- /dev/null
+++ b/optim.py
@@ -0,0 +1,21 @@
+from torch.nn.functional import hardtanh
+
+
+def gradient_clipping(optimizer, min=-1, max=1):
+
+    class OptimizerWrapper(object):
+
+        def step(self, closure):
+            def closure_wrapper():
+                loss = closure()
+                for group in optimizer.param_groups:
+                    for p in group['params']:
+                        hardtanh(p.grad, min, max, inplace=True)
+                return loss
+            
+            return optimizer.step(closure_wrapper)
+
+        def __getattr__(self, attr):
+            return getattr(optimizer, attr)
+
+    return OptimizerWrapper()