Add tanh method to tensor

pygrad/tensor.py

@@ -92,6 +92,18 @@ class Tensor:
     tensor._back = back
     return tensor
 
+  def tanh(self):
+    tensor = Tensor(np.tanh(self.value))
+    tensor._save(self)
+
+    def back(upstream):
+      # dtanh(x)/dx = 1 - tanh2(x)
+      a, = tensor._parents
+      return [1 - np.dot(np.tanh(a.value) ** 2, upstream)]
+
+    tensor._back = back
+    return tensor
+
   # TODO Compute gradients only for tensors that need it.
   def _backprop(self, upstream):
     # Backprop through the tensor iff it has any parents.