Fix RuntimeError when initialising from scratch

When initialising from scratch, `requires_grad` is passed and then `normal_` is called as below
```
w = torch.empty( ... , requires_grad=self.requires_grad)
w.normal_(std=1 / math.sqrt(self.n_in * self.kw ** 2))
```

Causing the following issue:
```
/usr/local/lib/python3.7/dist-packages/dall_e/utils.py in __attrs_post_init__(self)
     22                 size = (self.n_out, self.n_in, self.kw, self.kw)
     23                 w = torch.empty(size=size, dtype=torch.float32, device=self.device, requires_grad = self.requires_grad)
---> 24                 w.normal_(std=1 / math.sqrt(self.n_in * self.kw ** 2))
     25 

RuntimeError: a leaf Variable that requires grad is being used in an in-place operation.
```

The above change fixes it.

dall_e/utils.py

@@ -19,10 +19,13 @@ class Conv2d(nn.Module):
 
 	def __attrs_post_init__(self) -> None:
 		super().__init__()
-
-		w = torch.empty((self.n_out, self.n_in, self.kw, self.kw), dtype=torch.float32,
-			device=self.device, requires_grad=self.requires_grad)
+		size = (self.n_out, self.n_in, self.kw, self.kw)
+		w = torch.empty(size=size, dtype=torch.float32, device=self.device)
 		w.normal_(std=1 / math.sqrt(self.n_in * self.kw ** 2))
+
+		# move requires_grad after filling values using normal_
+		# RuntimeError: a leaf Variable that requires grad is being used in an in-place operation.
+		w.requires_grad = self.requires_grad
 
 		b = torch.zeros((self.n_out,), dtype=torch.float32, device=self.device,
 			requires_grad=self.requires_grad)