fix (torch frontends)(tensor.py): fixing the implementation of `torch…

….Tensor.masked_scatter` and `torch.Tensor.masked_scatter_`. The previous implementation was not handling broadcasting of the inputs and was thus was producing incorrect results.

ivy/functional/frontends/torch/tensor.py

@@ -1140,19 +1140,23 @@ def masked_select(self, mask):
         return torch_frontend.masked_select(self, mask)
 
     def masked_scatter(self, mask, source):
+        self = torch_frontend.broadcast_to(self, source.shape)
+        mask = torch_frontend.broadcast_to(mask, self.shape)
         flat_self = torch_frontend.flatten(self.clone())
         flat_mask = torch_frontend.flatten(mask)
         flat_source = torch_frontend.flatten(source)
         indices = torch_frontend.squeeze(torch_frontend.nonzero(flat_mask), -1)
-        flat_self.scatter_(0, indices, flat_source[: indices.shape[0]])
+        flat_self[indices] = flat_source[:indices.numel()]
         return flat_self.reshape(self.shape)
 
     def masked_scatter_(self, mask, source):
+        self = torch_frontend.broadcast_to(self, source.shape)
+        mask = torch_frontend.broadcast_to(mask, self.shape)
         flat_self = torch_frontend.flatten(self.clone())
         flat_mask = torch_frontend.flatten(mask)
         flat_source = torch_frontend.flatten(source)
         indices = torch_frontend.squeeze(torch_frontend.nonzero(flat_mask), -1)
-        flat_self.scatter_(0, indices, flat_source[: indices.shape[0]])
+        flat_self[indices] = flat_source[:indices.numel()]
         ret = flat_self.reshape(self.shape)
         self.ivy_array = ivy.inplace_update(self.ivy_array, ret.ivy_array)
         return self