Adding more helpful exception messages to prep_param_lists

apex/fp16_utils/fp16util.py

@@ -68,9 +68,23 @@ def prep_param_lists(model, flat_master=False):
     model_params = [param for param in model.parameters() if param.requires_grad]
 
     if flat_master:
-        # flatten_dense_tensors returns a contiguous flat array.
-        # http://pytorch.org/docs/master/_modules/torch/_utils.html
-        master_params = _flatten_dense_tensors([param.data for param in model_params]).float()
+        # Give the user some more useful error messages
+        try:
+            # flatten_dense_tensors returns a contiguous flat array.
+            # http://pytorch.org/docs/master/_modules/torch/_utils.html
+            master_params = _flatten_dense_tensors([param.data for param in model_params]).float()
+        except TypeError as instance:
+            # This is brittle, and depends on how cat chooses to word its error message.
+            if "cat received an invalid combination of arguments" not in instance.args[0]:
+                raise
+            else:
+                # If you append a message to the exception instance, via
+                # instance.args = instance.args + ("Error...",)
+                # this messes up the terminal-formatted printing of the instance's original message.
+                # Basic solution for now:
+                print("Error in prep_param_lists:  model likely contains a mixture of parameters "
+                      "of different types.  Use flat_master=False, or use F16_Optimizer.")
+                raise
         master_params = torch.nn.Parameter(master_params)
         master_params.requires_grad = True
         # master_params.register_hook(backwards_debug_hook)