move and fix check_optimizers (#268)

apex/amp/_initialize.py

@@ -111,7 +111,7 @@ def check_optimizers(optimizers):
         if isinstance(optim, FP16_Optimizer_for_fused):
             bad_optim_type = "apex.optimizers.FP16_Optimizer"
         if bad_optim_type is not None:
-            raise RuntimeError("An incoming optimizer is an instance of {}. ".format(optim_type) +
+            raise RuntimeError("An incoming optimizer is an instance of {}. ".format(bad_optim_type) +
                                "The optimizer(s) passed to amp.initialize() must be bare \n"
                                "instances of either ordinary Pytorch optimizers, or Apex fused \n"
                                "optimizers (currently just FusedAdam, but FusedSGD will be added \n"
@@ -148,7 +148,9 @@ def _initialize(models, optimizers, properties, num_losses=1, cast_model_outputs
         optimizers = []
     elif isinstance(optimizers, list):
         optimizers_was_list = True
+        check_optimizers(optimizers)
     else:
+        check_optimizers([optimizers])
         raise TypeError("optimizers must be either a single optimizer or a list of optimizers.")
 
     if isinstance(models, torch.nn.Module):
@@ -164,7 +166,6 @@ def _initialize(models, optimizers, properties, num_losses=1, cast_model_outputs
     if not _amp_state.allow_incoming_model_not_fp32:
         check_params_fp32(models)
 
-    check_optimizers(optimizers)
 
     # In the future, when FP16_Optimizer can be deprecated and master weights can
     # become an attribute, remember to stash master weights before casting the model.