[Flax tests] fix test_model_outputs_equivalence (#15571)

* fix test_model_outputs_equivalence

* fix tuple outputs for blenderbot

src/transformers/models/blenderbot/modeling_flax_blenderbot.py

@@ -719,7 +719,7 @@ class FlaxBlenderbotEncoder(nn.Module):
         last_hidden_states = self.layer_norm(last_hidden_states)
 
         if not return_dict:
-            return outputs
+            return (last_hidden_states,) + outputs[1:]
 
         return FlaxBaseModelOutput(
             last_hidden_state=last_hidden_states,
@@ -797,7 +797,7 @@ class FlaxBlenderbotDecoder(nn.Module):
         last_hidden_states = self.layer_norm(last_hidden_states)
 
         if not return_dict:
-            return outputs
+            return (last_hidden_states,) + outputs[1:]
 
         return FlaxBaseModelOutputWithPastAndCrossAttentions(
             last_hidden_state=last_hidden_states,

tests/test_modeling_flax_common.py

@@ -134,10 +134,6 @@ class FlaxModelTesterMixin:
     def test_model_outputs_equivalence(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
 
-        def set_nan_tensor_to_zero(t):
-            t[t != t] = 0
-            return t
-
         def check_equivalence(model, tuple_inputs, dict_inputs, additional_kwargs={}):
             tuple_output = model(**tuple_inputs, return_dict=False, **additional_kwargs)
             dict_output = model(**dict_inputs, return_dict=True, **additional_kwargs).to_tuple()
@@ -149,11 +145,9 @@ class FlaxModelTesterMixin:
                 elif tuple_object is None:
                     return
                 else:
-                    self.assert_almost_equals(
-                        set_nan_tensor_to_zero(tuple_object), set_nan_tensor_to_zero(dict_object), 1e-5
-                    )
+                    self.assert_almost_equals(jnp.nan_to_num(tuple_object), jnp.nan_to_num(dict_object), 1e-5)
 
-                recursive_check(tuple_output, dict_output)
+            recursive_check(tuple_output, dict_output)
 
         for model_class in self.all_model_classes:
             model = model_class(config)