Remove jnp.DeviceArray since it is deprecated. (#24875)

* Remove jnp.DeviceArray since it is deprecated.

* Replace all instances of jnp.DeviceArray with jax.Array

* Update src/transformers/models/bert/modeling_flax_bert.py

---------

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

src/transformers/models/bart/modeling_flax_bart.py

@@ -1467,8 +1467,8 @@ class FlaxBartForConditionalGeneration(FlaxBartPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):
@@ -1960,7 +1960,7 @@ class FlaxBartForCausalLMModule(nn.Module):
 class FlaxBartForCausalLM(FlaxBartDecoderPreTrainedModel):
     module_class = FlaxBartForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/bert/modeling_flax_bert.py

@@ -1677,7 +1677,7 @@ class FlaxBertForCausalLMModule(nn.Module):
 class FlaxBertForCausalLM(FlaxBertPreTrainedModel):
     module_class = FlaxBertForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/big_bird/modeling_flax_big_bird.py

@@ -2599,7 +2599,7 @@ class FlaxBigBirdForCausalLMModule(nn.Module):
 class FlaxBigBirdForCausalLM(FlaxBigBirdPreTrainedModel):
     module_class = FlaxBigBirdForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/blenderbot/modeling_flax_blenderbot.py

@@ -1443,8 +1443,8 @@ class FlaxBlenderbotForConditionalGeneration(FlaxBlenderbotPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/blenderbot_small/modeling_flax_blenderbot_small.py

@@ -1441,8 +1441,8 @@ class FlaxBlenderbotSmallForConditionalGeneration(FlaxBlenderbotSmallPreTrainedM
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/electra/modeling_flax_electra.py

@@ -1565,7 +1565,7 @@ class FlaxElectraForCausalLMModule(nn.Module):
 class FlaxElectraForCausalLM(FlaxElectraPreTrainedModel):
     module_class = FlaxElectraForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/encoder_decoder/modeling_flax_encoder_decoder.py

@@ -722,8 +722,8 @@ class FlaxEncoderDecoderModel(FlaxPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/gpt2/modeling_flax_gpt2.py

@@ -742,7 +742,7 @@ class FlaxGPT2LMHeadModule(nn.Module):
 class FlaxGPT2LMHeadModel(FlaxGPT2PreTrainedModel):
     module_class = FlaxGPT2LMHeadModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/gpt_neo/modeling_flax_gpt_neo.py

@@ -654,7 +654,7 @@ class FlaxGPTNeoForCausalLMModule(nn.Module):
 class FlaxGPTNeoForCausalLM(FlaxGPTNeoPreTrainedModel):
     module_class = FlaxGPTNeoForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/gptj/modeling_flax_gptj.py

@@ -683,7 +683,7 @@ class FlaxGPTJForCausalLMModule(nn.Module):
 class FlaxGPTJForCausalLM(FlaxGPTJPreTrainedModel):
     module_class = FlaxGPTJForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/longt5/modeling_flax_longt5.py

@@ -2388,8 +2388,8 @@ class FlaxLongT5ForConditionalGeneration(FlaxLongT5PreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/marian/modeling_flax_marian.py

@@ -1436,8 +1436,8 @@ class FlaxMarianMTModel(FlaxMarianPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/mbart/modeling_flax_mbart.py

@@ -1502,8 +1502,8 @@ class FlaxMBartForConditionalGeneration(FlaxMBartPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/opt/modeling_flax_opt.py

@@ -763,7 +763,7 @@ class FlaxOPTForCausalLMModule(nn.Module):
 class FlaxOPTForCausalLM(FlaxOPTPreTrainedModel):
     module_class = FlaxOPTForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/pegasus/modeling_flax_pegasus.py

@@ -1450,8 +1450,8 @@ class FlaxPegasusForConditionalGeneration(FlaxPegasusPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/roberta/modeling_flax_roberta.py

@@ -1452,7 +1452,7 @@ class FlaxRobertaForCausalLMModule(nn.Module):
 class FlaxRobertaForCausalLM(FlaxRobertaPreTrainedModel):
     module_class = FlaxRobertaForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/roberta_prelayernorm/modeling_flax_roberta_prelayernorm.py

@@ -1478,7 +1478,7 @@ class FlaxRobertaPreLayerNormForCausalLMModule(nn.Module):
 class FlaxRobertaPreLayerNormForCausalLM(FlaxRobertaPreLayerNormPreTrainedModel):
     module_class = FlaxRobertaPreLayerNormForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/speech_encoder_decoder/modeling_flax_speech_encoder_decoder.py

@@ -745,8 +745,8 @@ class FlaxSpeechEncoderDecoderModel(FlaxPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/t5/modeling_flax_t5.py

@@ -1740,8 +1740,8 @@ class FlaxT5ForConditionalGeneration(FlaxT5PreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/vision_encoder_decoder/modeling_flax_vision_encoder_decoder.py

@@ -688,7 +688,7 @@ class FlaxVisionEncoderDecoderModel(FlaxPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/whisper/modeling_flax_whisper.py

@@ -1448,8 +1448,8 @@ class FlaxWhisperForConditionalGeneration(FlaxWhisperPreTrainedModel):
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs,
     ):

src/transformers/models/xglm/modeling_flax_xglm.py

@@ -766,7 +766,7 @@ class FlaxXGLMForCausalLMModule(nn.Module):
 class FlaxXGLMForCausalLM(FlaxXGLMPreTrainedModel):
     module_class = FlaxXGLMForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

src/transformers/models/xlm_roberta/modeling_flax_xlm_roberta.py

@@ -1469,7 +1469,7 @@ class FlaxXLMRobertaForCausalLMModule(nn.Module):
 class FlaxXLMRobertaForCausalLM(FlaxXLMRobertaPreTrainedModel):
     module_class = FlaxXLMRobertaForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 

templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_flax_{{cookiecutter.lowercase_modelname}}.py

@@ -1469,7 +1469,7 @@ class Flax{{cookiecutter.camelcase_modelname}}ForCausalLMModule(nn.Module):
 class Flax{{cookiecutter.camelcase_modelname}}ForCausalLM(Flax{{cookiecutter.camelcase_modelname}}PreTrainedModel):
     module_class = Flax{{cookiecutter.camelcase_modelname}}ForCausalLMModule
 
-    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jnp.DeviceArray] = None):
+    def prepare_inputs_for_generation(self, input_ids, max_length, attention_mask: Optional[jax.Array] = None):
         # initializing the cache
         batch_size, seq_length = input_ids.shape
 
@@ -2969,8 +2969,8 @@ class Flax{{cookiecutter.camelcase_modelname}}ForConditionalGeneration(Flax{{coo
         self,
         decoder_input_ids,
         max_length,
-        attention_mask: Optional[jnp.DeviceArray] = None,
-        decoder_attention_mask: Optional[jnp.DeviceArray] = None,
+        attention_mask: Optional[jax.Array] = None,
+        decoder_attention_mask: Optional[jax.Array] = None,
         encoder_outputs=None,
         **kwargs
     ):