





import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow

from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor


if is_flax_available():
  import os

  # The slow tests are often failing with OOM error on GPU
  # This makes JAX allocate exactly what is needed on demand, and deallocate memory that is no longer needed
  # but will be slower as stated here https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html
  _snake_case           =			"""platform"""

  import jax
  import jax.numpy as jnp

  from transformers import BlenderbotTokenizer
  from transformers.models.blenderbot.modeling_flax_blenderbot import (
      FlaxBlenderbotForConditionalGeneration,
      FlaxBlenderbotModel,
      shift_tokens_right,
  )


def _A       (   __magic_name__  , __magic_name__  , __magic_name__=None  , __magic_name__=None  , __magic_name__=None  , __magic_name__=None  , __magic_name__=None  , __magic_name__=None  , ):
   if attention_mask is None:
      lowercase__			       =  np.where(input_ids != config.pad_token_id  , 1  , 0	)
   if decoder_attention_mask is None:
      lowercase__			       =  np.where(decoder_input_ids != config.pad_token_id  , 1  , 0	)
   if head_mask is None:
      lowercase__			       =  np.ones((config.encoder_layers, config.encoder_attention_heads)	)
   if decoder_head_mask is None:
      lowercase__			       =  np.ones((config.decoder_layers, config.decoder_attention_heads)	)
   if cross_attn_head_mask is None:
      lowercase__			       =  np.ones((config.decoder_layers, config.decoder_attention_heads)	)
   return {
       "input_ids": input_ids,
       "decoder_input_ids": decoder_input_ids,
       "attention_mask": attention_mask,
       "decoder_attention_mask": attention_mask,
   }





class  lowerCAmelCase							:







  def __init__(      self  :Dict   ,							_lowercase  :List[Any]   ,							_lowercase  :Any=13   ,							_lowercase  :Optional[Any]=7   ,							_lowercase  :Tuple=True   ,							_lowercase  :List[str]=False   ,							_lowercase  :Optional[int]=99   ,							_lowercase  :int=16   ,							_lowercase  :Dict=2   ,							_lowercase  :List[str]=4   ,							_lowercase  :Optional[int]=4   ,							_lowercase  :Union[str, Any]="gelu"   ,							_lowercase  :List[str]=0.1   ,							_lowercase  :Optional[int]=0.1   ,							_lowercase  :str=32   ,							_lowercase  :List[str]=2   ,							_lowercase  :Union[str, Any]=1   ,							_lowercase  :List[Any]=0   ,							_lowercase  :Optional[int]=0.02   ,							):






     '''simple docstring'''





     lowercase__			       =  parent
     lowercase__			       =  batch_size
     lowercase__			       =  seq_length
     lowercase__			       =  is_training
     lowercase__			       =  use_labels
     lowercase__			       =  vocab_size
     lowercase__			       =  hidden_size
     lowercase__			       =  num_hidden_layers
     lowercase__			       =  num_attention_heads
     lowercase__			       =  intermediate_size
     lowercase__			       =  hidden_act
     lowercase__			       =  hidden_dropout_prob
     lowercase__			       =  attention_probs_dropout_prob
     lowercase__			       =  max_position_embeddings
     lowercase__			       =  eos_token_id
     lowercase__			       =  pad_token_id
     lowercase__			       =  bos_token_id
     lowercase__			       =  initializer_range







  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     lowercase__			       =  np.clip(ids_tensor([self.batch_size, self.seq_length - 1]   ,							self.vocab_size )   ,							3   ,							self.vocab_size )
     lowercase__			       =  np.concatenate((input_ids, 2 * np.ones((self.batch_size, 1)   ,							dtype=np.intaa ))   ,							-1 )

     lowercase__			       =  shift_tokens_right(_lowercase   ,							1   ,							2 )

     lowercase__			       =  BlenderbotConfig(
         vocab_size=self.vocab_size   ,							d_model=self.hidden_size   ,							encoder_layers=self.num_hidden_layers   ,							decoder_layers=self.num_hidden_layers   ,							encoder_attention_heads=self.num_attention_heads   ,							decoder_attention_heads=self.num_attention_heads   ,							encoder_ffn_dim=self.intermediate_size   ,							decoder_ffn_dim=self.intermediate_size   ,							dropout=self.hidden_dropout_prob   ,							attention_dropout=self.attention_probs_dropout_prob   ,							max_position_embeddings=self.max_position_embeddings   ,							eos_token_id=self.eos_token_id   ,							bos_token_id=self.bos_token_id   ,							pad_token_id=self.pad_token_id   ,							initializer_range=self.initializer_range   ,							use_cache=_lowercase   ,							)
     lowercase__			       =  prepare_blenderbot_inputs_dict(_lowercase   ,							_lowercase   ,							_lowercase )
     return config, inputs_dict







  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  self.prepare_config_and_inputs()
     return config, inputs_dict







  def   UpperCAmelCase					(      self  :str   ,							_lowercase  :Tuple   ,							_lowercase  :Any   ,							_lowercase  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  20
     lowercase__			       =  model_class_name(_lowercase )

     lowercase__			       =  model.encode(inputs_dict["input_ids"] )

     lowercase__       ,							lowercase__			       =  (
         inputs_dict["decoder_input_ids"],
         inputs_dict["decoder_attention_mask"],
     )

     lowercase__			       =  model.init_cache(decoder_input_ids.shape[0]   ,							_lowercase   ,							_lowercase )
     lowercase__			       =  jnp.ones((decoder_input_ids.shape[0], max_decoder_length)   ,							dtype="i4" )

     lowercase__			       =  jnp.broadcast_to(
         jnp.arange(decoder_input_ids.shape[-1] - 1 )[None, :]   ,							(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)   ,							)
     lowercase__			       =  model.decode(
         decoder_input_ids[:, :-1]   ,							_lowercase   ,							decoder_attention_mask=_lowercase   ,							past_key_values=_lowercase   ,							decoder_position_ids=_lowercase   ,							)

     lowercase__			       =  jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]   ,							dtype="i4" )
     lowercase__			       =  model.decode(
         decoder_input_ids[:, -1:]   ,							_lowercase   ,							decoder_attention_mask=_lowercase   ,							past_key_values=outputs_cache.past_key_values   ,							decoder_position_ids=_lowercase   ,							)

     lowercase__			       =  model.decode(_lowercase   ,							_lowercase )

     lowercase__			       =  np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5]) ) )
     self.parent.assertTrue(diff < 1e-3   ,							msg=f'''Max diff is {diff}''' )







  def   UpperCAmelCase					(      self  :Optional[Any]   ,							_lowercase  :Optional[int]   ,							_lowercase  :Any   ,							_lowercase  :Any ):






     '''simple docstring'''





     lowercase__			       =  20
     lowercase__			       =  model_class_name(_lowercase )

     lowercase__			       =  model.encode(inputs_dict["input_ids"] )

     lowercase__       ,							lowercase__			       =  (
         inputs_dict["decoder_input_ids"],
         inputs_dict["decoder_attention_mask"],
     )

     lowercase__			       =  jnp.concatenate(
         [
             decoder_attention_mask,
             jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1]) ),
         ]   ,							axis=-1   ,							)

     lowercase__			       =  model.init_cache(decoder_input_ids.shape[0]   ,							_lowercase   ,							_lowercase )
     lowercase__			       =  jnp.broadcast_to(
         jnp.arange(decoder_input_ids.shape[-1] - 1 )[None, :]   ,							(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)   ,							)

     lowercase__			       =  model.decode(
         decoder_input_ids[:, :-1]   ,							_lowercase   ,							decoder_attention_mask=_lowercase   ,							past_key_values=_lowercase   ,							decoder_position_ids=_lowercase   ,							)
     lowercase__			       =  jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]   ,							dtype="i4" )
     lowercase__			       =  model.decode(
         decoder_input_ids[:, -1:]   ,							_lowercase   ,							past_key_values=outputs_cache.past_key_values   ,							decoder_attention_mask=_lowercase   ,							decoder_position_ids=_lowercase   ,							)

     lowercase__			       =  model.decode(_lowercase   ,							_lowercase   ,							decoder_attention_mask=_lowercase )

     lowercase__			       =  np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5]) ) )
     self.parent.assertTrue(diff < 1e-3   ,							msg=f'''Max diff is {diff}''' )





@require_flax
class  lowerCAmelCase							(       unittest.TestCase ):
  __lowerCamelCase		=      99







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  np.array(
         [
             [71, 82, 18, 33, 46, 91, 2],
             [68, 34, 26, 58, 30, 82, 2],
             [5, 97, 17, 39, 94, 40, 2],
             [76, 83, 94, 25, 70, 78, 2],
             [87, 59, 41, 35, 48, 66, 2],
             [55, 13, 16, 58, 5, 2, 1],  # note padding
             [64, 27, 31, 51, 12, 75, 2],
             [52, 64, 86, 17, 83, 39, 2],
             [48, 61, 9, 24, 71, 82, 2],
             [26, 1, 60, 48, 22, 13, 2],
             [21, 5, 62, 28, 14, 76, 2],
             [45, 98, 37, 86, 59, 48, 2],
             [70, 70, 50, 9, 28, 0, 2],
         ]   ,							dtype=np.intaa   ,							)

     lowercase__			       =  input_ids.shape[0]
     lowercase__			       =  BlenderbotConfig(
         vocab_size=self.vocab_size   ,							d_model=24   ,							encoder_layers=2   ,							decoder_layers=2   ,							encoder_attention_heads=2   ,							decoder_attention_heads=2   ,							encoder_ffn_dim=32   ,							decoder_ffn_dim=32   ,							max_position_embeddings=48   ,							eos_token_id=2   ,							pad_token_id=1   ,							bos_token_id=0   ,							)
     return config, input_ids, batch_size







  def   UpperCAmelCase					(      self  :int ):






     '''simple docstring'''





     lowercase__       ,							lowercase__       ,							lowercase__			       =  self._get_config_and_data()
     lowercase__			       =  FlaxBlenderbotForConditionalGeneration(_lowercase )
     lowercase__			       =  lm_model(input_ids=_lowercase )
     lowercase__			       =  (batch_size, input_ids.shape[1], config.vocab_size)
     self.assertEqual(outputs["logits"].shape   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__			       =  BlenderbotConfig(
         vocab_size=self.vocab_size   ,							d_model=14   ,							encoder_layers=2   ,							decoder_layers=2   ,							encoder_attention_heads=2   ,							decoder_attention_heads=2   ,							encoder_ffn_dim=8   ,							decoder_ffn_dim=8   ,							max_position_embeddings=48   ,							)
     lowercase__			       =  FlaxBlenderbotForConditionalGeneration(_lowercase )
     lowercase__			       =  np.array([[71, 82, 18, 33, 46, 91, 2], [68, 34, 26, 58, 30, 2, 1]]   ,							dtype=np.intaa )
     lowercase__			       =  np.array([[82, 71, 82, 18, 2], [58, 68, 2, 1, 1]]   ,							dtype=np.intaa )
     lowercase__			       =  lm_model(input_ids=_lowercase   ,							decoder_input_ids=_lowercase )
     lowercase__			       =  (*summary.shape, config.vocab_size)
     self.assertEqual(outputs["logits"].shape   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Union[str, Any] ):






     '''simple docstring'''





     lowercase__			       =  np.array([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]]   ,							dtype=np.intaa )
     lowercase__			       =  shift_tokens_right(_lowercase   ,							1   ,							2 )
     lowercase__			       =  np.equal(_lowercase   ,							1 ).astype(np.floataa ).sum()
     lowercase__			       =  np.equal(_lowercase   ,							1 ).astype(np.floataa ).sum()
     self.assertEqual(shifted.shape   ,							input_ids.shape )
     self.assertEqual(_lowercase   ,							n_pad_before - 1 )
     self.assertTrue(np.equal(shifted[:, 0]   ,							2 ).all() )





@require_flax
class  lowerCAmelCase							(       lowercase_							,							unittest.TestCase							,							lowercase_ ):
  __lowerCamelCase		=      True
  __lowerCamelCase		=      (
      (
          FlaxBlenderbotModel,
          FlaxBlenderbotForConditionalGeneration,
      )
      if is_flax_available()
      else ()
  )
  __lowerCamelCase		=      (FlaxBlenderbotForConditionalGeneration,) if is_flax_available() else ()







  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__			       =  FlaxBlenderbotModelTester(self )







  def   UpperCAmelCase					(      self  :Optional[Any] ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  self.model_tester.prepare_config_and_inputs()
     for model_class in self.all_model_classes:
        self.model_tester.check_use_cache_forward(_lowercase   ,							_lowercase   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  self.model_tester.prepare_config_and_inputs()
     for model_class in self.all_model_classes:
        self.model_tester.check_use_cache_forward_with_attn_mask(_lowercase   ,							_lowercase   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        with self.subTest(model_class.__name__ ):
           lowercase__			       =  self._prepare_for_class(_lowercase   ,							_lowercase )
           lowercase__			       =  model_class(_lowercase )

           @jax.jit
           def encode_jitted(_lowercase  :Union[str, Any]   ,							_lowercase  :Any=None   ,							**_lowercase  :Optional[Any] ):
              return model.encode(input_ids=_lowercase   ,							attention_mask=_lowercase )

           with self.subTest("JIT Enabled" ):
              lowercase__			       =  encode_jitted(**_lowercase ).to_tuple()

           with self.subTest("JIT Disabled" ):
              with jax.disable_jit():
                 lowercase__			       =  encode_jitted(**_lowercase ).to_tuple()

           self.assertEqual(len(_lowercase )   ,							len(_lowercase ) )
           for jitted_output, output in zip(_lowercase   ,							_lowercase ):
              self.assertEqual(jitted_output.shape   ,							output.shape )







  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        with self.subTest(model_class.__name__ ):
           lowercase__			       =  model_class(_lowercase )
           lowercase__			       =  model.encode(inputs_dict["input_ids"]   ,							inputs_dict["attention_mask"] )

           lowercase__			       =  {
               "decoder_input_ids": inputs_dict["decoder_input_ids"],
               "decoder_attention_mask": inputs_dict["decoder_attention_mask"],
               "encoder_outputs": encoder_outputs,
           }

           @jax.jit
           def decode_jitted(_lowercase  :Any   ,							_lowercase  :Union[str, Any]   ,							_lowercase  :Union[str, Any] ):
              return model.decode(
                  decoder_input_ids=_lowercase   ,							decoder_attention_mask=_lowercase   ,							encoder_outputs=_lowercase   ,							)

           with self.subTest("JIT Enabled" ):
              lowercase__			       =  decode_jitted(**_lowercase ).to_tuple()

           with self.subTest("JIT Disabled" ):
              with jax.disable_jit():
                 lowercase__			       =  decode_jitted(**_lowercase ).to_tuple()

           self.assertEqual(len(_lowercase )   ,							len(_lowercase ) )
           for jitted_output, output in zip(_lowercase   ,							_lowercase ):
              self.assertEqual(jitted_output.shape   ,							output.shape )







  @slow
  def   UpperCAmelCase					(      self  :Dict ):






     '''simple docstring'''





     for model_class_name in self.all_model_classes:
        lowercase__			       =  model_class_name.from_pretrained("facebook/blenderbot-400M-distill" )
        # FlaxBlenderbotForSequenceClassification expects eos token in input_ids
        lowercase__			       =  np.ones((1, 1) ) * model.config.eos_token_id
        lowercase__			       =  model(_lowercase )
        self.assertIsNotNone(_lowercase )







  @unittest.skipUnless(jax_device != "cpu"   ,							"3B test too slow on CPU." )
  @slow
  def   UpperCAmelCase					(      self  :int ):






     '''simple docstring'''





     lowercase__			       =  {"num_beams": 1, "early_stopping": True, "min_length": 15, "max_length": 25}
     lowercase__			       =  {"skip_special_tokens": True, "clean_up_tokenization_spaces": True}

     lowercase__			       =  FlaxBlenderbotForConditionalGeneration.from_pretrained("facebook/blenderbot-3B"   ,							from_pt=_lowercase )
     lowercase__			       =  BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B" )

     lowercase__			       =  ["Sam"]
     lowercase__			       =  tokenizer(_lowercase   ,							return_tensors="jax" )

     lowercase__			       =  model.generate(**_lowercase   ,							**_lowercase )
     lowercase__			       =  "Sam is a great name. It means \"sun\" in Gaelic."

     lowercase__			       =  tokenizer.batch_decode(_lowercase   ,							**_lowercase )
     assert generated_txt[0].strip() == tgt_text













from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments


def _A       (   ):
   lowercase__			       =  HfArgumentParser(__magic_name__	)
   lowercase__			       =  parser.parse_args_into_dataclasses()[0]
   lowercase__			       =  TensorFlowBenchmark(args=__magic_name__	)
   try:
      lowercase__			       =  parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      lowercase__			       =  "Arg --no_{0} is no longer used, please use --no-{0} instead."
      lowercase__			       =  " ".join(str(__magic_name__	).split(" "	)[:-1]	)
      lowercase__			       =  ""
      lowercase__			       =  eval(str(__magic_name__	).split(" "	)[-1]	)
      lowercase__			       =  []
      for arg in depreciated_args:
         # arg[2:] removes '--'
         if arg[2:] in TensorFlowBenchmark.deprecated_args:
            # arg[5:] removes '--no_'
            full_error_msg += arg_error_msg.format(arg[5:]	)
         else:
            wrong_args.append(__magic_name__	)
      if len(__magic_name__	) > 0:
         lowercase__			       =  full_error_msg + begin_error_msg + str(__magic_name__	)
      raise ValueError(__magic_name__	)
   benchmark.run()


if __name__ == "__main__":
  main()






