


'''simple docstring'''

import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union

from .. import config
from .filelock import FileLock
from .logging import get_logger


lowerCamelCase							:   Tuple  						=	get_logger(__name__)
class   __lowerCAmelCase						:





      '''simple docstring'''






      def __init__(self    :    Tuple   ,						UpperCamelCase    :    Optional[str] = None ):

             '''simple docstring'''







             lowercase__      			= (
                 os.path.join(UpperCamelCase   ,						config.EXTRACTED_DATASETS_DIR ) if cache_dir else config.EXTRACTED_DATASETS_PATH
             )
             lowercase__      			= Extractor



      def       UpperCamelCase__		(self    :    Union[str, Any]   ,						UpperCamelCase    :    str ):

             '''simple docstring'''







             from .file_utils import hash_url_to_filename

             # Path where we extract compressed archives
             # We extract in the cache dir, and get the extracted path name by hashing the original path"
             lowercase__      			= os.path.abspath(UpperCamelCase )
             return os.path.join(self.extract_dir   ,						hash_url_to_filename(UpperCamelCase ) )



      def       UpperCamelCase__		(self    :    List[str]   ,						UpperCamelCase    :    str   ,						UpperCamelCase    :    bool ):

             '''simple docstring'''







             return force_extract or (
                 not os.path.isfile(UpperCamelCase ) and not (os.path.isdir(UpperCamelCase ) and os.listdir(UpperCamelCase ))
             )






      def       UpperCamelCase__		(self    :    Dict   ,						UpperCamelCase    :    str   ,						UpperCamelCase    :    bool = False ):

             '''simple docstring'''







             lowercase__      			= self.extractor.infer_extractor_format(UpperCamelCase )
             if not extractor_format:
                    return input_path
             lowercase__      			= self._get_output_path(UpperCamelCase )
             if self._do_extract(UpperCamelCase   ,						UpperCamelCase ):
                    self.extractor.extract(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase )
             return output_path






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      @classmethod
      @abstractmethod
      def       UpperCamelCase__		(cls    :    Any   ,						UpperCamelCase    :    Union[Path, str]   ,						**UpperCamelCase    :    Optional[Any] ):

             '''simple docstring'''







             ...






      @staticmethod
      @abstractmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             ...






class   __lowerCAmelCase						(lowercase_  ,     lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     List[bytes]  					=							[]



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    int ):

             '''simple docstring'''







             with open(UpperCamelCase   ,						'''rb''' ) as f:
                    return f.read(UpperCamelCase )






      @classmethod
      def       UpperCamelCase__		(cls    :    int   ,						UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    bytes = b"" ):

             '''simple docstring'''







             if not magic_number:
                    lowercase__      			= max(len(UpperCamelCase ) for cls_magic_number in cls.magic_numbers )
                    try:
                           lowercase__      			= cls.read_magic_number(UpperCamelCase   ,						UpperCamelCase )
                    except OSError:
                           return False
             return any(magic_number.startswith(UpperCamelCase ) for cls_magic_number in cls.magic_numbers )






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      @classmethod
      def       UpperCamelCase__		(cls    :    Optional[int]   ,						UpperCamelCase    :    Union[Path, str]   ,						**UpperCamelCase    :    List[Any] ):

             '''simple docstring'''







             return tarfile.is_tarfile(UpperCamelCase )



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    List[str]   ,						UpperCamelCase    :    Optional[int] ):

             '''simple docstring'''







             def resolved(UpperCamelCase    :    str ) -> str:
                    return os.path.realpath(os.path.abspath(UpperCamelCase ) )

             def badpath(UpperCamelCase    :    str   ,						UpperCamelCase    :    str ) -> bool:
                    # joinpath will ignore base if path is absolute
                    return not resolved(os.path.join(UpperCamelCase   ,						UpperCamelCase ) ).startswith(UpperCamelCase )

             def badlink(UpperCamelCase    :    int   ,						UpperCamelCase    :    str ) -> bool:
                    # Links are interpreted relative to the directory containing the link
                    lowercase__      			= resolved(os.path.join(UpperCamelCase   ,						os.path.dirname(info.name ) ) )
                    return badpath(info.linkname   ,						base=UpperCamelCase )

             lowercase__      			= resolved(UpperCamelCase )

             for finfo in members:
                    if badpath(finfo.name   ,						UpperCamelCase ):
                           logger.error(f"Extraction of {finfo.name} is blocked (illegal path)" )
                    elif finfo.issym() and badlink(UpperCamelCase   ,						UpperCamelCase ):
                           logger.error(f"Extraction of {finfo.name} is blocked: Symlink to {finfo.linkname}" )
                    elif finfo.islnk() and badlink(UpperCamelCase   ,						UpperCamelCase ):
                           logger.error(f"Extraction of {finfo.name} is blocked: Hard link to {finfo.linkname}" )
                    else:
                           yield finfo






      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             os.makedirs(UpperCamelCase   ,						exist_ok=UpperCamelCase )
             lowercase__      			= tarfile.open(UpperCamelCase )
             tar_file.extractall(UpperCamelCase   ,						members=TarExtractor.safemembers(UpperCamelCase   ,						UpperCamelCase ) )
             tar_file.close()






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     Union[str, Any]  					=							[B"""\x1F\x8B"""]



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             with gzip.open(UpperCamelCase   ,						'''rb''' ) as gzip_file:
                    with open(UpperCamelCase   ,						'''wb''' ) as extracted_file:
                           shutil.copyfileobj(UpperCamelCase   ,						UpperCamelCase )






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     Optional[int]  					=							[
          B"""PK\x03\x04""",
          B"""PK\x05\x06""",  # empty archive
          B"""PK\x07\x08""",  # spanned archive
      ]



      @classmethod
      def       UpperCamelCase__		(cls    :    Tuple   ,						UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    bytes = b"" ):

             '''simple docstring'''







             if super().is_extractable(UpperCamelCase   ,						magic_number=UpperCamelCase ):
                    return True
             try:
                    # Alternative version of zipfile.is_zipfile that has less false positives, but misses executable zip archives.
                    # From: https://github.com/python/cpython/pull/5053
                    from zipfile import (
                        _CD_SIGNATURE,
                        _ECD_DISK_NUMBER,
                        _ECD_DISK_START,
                        _ECD_ENTRIES_TOTAL,
                        _ECD_OFFSET,
                        _ECD_SIZE,
                        _EndRecData,
                        sizeCentralDir,
                        stringCentralDir,
                        structCentralDir,
                    )

                    with open(UpperCamelCase   ,						'''rb''' ) as fp:
                           lowercase__      			= _EndRecData(UpperCamelCase )
                           if endrec:
                                  if endrec[_ECD_ENTRIES_TOTAL] == 0 and endrec[_ECD_SIZE] == 0 and endrec[_ECD_OFFSET] == 0:
                                         return True  # Empty zipfiles are still zipfiles
                                  elif endrec[_ECD_DISK_NUMBER] == endrec[_ECD_DISK_START]:
                                         fp.seek(endrec[_ECD_OFFSET] )  # Central directory is on the same disk
                                         if fp.tell() == endrec[_ECD_OFFSET] and endrec[_ECD_SIZE] >= sizeCentralDir:
                                                lowercase__      			= fp.read(UpperCamelCase )  # CD is where we expect it to be
                                                if len(UpperCamelCase ) == sizeCentralDir:
                                                       lowercase__      			= struct.unpack(UpperCamelCase   ,						UpperCamelCase )  # CD is the right size
                                                       if centdir[_CD_SIGNATURE] == stringCentralDir:
                                                              return True  # First central directory entry  has correct magic number
                    return False
             except Exception:  # catch all errors in case future python versions change the zipfile internals
                    return False






      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             os.makedirs(UpperCamelCase   ,						exist_ok=UpperCamelCase )
             with zipfile.ZipFile(UpperCamelCase   ,						'''r''' ) as zip_file:
                    zip_file.extractall(UpperCamelCase )
                    zip_file.close()






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     Dict  					=							[B"""\xFD\x37\x7A\x58\x5A\x00"""]



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             with lzma.open(UpperCamelCase ) as compressed_file:
                    with open(UpperCamelCase   ,						'''wb''' ) as extracted_file:
                           shutil.copyfileobj(UpperCamelCase   ,						UpperCamelCase )






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     Dict  					=							[B"""Rar!\x1a\x07\x00""", B"""Rar!\x1a\x07\x01\x00"""]  # RAR_ID  # RAR5_ID



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             if not config.RARFILE_AVAILABLE:
                    raise ImportError('''Please pip install rarfile''' )
             import rarfile

             os.makedirs(UpperCamelCase   ,						exist_ok=UpperCamelCase )
             lowercase__      			= rarfile.RarFile(UpperCamelCase )
             rf.extractall(UpperCamelCase )
             rf.close()






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     List[str]  					=							[B"""\x28\xb5\x2F\xFD"""]



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             if not config.ZSTANDARD_AVAILABLE:
                    raise ImportError('''Please pip install zstandard''' )
             import zstandard as zstd

             lowercase__      			= zstd.ZstdDecompressor()
             with open(UpperCamelCase   ,						'''rb''' ) as ifh, open(UpperCamelCase   ,						'''wb''' ) as ofh:
                    dctx.copy_stream(UpperCamelCase   ,						UpperCamelCase )






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     List[str]  					=							[B"""\x42\x5A\x68"""]



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             with bza.open(UpperCamelCase   ,						'''rb''' ) as compressed_file:
                    with open(UpperCamelCase   ,						'''wb''' ) as extracted_file:
                           shutil.copyfileobj(UpperCamelCase   ,						UpperCamelCase )






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     List[str]  					=							[B"""\x37\x7A\xBC\xAF\x27\x1C"""]



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             if not config.PY7ZR_AVAILABLE:
                    raise ImportError('''Please pip install py7zr''' )
             import pyazr

             os.makedirs(UpperCamelCase   ,						exist_ok=UpperCamelCase )
             with pyazr.SevenZipFile(UpperCamelCase   ,						'''r''' ) as archive:
                    archive.extractall(UpperCamelCase )






class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     List[Any]  					=							[B"""\x04\x22\x4D\x18"""]



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str] ):

             '''simple docstring'''







             if not config.LZ4_AVAILABLE:
                    raise ImportError('''Please pip install lz4''' )
             import lza.frame

             with lza.frame.open(UpperCamelCase   ,						'''rb''' ) as compressed_file:
                    with open(UpperCamelCase   ,						'''wb''' ) as extracted_file:
                           shutil.copyfileobj(UpperCamelCase   ,						UpperCamelCase )






class   __lowerCAmelCase						:





      '''simple docstring'''






      lowerCAmelCase__					:     Dict[str, Type[BaseExtractor]]  					=							{
          "tar": TarExtractor,
          "gzip": GzipExtractor,
          "zip": ZipExtractor,
          "xz": XzExtractor,
          "rar": RarExtractor,
          "zstd": ZstdExtractor,
          "bz2": BzipaExtractor,
          "7z": SevenZipExtractor,  # <Added version="2.4.0"/>
          "lz4": LzaExtractor,  # <Added version="2.4.0"/>
      }



      @classmethod
      def       UpperCamelCase__		(cls    :    Optional[Any] ):

             '''simple docstring'''







             return max(
                 len(UpperCamelCase )
                 for extractor in cls.extractors.values()
                 if issubclass(UpperCamelCase   ,						UpperCamelCase )
                 for extractor_magic_number in extractor.magic_numbers )



      @staticmethod
      def       UpperCamelCase__		(UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    int ):

             '''simple docstring'''







             try:
                    return MagicNumberBaseExtractor.read_magic_number(UpperCamelCase   ,						magic_number_length=UpperCamelCase )
             except OSError:
                    return b""



      @classmethod
      def       UpperCamelCase__		(cls    :    Any   ,						UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    bool = False ):

             '''simple docstring'''







             warnings.warn(
                 '''Method \'is_extractable\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '''
                 '''Use \'infer_extractor_format\' instead.'''   ,						category=UpperCamelCase   ,						)
             lowercase__      			= cls.infer_extractor_format(UpperCamelCase )
             if extractor_format:
                    return True if not return_extractor else (True, cls.extractors[extractor_format])
             return False if not return_extractor else (False, None)



      @classmethod
      def       UpperCamelCase__		(cls    :    int   ,						UpperCamelCase    :    Union[Path, str] ):  # <Added version="2.4.0"/>

             '''simple docstring'''







             lowercase__      			= cls._get_magic_number_max_length()
             lowercase__      			= cls._read_magic_number(UpperCamelCase   ,						UpperCamelCase )
             for extractor_format, extractor in cls.extractors.items():
                    if extractor.is_extractable(UpperCamelCase   ,						magic_number=UpperCamelCase ):
                           return extractor_format






      @classmethod
      def       UpperCamelCase__		(cls    :    Optional[Any]   ,						UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Union[Path, str]   ,						UpperCamelCase    :    Optional[str] = None   ,						UpperCamelCase    :    Optional[BaseExtractor] = "deprecated"   ,						):

             '''simple docstring'''







             os.makedirs(os.path.dirname(UpperCamelCase )   ,						exist_ok=UpperCamelCase )
             # Prevent parallel extractions
             lowercase__      			= str(Path(UpperCamelCase ).with_suffix('''.lock''' ) )
             with FileLock(UpperCamelCase ):
                    shutil.rmtree(UpperCamelCase   ,						ignore_errors=UpperCamelCase )
                    if extractor_format or extractor != "deprecated":
                           if extractor != "deprecated" or not isinstance(UpperCamelCase   ,						UpperCamelCase ):  # passed as positional arg
                                  warnings.warn(
                                      '''Parameter \'extractor\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '''
                                      '''Use \'extractor_format\' instead.'''   ,						category=UpperCamelCase   ,						)
                                  lowercase__      			= extractor if extractor != '''deprecated''' else extractor_format
                           else:
                                  lowercase__      			= cls.extractors[extractor_format]
                           return extractor.extract(UpperCamelCase   ,						UpperCamelCase )
                    else:
                           warnings.warn(
                               '''Parameter \'extractor_format\' was made required in version 2.4.0 and not passing it will raise an '''
                               '''exception in 3.0.0.'''   ,						category=UpperCamelCase   ,						)
                           for extractor in cls.extractors.values():
                                  if extractor.is_extractable(UpperCamelCase ):
                                         return extractor.extract(UpperCamelCase   ,						UpperCamelCase )






"""simple docstring"""





import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import 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
    _a		       =							'platform'

    import jax
    import jax.numpy as jnp

    from transformers.models.blenderbot_small.modeling_flax_blenderbot_small import (
        FlaxBlenderbotSmallForConditionalGeneration,
        FlaxBlenderbotSmallModel,
        shift_tokens_right,
    )







def 	__a     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase=None,		__lowerCamelCase=None,		__lowerCamelCase=None,		__lowerCamelCase=None,		__lowerCamelCase=None,		__lowerCamelCase=None,		):
   if attention_mask is None:
      UpperCAmelCase_					:					Union[str, Any]			     =    np.where(input_ids != config.pad_token_id,		1,		0  )
   if decoder_attention_mask is None:
      UpperCAmelCase_					:					Optional[int]			     =    np.where(decoder_input_ids != config.pad_token_id,		1,		0  )
   if head_mask is None:
      UpperCAmelCase_					:					int			     =    np.ones((config.encoder_layers, config.encoder_attention_heads)  )
   if decoder_head_mask is None:
      UpperCAmelCase_					:					Union[str, Any]			     =    np.ones((config.decoder_layers, config.decoder_attention_heads)  )
   if cross_attn_head_mask is None:
      UpperCAmelCase_					:					List[Any]			     =    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 A_	:




  '''simple docstring'''







  def __init__(		self				,   lowercase_				,   lowercase_=13				,   lowercase_=7				,   lowercase_=True				,   lowercase_=False				,   lowercase_=99				,   lowercase_=16				,   lowercase_=2				,   lowercase_=4				,   lowercase_=4				,   lowercase_="gelu"				,   lowercase_=0.1				,   lowercase_=0.1				,   lowercase_=32				,   lowercase_=2				,   lowercase_=1				,   lowercase_=0				,   lowercase_=0.02				,   ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    parent
     UpperCAmelCase_					:					Tuple			     =    batch_size
     UpperCAmelCase_					:					str			     =    seq_length
     UpperCAmelCase_					:					Dict			     =    is_training
     UpperCAmelCase_					:					List[Any]			     =    use_labels
     UpperCAmelCase_					:					Optional[int]			     =    vocab_size
     UpperCAmelCase_					:					int			     =    hidden_size
     UpperCAmelCase_					:					Optional[Any]			     =    num_hidden_layers
     UpperCAmelCase_					:					Dict			     =    num_attention_heads
     UpperCAmelCase_					:					List[str]			     =    intermediate_size
     UpperCAmelCase_					:					Optional[int]			     =    hidden_act
     UpperCAmelCase_					:					str			     =    hidden_dropout_prob
     UpperCAmelCase_					:					int			     =    attention_probs_dropout_prob
     UpperCAmelCase_					:					Optional[Any]			     =    max_position_embeddings
     UpperCAmelCase_					:					str			     =    eos_token_id
     UpperCAmelCase_					:					str			     =    pad_token_id
     UpperCAmelCase_					:					str			     =    bos_token_id
     UpperCAmelCase_					:					List[Any]			     =    initializer_range







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Optional[Any]			     =    np.clip(ids_tensor([self.batch_size, self.seq_length - 1]				,   self.vocab_size  )				,   3				,   self.vocab_size  )
     UpperCAmelCase_					:					Any			     =    np.concatenate((input_ids, 2 * np.ones((self.batch_size, 1)				,   dtype=np.intaa  ))				,   -1  )

     UpperCAmelCase_					:					str			     =    shift_tokens_right(lowercase_				,   1				,   2  )

     UpperCAmelCase_					:					str			     =    BlenderbotSmallConfig(
         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_				,   )
     UpperCAmelCase_					:					Optional[int]			     =    prepare_blenderbot_inputs_dict(lowercase_				,   lowercase_				,   lowercase_  )
     return config, inputs_dict







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_					:					Optional[int]			     =    self.prepare_config_and_inputs()
     return config, inputs_dict







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_				,   lowercase_  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    20
     UpperCAmelCase_					:					int			     =    model_class_name(lowercase_  )

     UpperCAmelCase_					:					Optional[int]			     =    model.encode(inputs_dict["input_ids"]  )

     UpperCAmelCase_     ,   UpperCAmelCase_					:					Any			     =    (
         inputs_dict["decoder_input_ids"],
         inputs_dict["decoder_attention_mask"],
     )

     UpperCAmelCase_					:					Any			     =    model.init_cache(decoder_input_ids.shape[0]				,   lowercase_				,   lowercase_  )
     UpperCAmelCase_					:					Tuple			     =    jnp.ones((decoder_input_ids.shape[0], max_decoder_length)				,   dtype="i4"  )

     UpperCAmelCase_					:					Union[str, Any]			     =    jnp.broadcast_to(
         jnp.arange(decoder_input_ids.shape[-1] - 1  )[None, :]				,   (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)				,   )
     UpperCAmelCase_					:					int			     =    model.decode(
         decoder_input_ids[:, :-1]				,   lowercase_				,   decoder_attention_mask=lowercase_				,   past_key_values=lowercase_				,   decoder_position_ids=lowercase_				,   )

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

     UpperCAmelCase_					:					Optional[Any]			     =    model.decode(lowercase_				,   lowercase_  )

     UpperCAmelCase_					:					Tuple			     =    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				,   lowercase_				,   lowercase_				,   lowercase_  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    20
     UpperCAmelCase_					:					Any			     =    model_class_name(lowercase_  )

     UpperCAmelCase_					:					Tuple			     =    model.encode(inputs_dict["input_ids"]  )

     UpperCAmelCase_     ,   UpperCAmelCase_					:					List[Any]			     =    (
         inputs_dict["decoder_input_ids"],
         inputs_dict["decoder_attention_mask"],
     )

     UpperCAmelCase_					:					Optional[Any]			     =    jnp.concatenate(
         [
             decoder_attention_mask,
             jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1])  ),
         ]				,   axis=-1				,   )

     UpperCAmelCase_					:					int			     =    model.init_cache(decoder_input_ids.shape[0]				,   lowercase_				,   lowercase_  )
     UpperCAmelCase_					:					List[str]			     =    jnp.broadcast_to(
         jnp.arange(decoder_input_ids.shape[-1] - 1  )[None, :]				,   (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)				,   )

     UpperCAmelCase_					:					List[str]			     =    model.decode(
         decoder_input_ids[:, :-1]				,   lowercase_				,   decoder_attention_mask=lowercase_				,   past_key_values=lowercase_				,   decoder_position_ids=lowercase_				,   )
     UpperCAmelCase_					:					Any			     =    jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]				,   dtype="i4"  )
     UpperCAmelCase_					:					Dict			     =    model.decode(
         decoder_input_ids[:, -1:]				,   lowercase_				,   past_key_values=outputs_cache.past_key_values				,   decoder_attention_mask=lowercase_				,   decoder_position_ids=lowercase_				,   )

     UpperCAmelCase_					:					Dict			     =    model.decode(lowercase_				,   lowercase_				,   decoder_attention_mask=lowercase_  )

     UpperCAmelCase_					:					Optional[Any]			     =    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 A_	(unittest.TestCase      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Tuple       =		99







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Optional[Any]			     =    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				,   )

     UpperCAmelCase_					:					Any			     =    input_ids.shape[0]
     UpperCAmelCase_					:					Dict			     =    BlenderbotSmallConfig(
         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  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_     ,   UpperCAmelCase_					:					Tuple			     =    self._get_config_and_data()
     UpperCAmelCase_					:					List[str]			     =    FlaxBlenderbotSmallForConditionalGeneration(lowercase_  )
     UpperCAmelCase_					:					Optional[int]			     =    lm_model(input_ids=lowercase_  )
     UpperCAmelCase_					:					Optional[int]			     =    (batch_size, input_ids.shape[1], config.vocab_size)
     self.assertEqual(outputs["logits"].shape				,   lowercase_  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    BlenderbotSmallConfig(
         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				,   )
     UpperCAmelCase_					:					Optional[int]			     =    FlaxBlenderbotSmallForConditionalGeneration(lowercase_  )
     UpperCAmelCase_					:					str			     =    np.array([[71, 82, 18, 33, 46, 91, 2], [68, 34, 26, 58, 30, 2, 1]]				,   dtype=np.intaa  )
     UpperCAmelCase_					:					str			     =    np.array([[82, 71, 82, 18, 2], [58, 68, 2, 1, 1]]				,   dtype=np.intaa  )
     UpperCAmelCase_					:					Tuple			     =    lm_model(input_ids=lowercase_				,   decoder_input_ids=lowercase_  )
     UpperCAmelCase_					:					Tuple			     =    (*summary.shape, config.vocab_size)
     self.assertEqual(outputs["logits"].shape				,   lowercase_  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[Any]			     =    np.array([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]]				,   dtype=np.intaa  )
     UpperCAmelCase_					:					Dict			     =    shift_tokens_right(lowercase_				,   1				,   2  )
     UpperCAmelCase_					:					Tuple			     =    np.equal(lowercase_				,   1  ).astype(np.floataa  ).sum()
     UpperCAmelCase_					:					Optional[Any]			     =    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 A_	(lowercase__				,unittest.TestCase				,lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						str       =		True
  SCREAMING_SNAKE_CASE__			:						Union[str, Any]       =		(
      (
          FlaxBlenderbotSmallModel,
          FlaxBlenderbotSmallForConditionalGeneration,
      )
      if is_flax_available()
      else ()
  )
  SCREAMING_SNAKE_CASE__			:						List[Any]       =		(FlaxBlenderbotSmallForConditionalGeneration,) if is_flax_available() else ()







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Dict			     =    FlaxBlenderbotSmallModelTester(self  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_					:					Tuple			     =    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  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_					:					Optional[Any]			     =    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  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_					:					Any			     =    self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        with self.subTest(model_class.__name__  ):
           UpperCAmelCase_					:					List[Any]			     =    self._prepare_for_class(lowercase_				,   lowercase_  )
           UpperCAmelCase_					:					Dict			     =    model_class(lowercase_  )

           @jax.jit
           def encode_jitted(lowercase_				,   lowercase_=None				,   **lowercase_  ):
              return model.encode(input_ids=lowercase_				,   attention_mask=lowercase_  )

           with self.subTest("JIT Enabled"  ):
              UpperCAmelCase_					:					List[Any]			     =    encode_jitted(**lowercase_  ).to_tuple()

           with self.subTest("JIT Disabled"  ):
              with jax.disable_jit():
                 UpperCAmelCase_					:					Optional[Any]			     =    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  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_					:					Union[str, Any]			     =    self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        with self.subTest(model_class.__name__  ):
           UpperCAmelCase_					:					Optional[int]			     =    model_class(lowercase_  )
           UpperCAmelCase_					:					Tuple			     =    model.encode(inputs_dict["input_ids"]				,   inputs_dict["attention_mask"]  )

           UpperCAmelCase_					:					int			     =    {
               "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_				,   lowercase_				,   lowercase_  ):
              return model.decode(
                  decoder_input_ids=lowercase_				,   decoder_attention_mask=lowercase_				,   encoder_outputs=lowercase_				,   )

           with self.subTest("JIT Enabled"  ):
              UpperCAmelCase_					:					str			     =    decode_jitted(**lowercase_  ).to_tuple()

           with self.subTest("JIT Disabled"  ):
              with jax.disable_jit():
                 UpperCAmelCase_					:					List[Any]			     =    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  ):

     """simple docstring"""
     for model_class_name in self.all_model_classes:
        UpperCAmelCase_					:					Optional[Any]			     =    model_class_name.from_pretrained("facebook/blenderbot_small-90M"  )
        # FlaxBlenderbotForSequenceClassification expects eos token in input_ids
        UpperCAmelCase_					:					List[str]			     =    np.ones((1, 1)  ) * model.config.eos_token_id
        UpperCAmelCase_					:					Optional[int]			     =    model(lowercase_  )
        self.assertIsNotNone(lowercase_  )


