"""simple docstring"""


import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optional, Tuple, Union, get_type_hints

import yaml


UpperCAmelCase__     						=  NewType("""DataClass""", Any)
UpperCAmelCase__     						=  NewType("""DataClassType""", Any)






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  if isinstance(lowercase      ,lowercase						):
    return v
  if v.lower() in ("yes", "true", "t", "y", "1"):
    return True
  elif v.lower() in ("no", "false", "f", "n", "0"):
    return False
  else:
    raise ArgumentTypeError(
        f'''Truthy value expected: got {v} but expected one of yes/no, true/false, t/f, y/n, 1/0 (case insensitive).'''						)






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					{str(lowercase						): choice for choice in choices}
  return lambda lowercase						: str_to_choice.get(lowercase      ,lowercase						)






def 			__UpperCAmelCase    (	*,
    lowercase = None      ,lowercase = None      ,lowercase = dataclasses.MISSING      ,lowercase = dataclasses.MISSING      ,lowercase = None      ,**lowercase      ,):







  """simple docstring"""
  if metadata is None:
    # Important, don't use as default param in function signature because dict is mutable and shared across function calls
    _UpperCAmelCase         =					{}
  if aliases is not None:
    _UpperCAmelCase         =					aliases
  if help is not None:
    _UpperCAmelCase         =					help

  return dataclasses.field(metadata=lowercase      ,default=lowercase      ,default_factory=lowercase      ,**lowercase						)


class 				a (						lowerCAmelCase_      ):
    _snake_case   :     Iterable[DataClassType]


    def __init__(    self		:     int      , __lowerCAmelCase		:     Union[DataClassType, Iterable[DataClassType]]      , **__lowerCAmelCase		:     str    ):
      # To make the default appear when using --help
      if "formatter_class" not in kwargs:
        _UpperCAmelCase         =					ArgumentDefaultsHelpFormatter
      super().__init__(**__lowerCAmelCase    )
      if dataclasses.is_dataclass(__lowerCAmelCase    ):
        _UpperCAmelCase         =					[dataclass_types]
      _UpperCAmelCase         =					list(__lowerCAmelCase    )
      for dtype in self.dataclass_types:
        self._add_dataclass_arguments(__lowerCAmelCase    )


    @staticmethod
    def    lowerCAmelCase_     (    __lowerCAmelCase		:     ArgumentParser      , __lowerCAmelCase		:     dataclasses.Field    ):
      _UpperCAmelCase         =					f'''--{field.name}'''
      _UpperCAmelCase         =					field.metadata.copy()
      # field.metadata is not used at all by Data Classes,
      # it is provided as a third-party extension mechanism.
      if isinstance(field.type      , __lowerCAmelCase    ):
        raise RuntimeError(
            """Unresolved type detected, which should have been done with the help of """
            """`typing.get_type_hints` method by default"""    )

      _UpperCAmelCase         =					kwargs.pop("""aliases"""      , []    )
      if isinstance(__lowerCAmelCase      , __lowerCAmelCase    ):
        _UpperCAmelCase         =					[aliases]

      _UpperCAmelCase         =					getattr(field.type      , """__origin__"""      , field.type    )
      if origin_type is Union or (hasattr(__lowerCAmelCase      , """UnionType"""    ) and isinstance(__lowerCAmelCase      , types.UnionType    )):
        if str not in field.type.__args__ and (
            len(field.type.__args__    ) != 2 or type(__lowerCAmelCase    ) not in field.type.__args__
        ):
          raise ValueError(
              """Only `Union[X, NoneType]` (i.e., `Optional[X]`) is allowed for `Union` because"""
              """ the argument parser only supports one type per argument."""
              f''' Problem encountered in field \'{field.name}\'.'''    )
        if type(__lowerCAmelCase    ) not in field.type.__args__:
          # filter `str` in Union
          _UpperCAmelCase         =					field.type.__args__[0] if field.type.__args__[1] == str else field.type.__args__[1]
          _UpperCAmelCase         =					getattr(field.type      , """__origin__"""      , field.type    )
        elif bool not in field.type.__args__:
          # filter `NoneType` in Union (except for `Union[bool, NoneType]`)
          _UpperCAmelCase         =					(
              field.type.__args__[0] if isinstance(__lowerCAmelCase      , field.type.__args__[1]    ) else field.type.__args__[1]
          )
          _UpperCAmelCase         =					getattr(field.type      , """__origin__"""      , field.type    )

        # A variable to store kwargs for a boolean field, if needed
        # so that we can init a `no_*` complement argument (see below)
      _UpperCAmelCase         =					{}
      if origin_type is Literal or (isinstance(field.type      , __lowerCAmelCase    ) and issubclass(field.type      , __lowerCAmelCase    )):
        if origin_type is Literal:
          _UpperCAmelCase         =					field.type.__args__
        else:
          _UpperCAmelCase         =					[x.value for x in field.type]

        _UpperCAmelCase         =					make_choice_type_function(kwargs["""choices"""]    )

        if field.default is not dataclasses.MISSING:
          _UpperCAmelCase         =					field.default
        else:
          _UpperCAmelCase         =					True
      elif field.type is bool or field.type == Optional[bool]:
        # Copy the currect kwargs to use to instantiate a `no_*` complement argument below.
        # We do not initialize it here because the `no_*` alternative must be instantiated after the real argument
        _UpperCAmelCase         =					copy(__lowerCAmelCase    )

        # Hack because type=bool in argparse does not behave as we want.
        _UpperCAmelCase         =					string_to_bool
        if field.type is bool or (field.default is not None and field.default is not dataclasses.MISSING):
          # Default value is False if we have no default when of type bool.
          _UpperCAmelCase         =					False if field.default is dataclasses.MISSING else field.default
          # This is the value that will get picked if we don't include --field_name in any way
          _UpperCAmelCase         =					default
          # This tells argparse we accept 0 or 1 value after --field_name
          _UpperCAmelCase         =					"""?"""
          # This is the value that will get picked if we do --field_name (without value)
          _UpperCAmelCase         =					True
      elif isclass(__lowerCAmelCase    ) and issubclass(__lowerCAmelCase      , __lowerCAmelCase    ):
        _UpperCAmelCase         =					field.type.__args__[0]
        _UpperCAmelCase         =					"""+"""
        if field.default_factory is not dataclasses.MISSING:
          _UpperCAmelCase         =					field.default_factory()
        elif field.default is dataclasses.MISSING:
          _UpperCAmelCase         =					True
      else:
        _UpperCAmelCase         =					field.type
        if field.default is not dataclasses.MISSING:
          _UpperCAmelCase         =					field.default
        elif field.default_factory is not dataclasses.MISSING:
          _UpperCAmelCase         =					field.default_factory()
        else:
          _UpperCAmelCase         =					True
      parser.add_argument(__lowerCAmelCase      , *__lowerCAmelCase      , **__lowerCAmelCase    )

      # Add a complement `no_*` argument for a boolean field AFTER the initial field has already been added.
      # Order is important for arguments with the same destination!
      # We use a copy of earlier kwargs because the original kwargs have changed a lot before reaching down
      # here and we do not need those changes/additional keys.
      if field.default is True and (field.type is bool or field.type == Optional[bool]):
        _UpperCAmelCase         =					False
        parser.add_argument(f'''--no_{field.name}'''      , action="""store_false"""      , dest=field.name      , **__lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     Any      , __lowerCAmelCase		:     DataClassType    ):
      if hasattr(__lowerCAmelCase      , """_argument_group_name"""    ):
        _UpperCAmelCase         =					self.add_argument_group(dtype._argument_group_name    )
      else:
        _UpperCAmelCase         =					self

      try:
        _UpperCAmelCase         =					get_type_hints(__lowerCAmelCase    )
      except NameError:
        raise RuntimeError(
            f'''Type resolution failed for {dtype}. Try declaring the class in global scope or '''
            """removing line of `from __future__ import annotations` which opts in Postponed """
            """Evaluation of Annotations (PEP 563)"""    )
      except TypeError as ex:
        # Remove this block when we drop Python 3.9 support
        if sys.version_info[:2] < (3, 10) and "unsupported operand type(s) for |" in str(__lowerCAmelCase    ):
          _UpperCAmelCase         =					""".""".join(map(__lowerCAmelCase      , sys.version_info[:3]    )    )
          raise RuntimeError(
              f'''Type resolution failed for {dtype} on Python {python_version}. Try removing '''
              """line of `from __future__ import annotations` which opts in union types as """
              """`X | Y` (PEP 604) via Postponed Evaluation of Annotations (PEP 563). To """
              """support Python versions that lower than 3.10, you need to use """
              """`typing.Union[X, Y]` instead of `X | Y` and `typing.Optional[X]` instead of """
              """`X | None`."""    ) from ex
        raise

      for field in dataclasses.fields(__lowerCAmelCase    ):
        if not field.init:
          continue
        _UpperCAmelCase         =					type_hints[field.name]
        self._parse_dataclass_field(__lowerCAmelCase      , __lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     Any      , __lowerCAmelCase		:     List[str]=None      , __lowerCAmelCase		:     Any=False      , __lowerCAmelCase		:     Dict=True      , __lowerCAmelCase		:     str=None      , __lowerCAmelCase		:     Optional[int]=None      , ):

      if args_file_flag or args_filename or (look_for_args_file and len(sys.argv    )):
        _UpperCAmelCase         =					[]

        if args_filename:
          args_files.append(Path(__lowerCAmelCase    )    )
        elif look_for_args_file and len(sys.argv    ):
          args_files.append(Path(sys.argv[0]    ).with_suffix(""".args"""    )    )

        # args files specified via command line flag should overwrite default args files so we add them last
        if args_file_flag:
          # Create special parser just to extract the args_file_flag values
          _UpperCAmelCase         =					ArgumentParser()
          args_file_parser.add_argument(__lowerCAmelCase      , type=__lowerCAmelCase      , action="""append"""    )

          # Use only remaining args for further parsing (remove the args_file_flag)
          _UpperCAmelCase       , _UpperCAmelCase         =					args_file_parser.parse_known_args(args=__lowerCAmelCase    )
          _UpperCAmelCase         =					vars(__lowerCAmelCase    ).get(args_file_flag.lstrip("""-"""    )      , __lowerCAmelCase    )

          if cmd_args_file_paths:
            args_files.extend([Path(__lowerCAmelCase    ) for p in cmd_args_file_paths]    )

        _UpperCAmelCase         =					[]
        for args_file in args_files:
          if args_file.exists():
            file_args += args_file.read_text().split()

            # in case of duplicate arguments the last one has precedence
            # args specified via the command line should overwrite args from files, so we add them last
        _UpperCAmelCase         =					file_args + args if args is not None else file_args + sys.argv[1:]
      _UpperCAmelCase       , _UpperCAmelCase         =					self.parse_known_args(args=__lowerCAmelCase    )
      _UpperCAmelCase         =					[]
      for dtype in self.dataclass_types:
        _UpperCAmelCase         =					{f.name for f in dataclasses.fields(__lowerCAmelCase    ) if f.init}
        _UpperCAmelCase         =					{k: v for k, v in vars(__lowerCAmelCase    ).items() if k in keys}
        for k in keys:
          delattr(__lowerCAmelCase      , __lowerCAmelCase    )
        _UpperCAmelCase         =					dtype(**__lowerCAmelCase    )
        outputs.append(__lowerCAmelCase    )
      if len(namespace.__dict__    ) > 0:
        # additional namespace.
        outputs.append(__lowerCAmelCase    )
      if return_remaining_strings:
        return (*outputs, remaining_args)
      else:
        if remaining_args:
          raise ValueError(f'''Some specified arguments are not used by the HfArgumentParser: {remaining_args}'''    )

        return (*outputs,)


    def    lowerCAmelCase_     (    self		:     str      , __lowerCAmelCase		:     Dict[str, Any]      , __lowerCAmelCase		:     bool = False    ):
      _UpperCAmelCase         =					set(args.keys()    )
      _UpperCAmelCase         =					[]
      for dtype in self.dataclass_types:
        _UpperCAmelCase         =					{f.name for f in dataclasses.fields(__lowerCAmelCase    ) if f.init}
        _UpperCAmelCase         =					{k: v for k, v in args.items() if k in keys}
        unused_keys.difference_update(inputs.keys()    )
        _UpperCAmelCase         =					dtype(**__lowerCAmelCase    )
        outputs.append(__lowerCAmelCase    )
      if not allow_extra_keys and unused_keys:
        raise ValueError(f'''Some keys are not used by the HfArgumentParser: {sorted(__lowerCAmelCase    )}'''    )
      return tuple(__lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     Any      , __lowerCAmelCase		:     str      , __lowerCAmelCase		:     bool = False    ):
      with open(Path(__lowerCAmelCase    )      , encoding="""utf-8"""    ) as open_json_file:
        _UpperCAmelCase         =					json.loads(open_json_file.read()    )
      _UpperCAmelCase         =					self.parse_dict(__lowerCAmelCase      , allow_extra_keys=__lowerCAmelCase    )
      return tuple(__lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     int      , __lowerCAmelCase		:     str      , __lowerCAmelCase		:     bool = False    ):
      _UpperCAmelCase         =					self.parse_dict(yaml.safe_load(Path(__lowerCAmelCase    ).read_text()    )      , allow_extra_keys=__lowerCAmelCase    )
      return tuple(__lowerCAmelCase    )

"""simple docstring"""


import unittest

from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_configuration_common import ConfigTester
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
    UpperCAmelCase__     						=  """platform"""
    import jax
    import jax.numpy as jnp
    import numpy as np

    from transformers import FlaxPegasusForConditionalGeneration, FlaxPegasusModel


@require_flax
class 				a :
    _snake_case   :     Tuple   							=							PegasusConfig
    _snake_case   :     int   							=							{}
    _snake_case   :     str   							=							'gelu'


    def __init__(    self		:     Optional[Any]      , __lowerCAmelCase		:     List[str]      , __lowerCAmelCase		:     int=13      , __lowerCAmelCase		:     Any=7      , __lowerCAmelCase		:     str=True      , __lowerCAmelCase		:     Optional[int]=False      , __lowerCAmelCase		:     int=99      , __lowerCAmelCase		:     List[Any]=32      , __lowerCAmelCase		:     Dict=5      , __lowerCAmelCase		:     int=4      , __lowerCAmelCase		:     Dict=37      , __lowerCAmelCase		:     Union[str, Any]=0.1      , __lowerCAmelCase		:     List[str]=0.1      , __lowerCAmelCase		:     Union[str, Any]=20      , __lowerCAmelCase		:     Optional[Any]=2      , __lowerCAmelCase		:     Union[str, Any]=1      , __lowerCAmelCase		:     Any=0      , ):
      _UpperCAmelCase         =					parent
      _UpperCAmelCase         =					batch_size
      _UpperCAmelCase         =					seq_length
      _UpperCAmelCase         =					is_training
      _UpperCAmelCase         =					use_labels
      _UpperCAmelCase         =					vocab_size
      _UpperCAmelCase         =					hidden_size
      _UpperCAmelCase         =					num_hidden_layers
      _UpperCAmelCase         =					num_attention_heads
      _UpperCAmelCase         =					intermediate_size

      _UpperCAmelCase         =					hidden_dropout_prob
      _UpperCAmelCase         =					attention_probs_dropout_prob
      _UpperCAmelCase         =					max_position_embeddings
      _UpperCAmelCase         =					eos_token_id
      _UpperCAmelCase         =					pad_token_id
      _UpperCAmelCase         =					bos_token_id


    def    lowerCAmelCase_     (    self		:     Any    ):
      _UpperCAmelCase         =					ids_tensor([self.batch_size, self.seq_length - 1]      , self.vocab_size    ).clip(3      , self.vocab_size    )
      _UpperCAmelCase         =					np.expand_dims(np.array([self.eos_token_id] * self.batch_size    )      , 1    )
      _UpperCAmelCase         =					np.concatenate([input_ids, eos_tensor]      , axis=1    )

      _UpperCAmelCase         =					ids_tensor([self.batch_size, self.seq_length]      , self.vocab_size    )

      _UpperCAmelCase         =					self.config_cls(
          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_ids=[2]      , bos_token_id=self.bos_token_id      , pad_token_id=self.pad_token_id      , decoder_start_token_id=self.pad_token_id      , **self.config_updates      , )
      _UpperCAmelCase         =					prepare_pegasus_inputs_dict(__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase    )
      return config, inputs_dict


    def    lowerCAmelCase_     (    self		:     Tuple      , __lowerCAmelCase		:     Dict      , __lowerCAmelCase		:     Union[str, Any]      , __lowerCAmelCase		:     int    ):
      _UpperCAmelCase         =					20
      _UpperCAmelCase         =					model_class_name(__lowerCAmelCase    )

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

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

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

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

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

      _UpperCAmelCase         =					model.decode(__lowerCAmelCase      , __lowerCAmelCase    )

      _UpperCAmelCase         =					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    lowerCAmelCase_     (    self		:     str      , __lowerCAmelCase		:     Dict      , __lowerCAmelCase		:     List[str]      , __lowerCAmelCase		:     Any    ):
      _UpperCAmelCase         =					20
      _UpperCAmelCase         =					model_class_name(__lowerCAmelCase    )

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

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

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

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

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

      _UpperCAmelCase         =					model.decode(__lowerCAmelCase      , __lowerCAmelCase      , decoder_attention_mask=__lowerCAmelCase    )

      _UpperCAmelCase         =					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    (	lowercase      ,lowercase      ,lowercase      ,lowercase=None      ,lowercase=None      ,):







  """simple docstring"""
  if attention_mask is None:
    _UpperCAmelCase         =					np.not_equal(lowercase      ,config.pad_token_id						).astype(np.inta						)
  if decoder_attention_mask is None:
    _UpperCAmelCase         =					np.concatenate(
        [
            np.ones(decoder_input_ids[:, :1].shape      ,dtype=np.inta						),
            np.not_equal(decoder_input_ids[:, 1:]      ,config.pad_token_id						).astype(np.inta						),
        ]      ,axis=-1      ,)
  return {
      "input_ids": input_ids,
      "decoder_input_ids": decoder_input_ids,
      "attention_mask": attention_mask,
      "decoder_attention_mask": decoder_attention_mask,
  }


@require_flax
class 				a (						lowerCAmelCase_		,							unittest.TestCase      ):
    _snake_case   :     Dict   							=							(
        (
            FlaxPegasusForConditionalGeneration,
            FlaxPegasusModel,
        )
        if is_flax_available()
        else ()
    )
    _snake_case   :     Optional[int]   							=							(FlaxPegasusForConditionalGeneration,) if is_flax_available() else ()
    _snake_case   :     Optional[Any]   							=							True
    _snake_case   :     List[str]   							=							False
    _snake_case   :     Dict   							=							False
    _snake_case   :     str   							=							False


    def    lowerCAmelCase_     (    self		:     Optional[int]    ):
      _UpperCAmelCase         =					FlaxPegasusModelTester(self    )
      _UpperCAmelCase         =					ConfigTester(self      , config_class=__lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     List[Any]    ):
      self.config_tester.run_common_tests()


    def    lowerCAmelCase_     (    self		:     Union[str, Any]    ):
      _UpperCAmelCase       , _UpperCAmelCase         =					self.model_tester.prepare_config_and_inputs_for_common()
      for model_class in self.all_model_classes:
        self.model_tester.check_use_cache_forward(__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     str    ):
      _UpperCAmelCase       , _UpperCAmelCase         =					self.model_tester.prepare_config_and_inputs_for_common()
      for model_class in self.all_model_classes:
        self.model_tester.check_use_cache_forward_with_attn_mask(__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     Any    ):
      _UpperCAmelCase       , _UpperCAmelCase         =					self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
        with self.subTest(model_class.__name__    ):
          _UpperCAmelCase         =					self._prepare_for_class(__lowerCAmelCase      , __lowerCAmelCase    )
          _UpperCAmelCase         =					model_class(__lowerCAmelCase    )

          @jax.jit
          def encode_jitted(__lowerCAmelCase		:     str      , __lowerCAmelCase		:     Tuple=None      , **__lowerCAmelCase		:     Dict    ):
            return model.encode(input_ids=__lowerCAmelCase      , attention_mask=__lowerCAmelCase    )

          with self.subTest("""JIT Enabled"""    ):
            _UpperCAmelCase         =					encode_jitted(**__lowerCAmelCase    ).to_tuple()

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

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


    def    lowerCAmelCase_     (    self		:     Optional[Any]    ):
      _UpperCAmelCase       , _UpperCAmelCase         =					self.model_tester.prepare_config_and_inputs_for_common()

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

          _UpperCAmelCase         =					{
              """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(__lowerCAmelCase		:     Dict      , __lowerCAmelCase		:     Optional[int]      , __lowerCAmelCase		:     Optional[int]    ):
            return model.decode(
                decoder_input_ids=__lowerCAmelCase      , decoder_attention_mask=__lowerCAmelCase      , encoder_outputs=__lowerCAmelCase      , )

          with self.subTest("""JIT Enabled"""    ):
            _UpperCAmelCase         =					decode_jitted(**__lowerCAmelCase    ).to_tuple()

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

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


    @slow
    def    lowerCAmelCase_     (    self		:     Optional[int]    ):
      for model_class_name in self.all_model_classes:
        _UpperCAmelCase         =					model_class_name.from_pretrained("""google/pegasus-large"""      , from_pt=__lowerCAmelCase    )
        _UpperCAmelCase         =					np.ones((1, 1)    )
        _UpperCAmelCase         =					model(__lowerCAmelCase    )
        self.assertIsNotNone(__lowerCAmelCase    )


    @slow
    def    lowerCAmelCase_     (    self		:     Dict    ):
      _UpperCAmelCase         =					FlaxPegasusForConditionalGeneration.from_pretrained("""google/pegasus-xsum"""    )
      _UpperCAmelCase         =					PegasusTokenizer.from_pretrained("""google/pegasus-xsum"""    )

      _UpperCAmelCase         =					[
          """ PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.""",
          """ The London trio are up for best UK act and best album, as well as getting two nominations in the best song category.\"We got told like this morning 'Oh I think you're nominated'\", said Dappy.\"And I was like 'Oh yeah, which one?' And now we've got nominated for four awards. I mean, wow!\"Bandmate Fazer added: \"We thought it's best of us to come down and mingle with everyone and say hello to the cameras. And now we find we've got four nominations.\"The band have two shots at the best song prize, getting the nod for their Tynchy Stryder collaboration Number One, and single Strong Again.Their album Uncle B will also go up against records by the likes of Beyonce and Kanye West.N-Dubz picked up the best newcomer Mobo in 2007, but female member Tulisa said they wouldn't be too disappointed if they didn't win this time around.\"At the end of the day we're grateful to be where we are in our careers.\"If it don't happen then it don't happen - live to fight another day and keep on making albums and hits for the fans.\"Dappy also revealed they could be performing live several times on the night.The group will be doing Number One and also a possible rendition of the War Child single, I Got Soul.The charity song is a  re-working of The Killers' All These Things That I've Done and is set to feature artists like Chipmunk, Ironik and Pixie Lott.This year's Mobos will be held outside of London for the first time, in Glasgow on 30 September.N-Dubz said they were looking forward to performing for their Scottish fans and boasted about their recent shows north of the border.\"We just done Edinburgh the other day,\" said Dappy.\"We smashed up an N-Dubz show over there. We done Aberdeen about three or four months ago - we smashed up that show over there! Everywhere we go we smash it up!\" """,
      ]

      _UpperCAmelCase         =					[
          """California's largest electricity provider has turned off power to hundreds of thousands of customers.""",
          """Pop group N-Dubz have revealed they were surprised to get four nominations for this year's Mobo Awards.""",
      ]

      _UpperCAmelCase         =					tokenizer(__lowerCAmelCase      , return_tensors="""np"""      , truncation=__lowerCAmelCase      , max_length=512      , padding=__lowerCAmelCase    )
      _UpperCAmelCase         =					model.generate(**__lowerCAmelCase      , num_beams=2    ).sequences
      _UpperCAmelCase         =					tokenizer.batch_decode(__lowerCAmelCase      , skip_special_tokens=__lowerCAmelCase    )
      assert tgt_text == decoded
