
'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a_     =  {
    "configuration_marian": ["MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "MarianConfig", "MarianOnnxConfig"],
}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_     =  ["MarianTokenizer"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_     =  [
      "MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST",
      "MarianForCausalLM",
      "MarianModel",
      "MarianMTModel",
      "MarianPreTrainedModel",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_     =  ["TFMarianModel", "TFMarianMTModel", "TFMarianPreTrainedModel"]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_     =  ["FlaxMarianModel", "FlaxMarianMTModel", "FlaxMarianPreTrainedModel"]

if TYPE_CHECKING:
  from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_marian import MarianTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_marian import (
        MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
        MarianForCausalLM,
        MarianModel,
        MarianMTModel,
        MarianPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
  import sys

  a_     =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






'''simple docstring'''
import importlib.metadata
import sys

from transformers.testing_utils import TestCasePlus
from transformers.utils.versions import require_version, require_version_core


a_     =  importlib.metadata.version("numpy")
a_     =  ".".join([str(x) for x in sys.version_info[:3]])






class 				UpperCAmelCase_			(		snake_case__   ):





 def     snake_case__						(      self):
     # lt + different version strings
     require_version_core("numpy<1000.4.5")
     require_version_core("numpy<1000.4")
     require_version_core("numpy<1000")

     # le
     require_version_core("numpy<=1000.4.5")
     require_version_core(F'numpy<={numpy_ver}')

     # eq
     require_version_core(F'numpy=={numpy_ver}')

     # ne
     require_version_core("numpy!=1000.4.5")

     # ge
     require_version_core("numpy>=1.0")
     require_version_core("numpy>=1.0.0")
     require_version_core(F'numpy>={numpy_ver}')

     # gt
     require_version_core("numpy>1.0.0")

     # mix
     require_version_core("numpy>1.0.0,<1000")

     # requirement w/o version
     require_version_core("numpy")

     # unmet requirements due to version conflict
     for req in ["numpy==1.0.0", "numpy>=1000.0.0", F'numpy<{numpy_ver}']:
         try:
             require_version_core(lowercase_)
         except ImportError as e:
             self.assertIn(F'{req} is required'	,    str(lowercase_))
             self.assertIn("but found"	,    str(lowercase_))

        # unmet requirements due to missing module
     for req in ["numpipypie>1", "numpipypie2"]:
         try:
             require_version_core(lowercase_)
         except importlib.metadata.PackageNotFoundError as e:
             self.assertIn(F'The \'{req}\' distribution was not found and is required by this application'	,    str(lowercase_))
             self.assertIn("Try: pip install transformers -U"	,    str(lowercase_))

        # bogus requirements formats:
        # 1. whole thing
     for req in ["numpy??1.0.0", "numpy1.0.0"]:
         try:
             require_version_core(lowercase_)
         except ValueError as e:
             self.assertIn("requirement needs to be in the pip package format"	,    str(lowercase_))
        # 2. only operators
     for req in ["numpy=1.0.0", "numpy == 1.00", "numpy<>1.0.0", "numpy><1.00", "numpy>>1.0.0"]:
         try:
             require_version_core(lowercase_)
         except ValueError as e:
             self.assertIn("need one of "	,    str(lowercase_))





 def     snake_case__						(      self):
     # matching requirement
     require_version("python>=3.6.0")

     # not matching requirements
     for req in ["python>9.9.9", "python<3.0.0"]:
         try:
             require_version_core(lowercase_)
         except ImportError as e:
             self.assertIn(F'{req} is required'	,    str(lowercase_))
             self.assertIn(F'but found python=={python_ver}'	,    str(lowercase_))




