
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,
)


__lowerCAmelCase					:			List[Any]			      =		{"configuration_xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XGLMConfig"]}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase					:			Optional[Any]			      =		["XGLMTokenizer"]

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase					:			str			      =		["XGLMTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase					:			Optional[int]			      =		[
     "XGLM_PRETRAINED_MODEL_ARCHIVE_LIST",
     "XGLMForCausalLM",
     "XGLMModel",
     "XGLMPreTrainedModel",
 ]


try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase					:			str			      =		[
     "FlaxXGLMForCausalLM",
     "FlaxXGLMModel",
     "FlaxXGLMPreTrainedModel",
 ]


try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase					:			List[str]			      =		[
     "TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFXGLMForCausalLM",
     "TFXGLMModel",
     "TFXGLMPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_xglm import XGLMTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_xglm_fast import XGLMTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_xglm import (
      TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFXGLMForCausalLM,
      TFXGLMModel,
      TFXGLMPreTrainedModel,
  )


else:
 import sys

 __lowerCAmelCase					:			Any			      =		_LazyModule(__name__, globals()["__file__"], _import_structure)




from __future__ import annotations


def     UpperCAmelCase_  (						__lowerCAmelCase	) ->						int:
    if not nums:
        return 0
    __lowercase		:			List[Any]	    =       nums[0]
    __lowercase		:			Union[str, Any]	    =       0
    for num in nums[1:]:
        __lowercase    ,      __lowercase		:			Dict	    =       (
            max_excluding + num,
            max(__lowerCAmelCase	,					__lowerCAmelCase	),
        )
    return max(__lowerCAmelCase	,					__lowerCAmelCase	)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


