





import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
	lowerCAmelCase_    =    {
	    '''linear''': PIL.Image.Resampling.BILINEAR,
	    '''bilinear''': PIL.Image.Resampling.BILINEAR,
	    '''bicubic''': PIL.Image.Resampling.BICUBIC,
	    '''lanczos''': PIL.Image.Resampling.LANCZOS,
	    '''nearest''': PIL.Image.Resampling.NEAREST,
	}
else:
	lowerCAmelCase_    =    {
	    '''linear''': PIL.Image.LINEAR,
	    '''bilinear''': PIL.Image.BILINEAR,
	    '''bicubic''': PIL.Image.BICUBIC,
	    '''lanczos''': PIL.Image.LANCZOS,
	    '''nearest''': PIL.Image.NEAREST,
	}






def 					lowerCamelCase_						(    _UpperCamelCase			)		->						Tuple:






				"""simple docstring"""


				snake_case_						:   Any           =  (images / 2 + 0.5).clamp(0			,    1			)
				snake_case_						:   List[str]           =  images.cpu().permute(0			,    2			,    3			,    1			).float().numpy()
				snake_case_						:   Optional[int]           =  numpy_to_pil(_UpperCamelCase			)
				return images






def 					lowerCamelCase_						(    _UpperCamelCase			)		->						str:






				"""simple docstring"""


				if images.ndim == 3:
								snake_case_						:   Any           =  images[None, ...]
				snake_case_						:   Tuple           =  (images * 255).round().astype('''uint8'''			)
				if images.shape[-1] == 1:
								# special case for grayscale (single channel) images
								snake_case_						:   Optional[Any]           =  [Image.fromarray(image.squeeze()			,    mode='''L'''			) for image in images]
				else:
								snake_case_						:   List[Any]           =  [Image.fromarray(_UpperCamelCase			) for image in images]

				return pil_images







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_    =    {'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    ['''XGLMTokenizer''']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    ['''XGLMTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    [
	    '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''XGLMForCausalLM''',
	    '''XGLMModel''',
	    '''XGLMPreTrainedModel''',
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    [
	    '''FlaxXGLMForCausalLM''',
	    '''FlaxXGLMModel''',
	    '''FlaxXGLMPreTrainedModel''',
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    [
	    '''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_    =    _LazyModule(__name__, globals()['''__file__'''], _import_structure)
