



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase								=   {
    """configuration_deta""": ["""DETA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DetaConfig"""],
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase								=   ["""DetaImageProcessor"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase								=   [
	    """DETA_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """DetaForObjectDetection""",
	    """DetaModel""",
	    """DetaPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .image_processing_deta import DetaImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_deta import (
		    DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DetaForObjectDetection,
		    DetaModel,
		    DetaPreTrainedModel,
		)

else:
	import sys

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






import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property

class 	__snake_case (				unittest.TestCase):







							'''simple docstring'''






							@cached_property
							def _a (							self						):
											return BlenderbotTokenizer.from_pretrained("""facebook/blenderbot-3B"""						)


							@cached_property
							def _a (							self						):
											return BlenderbotTokenizerFast.from_pretrained("""facebook/blenderbot-3B"""						)


							def _a (							self						):
											a__			 =						self.tokenizer_ab
											a__			 =						""" I am a small frog."""
											a__			 =						tok([src_text]					,					padding=a_					,					truncation=a_						)["""input_ids"""]
											a__			 =						tok.batch_decode(a_					,					skip_special_tokens=a_					,					clean_up_tokenization_spaces=a_						)[0]
											assert src_text == decoded


							def _a (							self						):
											a__			 =						self.rust_tokenizer_ab
											a__			 =						""" I am a small frog."""
											a__			 =						tok([src_text]					,					padding=a_					,					truncation=a_						)["""input_ids"""]
											a__			 =						tok.batch_decode(a_					,					skip_special_tokens=a_					,					clean_up_tokenization_spaces=a_						)[0]
											assert src_text == decoded


							def _a (							self						):
											assert self.tokenizer_ab.add_prefix_space
											assert self.tokenizer_ab([""" Sam""", """Sam"""]						).input_ids == [[5_502, 2], [5_502, 2]]







							def _a (							self						):
											assert self.rust_tokenizer_ab.add_prefix_space
											assert self.rust_tokenizer_ab([""" Sam""", """Sam"""]						).input_ids == [[5_502, 2], [5_502, 2]]

