
'''simple docstring'''



from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
						from ..models.auto import AutoTokenizer




class   UpperCAmelCase_					:






						'''simple docstring'''






						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												raise NotImplementedError()




						def  _lowercase     ( self				):

												"""simple docstring"""



												raise NotImplementedError()






class   UpperCAmelCase_					(		lowerCAmelCase_			):






						'''simple docstring'''






						def __init__( self   ,       _lowercase   ,       _lowercase = False   ,       **_lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			tokenizer
												_lowerCAmelCase  						=			skip_prompt
												_lowerCAmelCase  						=			decode_kwargs

												# variables used in the streaming process
												_lowerCAmelCase  						=			[]
												_lowerCAmelCase  						=			0
												_lowerCAmelCase  						=			True




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												if len(value.shape				) > 1 and value.shape[0] > 1:
																		raise ValueError("""TextStreamer only supports batch size 1"""				)
												elif len(value.shape				) > 1:
																		_lowerCAmelCase  						=			value[0]

												if self.skip_prompt and self.next_tokens_are_prompt:
																		_lowerCAmelCase  						=			False
																		return

												# Add the new token to the cache and decodes the entire thing.
												self.token_cache.extend(value.tolist()				)
												_lowerCAmelCase  						=			self.tokenizer.decode(self.token_cache   ,       **self.decode_kwargs				)

												# After the symbol for a new line, we flush the cache.
												if text.endswith("""\n"""				):
																		_lowerCAmelCase  						=			text[self.print_len :]
																		_lowerCAmelCase  						=			[]
																		_lowerCAmelCase  						=			0
												# If the last token is a CJK character, we print the characters.
												elif len(__lowerCAmelCase				) > 0 and self._is_chinese_char(ord(text[-1]				)				):
																		_lowerCAmelCase  						=			text[self.print_len :]
																		self.print_len += len(__lowerCAmelCase				)
												# Otherwise, prints until the last space char (simple heuristic to avoid printing incomplete words,
												# which may change with the subsequent token -- there are probably smarter ways to do this!)
												else:
																		_lowerCAmelCase  						=			text[self.print_len : text.rfind(""" """				) + 1]
																		self.print_len += len(__lowerCAmelCase				)

												self.on_finalized_text(__lowerCAmelCase				)




						def  _lowercase     ( self				):

												"""simple docstring"""



												if len(self.token_cache				) > 0:
																		_lowerCAmelCase  						=			self.tokenizer.decode(self.token_cache   ,       **self.decode_kwargs				)
																		_lowerCAmelCase  						=			text[self.print_len :]
																		_lowerCAmelCase  						=			[]
																		_lowerCAmelCase  						=			0
												else:
																		_lowerCAmelCase  						=			""""""

												_lowerCAmelCase  						=			True
												self.on_finalized_text(__lowerCAmelCase   ,       stream_end=__lowerCAmelCase				)




						def  _lowercase     ( self   ,       _lowercase   ,       _lowercase = False				):

												"""simple docstring"""



												print(__lowerCAmelCase   ,       flush=__lowerCAmelCase   ,       end="""""" if not stream_end else None				)




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												if (
												    (cp >= 0x4_E_0_0 and cp <= 0x9_F_F_F)
												    or (cp >= 0x3_4_0_0 and cp <= 0x4_D_B_F)  #
												    or (cp >= 0x2_0_0_0_0 and cp <= 0x2_A_6_D_F)  #
												    or (cp >= 0x2_A_7_0_0 and cp <= 0x2_B_7_3_F)  #
												    or (cp >= 0x2_B_7_4_0 and cp <= 0x2_B_8_1_F)  #
												    or (cp >= 0x2_B_8_2_0 and cp <= 0x2_C_E_A_F)  #
												    or (cp >= 0xF_9_0_0 and cp <= 0xF_A_F_F)
												    or (cp >= 0x2_F_8_0_0 and cp <= 0x2_F_A_1_F)  #
												):  #
																		return True

												return False






class   UpperCAmelCase_					(		lowerCAmelCase_			):






						'''simple docstring'''






						def __init__( self   ,       _lowercase   ,       _lowercase = False   ,       _lowercase = None   ,       **_lowercase				):

												"""simple docstring"""



												super().__init__(__lowerCAmelCase   ,       __lowerCAmelCase   ,       **__lowerCAmelCase				)
												_lowerCAmelCase  						=			Queue()
												_lowerCAmelCase  						=			None
												_lowerCAmelCase  						=			timeout




						def  _lowercase     ( self   ,       _lowercase   ,       _lowercase = False				):

												"""simple docstring"""



												self.text_queue.put(__lowerCAmelCase   ,       timeout=self.timeout				)
												if stream_end:
																		self.text_queue.put(self.stop_signal   ,       timeout=self.timeout				)




						def __iter__( self				):

												"""simple docstring"""



												return self




						def  _lowercase     ( self				):

												"""simple docstring"""



												_lowerCAmelCase  						=			self.text_queue.get(timeout=self.timeout				)
												if value == self.stop_signal:
																		raise StopIteration()
												else:
																		return value


'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase    =		{
    """configuration_table_transformer""": [
        """TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """TableTransformerConfig""",
        """TableTransformerOnnxConfig""",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase    =		[
						    """TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TableTransformerForObjectDetection""",
						    """TableTransformerModel""",
						    """TableTransformerPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_table_transformer import (
						    TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    TableTransformerConfig,
						    TableTransformerOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_table_transformer import (
												    TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TableTransformerForObjectDetection,
												    TableTransformerModel,
												    TableTransformerPreTrainedModel,
												)

else:
						import sys

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