




lowerCamelCase__					:  int      							=				tuple[float, float, float]
lowerCamelCase__					:  Optional[Any]      							=				tuple[float, float, float]

def    UpperCAmelCase_				( __UpperCAmelCase		:      Pointad     ,     __UpperCAmelCase		:      Pointad				)   ->					Vectorad:
      SCREAMING_SNAKE_CASE_      		=     end_pointa[0] - end_pointa[0]
      SCREAMING_SNAKE_CASE_      		=     end_pointa[1] - end_pointa[1]
      SCREAMING_SNAKE_CASE_      		=     end_pointa[2] - end_pointa[2]
      return (x, y, z)

def    UpperCAmelCase_				( __UpperCAmelCase		:      Vectorad     ,     __UpperCAmelCase		:      Vectorad				)   ->					Vectorad:
      SCREAMING_SNAKE_CASE_      		=     ab[1] * ac[2] - ab[2] * ac[1]  # *i
      SCREAMING_SNAKE_CASE_      		=     (ab[0] * ac[2] - ab[2] * ac[0]) * -1  # *j
      SCREAMING_SNAKE_CASE_      		=     ab[0] * ac[1] - ab[1] * ac[0]  # *k
      return (x, y, z)

def    UpperCAmelCase_				( __UpperCAmelCase		:      Vectorad     ,     __UpperCAmelCase		:      int				)   ->					bool:
      return tuple(round(__UpperCAmelCase     ,     __UpperCAmelCase				) for x in vector				) == (0, 0, 0)





def    UpperCAmelCase_				( __UpperCAmelCase		:      Pointad     ,     __UpperCAmelCase		:      Pointad     ,     __UpperCAmelCase		:      Pointad     ,     __UpperCAmelCase		:      int = 10				)   ->					bool:
      SCREAMING_SNAKE_CASE_      		=     create_vector(__UpperCAmelCase     ,     __UpperCAmelCase				)
      SCREAMING_SNAKE_CASE_      		=     create_vector(__UpperCAmelCase     ,     __UpperCAmelCase				)
      return is_zero_vector(get_ad_vectors_cross(__UpperCAmelCase     ,     __UpperCAmelCase				)     ,     __UpperCAmelCase				)





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,
)


if is_sentencepiece_available():
   from ..ta.tokenization_ta import TaTokenizer
else:
   from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCamelCase__					:  List[Any]      							=				TaTokenizer

if is_tokenizers_available():
   from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
   from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCamelCase__					:  Union[str, Any]      							=				TaTokenizerFast

lowerCamelCase__					:  Dict      							=				{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				[
       'MT5EncoderModel',
       'MT5ForConditionalGeneration',
       'MT5ForQuestionAnswering',
       'MT5Model',
       'MT5PreTrainedModel',
       'MT5Stack',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
   from .configuration_mta import MTaConfig, MTaOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mta import (
          MTaEncoderModel,
          MTaForConditionalGeneration,
          MTaForQuestionAnswering,
          MTaModel,
          MTaPreTrainedModel,
          MTaStack,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
   import sys

   lowerCamelCase__					:  int      							=				_LazyModule(
       __name__,
       globals()['__file__'],
       _import_structure,
       extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
       module_spec=__spec__,
   )