
import jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


lowercase__		:Optional[int]   =    logging.get_logger(__name__)

lowercase__		:Optional[int]   =    "T5Config"



def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		):
					'''simple docstring'''
					lowercase							=						jnp.zeros_like(lowerCAmelCase__		)
					lowercase							=						shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]		)
					lowercase							=						shifted_input_ids.at[:, 0].set(lowerCAmelCase__		)

					lowercase							=						jnp.where(shifted_input_ids == -100 ,			lowerCAmelCase__ ,			lowerCAmelCase__		)
					return shifted_input_ids







class 				lowercase		(					__UpperCamelCase		):
							lowercase_       :       str       					='mt5'
							lowercase_       :       Optional[int]       					=MTaConfig







class 				lowercase		(					__UpperCamelCase		):
							lowercase_       :       int       					='mt5'
							lowercase_       :       Tuple       					=MTaConfig







class 				lowercase		(					__UpperCamelCase		):
							lowercase_       :       List[Any]       					='mt5'
							lowercase_       :       int       					=MTaConfig








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__lowerCAmelCase		       =							{
    '''configuration_encodec''': [
        '''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EncodecConfig''',
    ],
    '''feature_extraction_encodec''': ['''EncodecFeatureExtractor'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase		       =							[
     '''ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''EncodecModel''',
     '''EncodecPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_encodec import (
     ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
     EncodecConfig,
 )
 from .feature_extraction_encodec import EncodecFeatureExtractor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_encodec import (
      ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
      EncodecModel,
      EncodecPreTrainedModel,
  )

else:
 import sys

 __lowerCAmelCase		       =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


