
"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_a								=						logging.get_logger(__name__)

_a								=						{
    """google/vivit-b-16x2-kinetics400""": (
        """https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}






class        _UpperCAmelCase(       lowerCamelCase      ):
		lowercase__         = 'vivit'



		def __init__(   self							,						__a=2_24							,						__a=32							,						__a=[2, 16, 16]							,						__a=3							,						__a=7_68							,						__a=12							,						__a=12							,						__a=30_72							,						__a="gelu_fast"							,						__a=0.0							,						__a=0.0							,						__a=0.02							,						__a=1e-06							,						__a=True							,						**__a							,						)			->			int:






							'''simple docstring'''
							_UpperCamelCase									=    hidden_size
							_UpperCamelCase									=    num_hidden_layers
							_UpperCamelCase									=    num_attention_heads
							_UpperCamelCase									=    intermediate_size
							_UpperCamelCase									=    hidden_act
							_UpperCamelCase									=    hidden_dropout_prob
							_UpperCamelCase									=    attention_probs_dropout_prob
							_UpperCamelCase									=    initializer_range
							_UpperCamelCase									=    layer_norm_eps

							_UpperCamelCase									=    image_size
							_UpperCamelCase									=    num_frames
							_UpperCamelCase									=    tubelet_size
							_UpperCamelCase									=    num_channels
							_UpperCamelCase									=    qkv_bias

							super().__init__(**__a)













'''simple docstring'''

import jax.numpy as jnp

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


lowercase__		:     int			=							logging.get_logger(__name__)

lowercase__		:     Any			=							'T5Config'







def    a__							(							lowercase   :	jnp.array,   lowercase   :	int,   lowercase   :	int )						->						jnp.ndarray:





     """simple docstring"""

     _UpperCamelCase							       =			jnp.zeros_like(lowercase )
     _UpperCamelCase							       =			shifted_input_ids.at[:, 1:].set(input_ids[:, :-1] )
     _UpperCamelCase							       =			shifted_input_ids.at[:, 0].set(lowercase )

     _UpperCamelCase							       =			jnp.where(shifted_input_ids == -100,   lowercase,   lowercase )
     return shifted_input_ids
class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""
       _snake_case      :	Optional[Any]									=       'mt5'
       _snake_case      :	Union[str, Any]									=       MTaConfig

class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""
       _snake_case      :	Tuple									=       'mt5'
       _snake_case      :	int									=       MTaConfig

class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""
       _snake_case      :	Optional[int]									=       'mt5'
       _snake_case      :	Optional[Any]									=       MTaConfig



