

"""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


__A						       =      logging.get_logger(__name__)

__A						       =      "T5Config"






def    a__   (   __SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE			)     ->     jnp.ndarray:
		__lowerCAmelCase:	int   				=      jnp.zeros_like(__SCREAMING_SNAKE_CASE			)
		__lowerCAmelCase:	Tuple   				=      shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]			)
		__lowerCAmelCase:	Tuple   				=      shifted_input_ids.at[:, 0].set(__SCREAMING_SNAKE_CASE			)

		__lowerCAmelCase:	Any   				=      jnp.where(shifted_input_ids == -1_0_0 ,			__SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE			)
		return shifted_input_ids





class    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Tuple       				=  """mt5"""
				SCREAMING_SNAKE_CASE_       :				Dict       				=  MTaConfig





class    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				str       				=  """mt5"""
				SCREAMING_SNAKE_CASE_       :				Tuple       				=  MTaConfig





class    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Tuple       				=  """mt5"""
				SCREAMING_SNAKE_CASE_       :				List[str]       				=  MTaConfig





"""simple docstring"""


from math import ceil






def    a__   (   __SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE			)     ->     str:
		__lowerCAmelCase:	Tuple   				=      list(range(0 ,			__SCREAMING_SNAKE_CASE			)			)

		__lowerCAmelCase:	Optional[Any]   				=      [item for sublist in list(device_map.values()			) for item in sublist]

		# Duplicate check
		__lowerCAmelCase:	List[Any]   				=      []
		for i in device_map_blocks:
				if device_map_blocks.count(__SCREAMING_SNAKE_CASE			) > 1 and i not in duplicate_blocks:
						duplicate_blocks.append(__SCREAMING_SNAKE_CASE			)
    # Missing blocks
		__lowerCAmelCase:	Optional[Any]   				=      [i for i in blocks if i not in device_map_blocks]
		__lowerCAmelCase:	List[Any]   				=      [i for i in device_map_blocks if i not in blocks]

		if len(__SCREAMING_SNAKE_CASE			) != 0:
				raise ValueError(
				    "Duplicate attention blocks specified in device_map. Attention blocks must be specified to one device."
				    " These attention blocks were specified more than once: " + str(__SCREAMING_SNAKE_CASE			)			)
		if len(__SCREAMING_SNAKE_CASE			) != 0:
				raise ValueError(
				    "There are attention blocks for this model that are not specified in the device_map. Add these attention "
				    "blocks to a device on the device_map: " + str(__SCREAMING_SNAKE_CASE			)			)
		if len(__SCREAMING_SNAKE_CASE			) != 0:
				raise ValueError(
				    "The device_map contains more attention blocks than this model has. Remove these from the device_map:"
				    + str(__SCREAMING_SNAKE_CASE			)			)






def    a__   (   __SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE			)     ->     str:
		__lowerCAmelCase:	List[Any]   				=      list(range(__SCREAMING_SNAKE_CASE			)			)
		__lowerCAmelCase:	Dict   				=      int(ceil(n_layers / len(__SCREAMING_SNAKE_CASE			)			)			)
		__lowerCAmelCase:	Union[str, Any]   				=      [layers[i : i + n_blocks] for i in range(0 ,			__SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE			)]

		return dict(zip(__SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE			)			)


