


"""simple docstring"""







import random
import unittest

from torch.utils.data import BatchSampler, DataLoader, IterableDataset

from accelerate import Accelerator
from accelerate.data_loader import (
    BatchSamplerShard,
    DataLoaderDispatcher,
    DataLoaderShard,
    IterableDatasetShard,
    SkipBatchSampler,
    SkipDataLoader,
    skip_first_batches,
)


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       def __init__(						self		,     snake_case__=0.01		,     snake_case__=1_000						):






         """simple docstring"""





         lowerCAmelCase     :     List[Any]								=							p_stop
         lowerCAmelCase     :     Optional[Any]								=							max_length







       def __iter__(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Optional[Any]								=							0
         lowerCAmelCase     :     Tuple								=							False
         while not stop and count < self.max_length:
           yield count
           count += 1
           lowerCAmelCase     :     Dict								=							random.random() < self.p_stop


class       SCREAMING_SNAKE_CASE__				(		unittest.TestCase				):
       """simple docstring"""


       def        lowercase__							(						self		,     snake_case__		,     snake_case__		,     snake_case__=False		,     snake_case__=True						):






         """simple docstring"""





         lowerCAmelCase     :     Dict								=							[
             BatchSamplerShard(snake_case__		,     2		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)
             for i in range(2						)
         ]
         lowerCAmelCase     :     Any								=							[list(snake_case__						) for batch_sampler_shard in batch_sampler_shards]
         if not split_batches:
           self.assertListEqual([len(snake_case__						) for shard in batch_sampler_shards]		,     [len(snake_case__						) for e in expected]						)
         self.assertListEqual(snake_case__		,     snake_case__						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Union[str, Any]								=							BatchSampler(range(24						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Any								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19, 20]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17], [21, 22, 23]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         lowerCAmelCase     :     Tuple								=							BatchSampler(range(24						)		,     batch_size=3		,     drop_last=snake_case__						)
         # Expected shouldn't change
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         # Check the shards when the dataset is a round multiple of batch size but not total batch size.
         lowerCAmelCase     :     Union[str, Any]								=							BatchSampler(range(21						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19, 20]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17], [0, 1, 2]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         lowerCAmelCase     :     Tuple								=							BatchSampler(range(21						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Any								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size but has a multiple of
         # num_processes batch.
         lowerCAmelCase     :     List[str]								=							BatchSampler(range(22						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Dict								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19, 20]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17], [21, 0, 1]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         lowerCAmelCase     :     Dict								=							BatchSampler(range(22						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Optional[Any]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size but and has not a multiple of
         # num_processes batch.
         lowerCAmelCase     :     Any								=							BatchSampler(range(20						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Tuple								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19, 0]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17], [1, 2, 3]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         lowerCAmelCase     :     List[str]								=							BatchSampler(range(20						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         # Check the shards when the dataset is very small.
         lowerCAmelCase     :     Dict								=							BatchSampler(range(2						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Union[str, Any]								=							[[[0, 1, 0]], [[1, 0, 1]]]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

         lowerCAmelCase     :     Optional[Any]								=							BatchSampler(range(2						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Any								=							[[], []]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Tuple								=							BatchSampler(range(24						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     int								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17], [20, 21]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19], [22, 23]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

         lowerCAmelCase     :     Dict								=							BatchSampler(range(24						)		,     batch_size=4		,     drop_last=snake_case__						)
         # Expected shouldn't change
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size.
         lowerCAmelCase     :     Optional[int]								=							BatchSampler(range(22						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Optional[Any]								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17], [20, 21]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19], [0, 1]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

         lowerCAmelCase     :     List[Any]								=							BatchSampler(range(22						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size or num_processes.
         lowerCAmelCase     :     Tuple								=							BatchSampler(range(21						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17], [20, 0]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19], [1, 2]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

         lowerCAmelCase     :     Any								=							BatchSampler(range(21						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Optional[Any]								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

         # Check the shards when the dataset is very small.
         lowerCAmelCase     :     Optional[Any]								=							BatchSampler(range(2						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Optional[int]								=							[[[0, 1]], [[0, 1]]]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

         lowerCAmelCase     :     Optional[Any]								=							BatchSampler(range(2						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Optional[int]								=							[[], []]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Optional[int]								=							BatchSampler(range(24						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Any								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19, 20]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17], [21, 22, 23]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     Optional[Any]								=							BatchSampler(range(24						)		,     batch_size=3		,     drop_last=snake_case__						)
         # Expected shouldn't change
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         # Check the shards when the dataset is a round multiple of batch size but not total batch size.
         lowerCAmelCase     :     Dict								=							BatchSampler(range(21						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Dict								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19, 20]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     int								=							BatchSampler(range(21						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size but has a multiple of
         # num_processes batch.
         lowerCAmelCase     :     str								=							BatchSampler(range(22						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Union[str, Any]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19, 20]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17], [21]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     List[str]								=							BatchSampler(range(22						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Union[str, Any]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size but and has not a multiple of
         # num_processes batch.
         lowerCAmelCase     :     str								=							BatchSampler(range(20						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Union[str, Any]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14], [18, 19]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     Any								=							BatchSampler(range(20						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Union[str, Any]								=							[
             [[0, 1, 2], [6, 7, 8], [12, 13, 14]],
             [[3, 4, 5], [9, 10, 11], [15, 16, 17]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         # Check the shards when the dataset is very small.
         lowerCAmelCase     :     Optional[int]								=							BatchSampler(range(2						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[[[0, 1]], []]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     str								=							BatchSampler(range(2						)		,     batch_size=3		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Optional[Any]								=							[[], []]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     even_batches=snake_case__						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     str								=							BatchSampler(range(24						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Dict								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17], [20, 21]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19], [22, 23]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     List[Any]								=							BatchSampler(range(24						)		,     batch_size=4		,     drop_last=snake_case__						)
         # Expected shouldn't change
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size.
         lowerCAmelCase     :     Tuple								=							BatchSampler(range(22						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17], [20, 21]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     int								=							BatchSampler(range(22						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     str								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

         # Check the shards when the dataset is not a round multiple of batch size or num_processes.
         lowerCAmelCase     :     int								=							BatchSampler(range(21						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     str								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17], [20]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     str								=							BatchSampler(range(21						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     Union[str, Any]								=							[
             [[0, 1], [4, 5], [8, 9], [12, 13], [16, 17]],
             [[2, 3], [6, 7], [10, 11], [14, 15], [18, 19]],
         ]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

         # Check the shards when the dataset is very small.
         lowerCAmelCase     :     Optional[Any]								=							BatchSampler(range(2						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     int								=							[[[0, 1]], []]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

         lowerCAmelCase     :     Dict								=							BatchSampler(range(2						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[str]								=							[[], []]
         self.check_batch_sampler_shards(snake_case__		,     snake_case__		,     split_batches=snake_case__		,     even_batches=snake_case__						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     List[str]								=							[[0, 1, 2], [3, 4], [5, 6, 7, 8], [9, 10, 11], [12, 13]]
         lowerCAmelCase     :     Tuple								=							[BatchSamplerShard(snake_case__		,     2		,     snake_case__		,     even_batches=snake_case__						) for i in range(2						)]

         self.assertEqual(len(batch_sampler_shards[0]						)		,     3						)
         self.assertEqual(len(batch_sampler_shards[1]						)		,     2						)

         self.assertListEqual(list(batch_sampler_shards[0]						)		,     [[0, 1, 2], [5, 6, 7, 8], [12, 13]]						)
         self.assertListEqual(list(batch_sampler_shards[1]						)		,     [[3, 4], [9, 10, 11]]						)

       def        lowercase__							(						self		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__=False		,     snake_case__=2		,     snake_case__=False						):






         """simple docstring"""





         random.seed(snake_case__						)
         lowerCAmelCase     :     List[str]								=							list(snake_case__						)

         lowerCAmelCase     :     Optional[int]								=							[
             IterableDatasetShard(
                 snake_case__		,     batch_size=snake_case__		,     drop_last=snake_case__		,     num_processes=snake_case__		,     process_index=snake_case__		,     split_batches=snake_case__		,     )
             for i in range(snake_case__						)
         ]
         lowerCAmelCase     :     str								=							[]
         for iterable_dataset_shard in iterable_dataset_shards:
           # Since our random iterable dataset will be... random... we need to use a seed to get reproducible results.
           random.seed(snake_case__						)
           iterable_dataset_lists.append(list(snake_case__						)						)

         lowerCAmelCase     :     List[Any]								=							batch_size // num_processes if split_batches else batch_size
         # All iterable dataset shard should have the same length, a round multiple of shard_batch_size
         lowerCAmelCase     :     Tuple								=							iterable_dataset_lists[0]
         for l in iterable_dataset_lists[1:]:
           self.assertEqual(len(snake_case__						)		,     len(snake_case__						)						)
           self.assertTrue(len(snake_case__						) % shard_batch_size == 0						)

         lowerCAmelCase     :     List[Any]								=							[]
         for idx in range(0		,     len(snake_case__						)		,     snake_case__						):
           for l in iterable_dataset_lists:
             observed += l[idx : idx + shard_batch_size]

         if not drop_last:
           while len(snake_case__						) < len(snake_case__						):
             reference += reference
         self.assertListEqual(snake_case__		,     reference[: len(snake_case__						)]						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     List[str]								=							42
         lowerCAmelCase     :     Tuple								=							RandomIterableDataset()

         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)
         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)
         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)
         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)

         # Edge case with a very small dataset
         lowerCAmelCase     :     List[str]								=							RandomIterableDataset(max_length=2						)

         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)
         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)
         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)
         self.check_iterable_dataset_shards(snake_case__		,     snake_case__		,     batch_size=4		,     drop_last=snake_case__		,     split_batches=snake_case__						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Tuple								=							BatchSampler(range(16						)		,     batch_size=4		,     drop_last=snake_case__						)
         lowerCAmelCase     :     List[Any]								=							SkipBatchSampler(snake_case__		,     2						)
         self.assertListEqual(list(snake_case__						)		,     [[8, 9, 10, 11], [12, 13, 14, 15]]						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     List[str]								=							SkipDataLoader(list(range(16						)						)		,     batch_size=4		,     skip_batches=2						)
         self.assertListEqual([t.tolist() for t in dataloader]		,     [[8, 9, 10, 11], [12, 13, 14, 15]]						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     int								=							DataLoader(list(range(16						)						)		,     batch_size=4						)
         lowerCAmelCase     :     Optional[int]								=							skip_first_batches(snake_case__		,     num_batches=2						)
         self.assertListEqual([t.tolist() for t in new_dataloader]		,     [[8, 9, 10, 11], [12, 13, 14, 15]]						)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Tuple								=							DataLoaderShard(list(range(16						)						)		,     batch_size=4						)
         for idx, _ in enumerate(snake_case__						):
           self.assertEqual(dataloader.end_of_dataloader		,     idx == 3						)

         # Test it also works on the second iteration
         for idx, _ in enumerate(snake_case__						):
           self.assertEqual(dataloader.end_of_dataloader		,     idx == 3						)







       def        lowercase__							(						self						):






         """simple docstring"""





         Accelerator()
         lowerCAmelCase     :     Dict								=							DataLoaderDispatcher(range(16						)		,     batch_size=4						)
         for idx, _ in enumerate(snake_case__						):
           self.assertEqual(dataloader.end_of_dataloader		,     idx == 3						)

         # Test it also works on the second iteration
         for idx, _ in enumerate(snake_case__						):
           self.assertEqual(dataloader.end_of_dataloader		,     idx == 3						)









"""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


lowerCAmelCase__      				=   logging.get_logger(__name__)

lowerCAmelCase__      				=   '''T5Config'''
def 					a__			(				SCREAMING_SNAKE_CASE    :    jnp.array				,      SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    int				):


  '''simple docstring'''







  lowerCAmelCase     :     List[str]								=							jnp.zeros_like(SCREAMING_SNAKE_CASE				)
  lowerCAmelCase     :     Optional[int]								=							shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]				)
  lowerCAmelCase     :     List[str]								=							shifted_input_ids.at[:, 0].set(SCREAMING_SNAKE_CASE				)

  lowerCAmelCase     :     str								=							jnp.where(shifted_input_ids == -1_0_0				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
  return shifted_input_ids


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				List[Any]   ="mt5"
       a  :				Tuple   =MTaConfig


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				Union[str, Any]   ="mt5"
       a  :				Optional[Any]   =MTaConfig


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				str   ="mt5"
       a  :				Dict   =MTaConfig





