from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


UpperCamelCase__       							=      logging.get_logger(__name__)

UpperCamelCase__       							=      {
    'google/long-t5-local-base': 'https://huggingface.co/google/long-t5-local-base/blob/main/config.json',
    'google/long-t5-local-large': 'https://huggingface.co/google/long-t5-local-large/blob/main/config.json',
    'google/long-t5-tglobal-base': 'https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json',
    'google/long-t5-tglobal-large': 'https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json',
}





class   A							(       UpperCAmelCase_  ):
   __UpperCAmelCase				:				Any          =    'longt5'
   __UpperCAmelCase				:				Any          =    ['past_key_values']
   __UpperCAmelCase				:				Optional[Any]          =    {'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}


   def __init__(self  :		Union[str, Any] ,						__UpperCAmelCase  :		Any=3_2_1_2_8 ,						__UpperCAmelCase  :		Optional[Any]=5_1_2 ,						__UpperCAmelCase  :		int=6_4 ,						__UpperCAmelCase  :		List[Any]=2_0_4_8 ,						__UpperCAmelCase  :		Any=6 ,						__UpperCAmelCase  :		Optional[Any]=None ,						__UpperCAmelCase  :		Union[str, Any]=8 ,						__UpperCAmelCase  :		Optional[Any]=1_2_7 ,						__UpperCAmelCase  :		Optional[Any]=1_6 ,						__UpperCAmelCase  :		str=3_2 ,						__UpperCAmelCase  :		Optional[Any]=1_2_8 ,						__UpperCAmelCase  :		Optional[Any]=0.1 ,						__UpperCAmelCase  :		int=1E-6 ,						__UpperCAmelCase  :		Tuple=1.0 ,						__UpperCAmelCase  :		Optional[Any]="relu" ,						__UpperCAmelCase  :		Optional[Any]=True ,						__UpperCAmelCase  :		str="local" ,						__UpperCAmelCase  :		Dict=True ,						__UpperCAmelCase  :		Union[str, Any]=0 ,						__UpperCAmelCase  :		List[str]=1 ,						**__UpperCAmelCase  :		Dict ,						)		->       Dict:
         """simple docstring"""



         UpperCAmelCase__			=						vocab_size
         UpperCAmelCase__			=						d_model
         UpperCAmelCase__			=						d_kv
         UpperCAmelCase__			=						d_ff
         UpperCAmelCase__			=						num_layers
         # default = symmetry
         UpperCAmelCase__			=						num_decoder_layers if num_decoder_layers is not None else self.num_layers
         UpperCAmelCase__			=						num_heads
         UpperCAmelCase__			=						local_radius
         UpperCAmelCase__			=						global_block_size
         UpperCAmelCase__			=						relative_attention_num_buckets
         UpperCAmelCase__			=						relative_attention_max_distance
         UpperCAmelCase__			=						dropout_rate
         UpperCAmelCase__			=						layer_norm_epsilon
         UpperCAmelCase__			=						initializer_factor
         UpperCAmelCase__			=						feed_forward_proj
         UpperCAmelCase__			=						encoder_attention_type
         UpperCAmelCase__			=						use_cache

         UpperCAmelCase__			=						self.feed_forward_proj.split("-"	)
         UpperCAmelCase__			=						act_info[-1]
         UpperCAmelCase__			=						act_info[0] == "gated"

         if len(__UpperCAmelCase	) > 1 and act_info[0] != "gated" or len(__UpperCAmelCase	) > 2:
               raise ValueError(
                   f"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
                   "Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. "
                   "'gated-gelu' or 'relu'"	)

         # for backwards compatibility
         if feed_forward_proj == "gated-gelu":
               UpperCAmelCase__			=						"gelu_new"

         super().__init__(
             pad_token_id=__UpperCAmelCase ,						eos_token_id=__UpperCAmelCase ,						is_encoder_decoder=__UpperCAmelCase ,						**__UpperCAmelCase ,						)





class   A							(       UpperCAmelCase_  ):


   @property
   def     lowercase_   (self  :		Optional[Any]	)		->       Mapping[str, Mapping[int, str]]:
         """simple docstring"""



         UpperCAmelCase__			=						{
             "input_ids": {0: "batch", 1: "encoder_sequence"},
             "attention_mask": {0: "batch", 1: "encoder_sequence"},
         }
         if self.use_past:
               UpperCAmelCase__			=						"past_encoder_sequence + sequence"
               UpperCAmelCase__			=						{0: "batch"}
               UpperCAmelCase__			=						{0: "batch", 1: "past_decoder_sequence + sequence"}
         else:
               UpperCAmelCase__			=						{0: "batch", 1: "decoder_sequence"}
               UpperCAmelCase__			=						{0: "batch", 1: "decoder_sequence"}

         if self.use_past:
               self.fill_with_past_key_values_(__UpperCAmelCase ,						direction="inputs"	)

         return common_inputs





   @property
   def     lowercase_   (self  :		List[Any]	)		->       int:
         """simple docstring"""



         return 1_3




import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases





class   A							(       UpperCAmelCase_  ):


   def     lowercase_   (self  :		Dict ,						__UpperCAmelCase  :		Optional[int] ,						__UpperCAmelCase  :		List[str]=False	)		->       Union[str, Any]:
         """simple docstring"""



         UpperCAmelCase__	,   UpperCAmelCase__	,   UpperCAmelCase__			=						(
             filename_skip_take["filename"],
             filename_skip_take["skip"] if "skip" in filename_skip_take else None,
             filename_skip_take["take"] if "take" in filename_skip_take else None,
         )
         open(os.path.join(__UpperCAmelCase	) ,						"wb"	).close()
         UpperCAmelCase__			=						pa.Table.from_pydict({"filename": [Path(__UpperCAmelCase	).name] * 1_0_0}	)
         if take == -1:
               UpperCAmelCase__			=						len(__UpperCAmelCase	) - skip
         if skip is not None and take is not None:
               UpperCAmelCase__			=						pa_table.slice(__UpperCAmelCase ,						__UpperCAmelCase	)
         return pa_table





class   A							(       UpperCAmelCase_  ):


   def     lowercase_   (self  :		Tuple	)		->       Tuple:
         """simple docstring"""



         UpperCAmelCase__			=						"my_name"
         UpperCAmelCase__			=						SplitInfo(name="train" ,						num_examples=1_0_0	)
         UpperCAmelCase__			=						SplitInfo(name="test" ,						num_examples=1_0_0	)
         UpperCAmelCase__			=						[train_info, test_info]
         UpperCAmelCase__			=						SplitDict()
         split_dict.add(__UpperCAmelCase	)
         split_dict.add(__UpperCAmelCase	)
         UpperCAmelCase__			=						DatasetInfo(splits=__UpperCAmelCase	)

         with tempfile.TemporaryDirectory() as tmp_dir:
               UpperCAmelCase__			=						ReaderTest(__UpperCAmelCase ,						__UpperCAmelCase	)

               UpperCAmelCase__			=						"test[:33%]"
               UpperCAmelCase__			=						Dataset(**reader.read(__UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase	)	)
               self.assertEqual(dset["filename"][0] ,						f"""{name}-test"""	)
               self.assertEqual(dset.num_rows ,						3_3	)
               self.assertEqual(dset.num_columns ,						1	)

               UpperCAmelCase__			=						["train", "test[:33%]"]
               UpperCAmelCase__			=						[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"	)]
               for instructions in [instructionsa, instructionsa]:
                     UpperCAmelCase__			=						[reader.read(__UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase	) for instr in instructions]
                     UpperCAmelCase__	,   UpperCAmelCase__			=						(Dataset(**__UpperCAmelCase	) for dataset_kwargs in datasets_kwargs)
                     self.assertEqual(train_dset["filename"][0] ,						f"""{name}-train"""	)
                     self.assertEqual(train_dset.num_rows ,						1_0_0	)
                     self.assertEqual(train_dset.num_columns ,						1	)
                     self.assertIsInstance(train_dset.split ,						__UpperCAmelCase	)
                     self.assertEqual(str(train_dset.split	) ,						"train"	)
                     self.assertEqual(test_dset["filename"][0] ,						f"""{name}-test"""	)
                     self.assertEqual(test_dset.num_rows ,						3_3	)
                     self.assertEqual(test_dset.num_columns ,						1	)
                     self.assertIsInstance(test_dset.split ,						__UpperCAmelCase	)
                     self.assertEqual(str(test_dset.split	) ,						"test[:33%]"	)
                     del train_dset, test_dset


   def     lowercase_   (self  :		Any	)		->       Any:
         """simple docstring"""



         UpperCAmelCase__			=						"my_name"
         UpperCAmelCase__			=						SplitInfo(name="train" ,						num_examples=1_0_0_0 ,						shard_lengths=[1_0_0] * 1_0	)
         UpperCAmelCase__			=						[train_info]
         UpperCAmelCase__			=						SplitDict()
         split_dict.add(__UpperCAmelCase	)
         UpperCAmelCase__			=						DatasetInfo(splits=__UpperCAmelCase	)

         with tempfile.TemporaryDirectory() as tmp_dir:
               UpperCAmelCase__			=						ReaderTest(__UpperCAmelCase ,						__UpperCAmelCase	)

               UpperCAmelCase__			=						"train[:33%]"
               UpperCAmelCase__			=						Dataset(**reader.read(__UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase	)	)
               self.assertEqual(dset["filename"][0] ,						f"""{name}-train-00000-of-00010"""	)
               self.assertEqual(dset["filename"][-1] ,						f"""{name}-train-00003-of-00010"""	)
               self.assertEqual(dset.num_rows ,						3_3_0	)
               self.assertEqual(dset.num_columns ,						1	)





   def     lowercase_   (self  :		Dict	)		->       Dict:
         """simple docstring"""



         UpperCAmelCase__			=						SplitInfo(name="train" ,						num_examples=1_0_0	)
         UpperCAmelCase__			=						SplitInfo(name="test" ,						num_examples=1_0_0	)
         UpperCAmelCase__			=						SplitDict()
         split_dict.add(__UpperCAmelCase	)
         split_dict.add(__UpperCAmelCase	)
         UpperCAmelCase__			=						DatasetInfo(splits=__UpperCAmelCase	)

         with tempfile.TemporaryDirectory() as tmp_dir:
               UpperCAmelCase__			=						ReaderTest(__UpperCAmelCase ,						__UpperCAmelCase	)

               UpperCAmelCase__			=						[
                   {"filename": os.path.join(__UpperCAmelCase ,						"train"	)},
                   {"filename": os.path.join(__UpperCAmelCase ,						"test"	), "skip": 1_0, "take": 1_0},
               ]
               UpperCAmelCase__			=						Dataset(**reader.read_files(__UpperCAmelCase ,						original_instructions="train+test[10:20]"	)	)
               self.assertEqual(dset.num_rows ,						1_1_0	)
               self.assertEqual(dset.num_columns ,						1	)
               del dset




@pytest.mark.parametrize("in_memory",						[False, True]							)
def      lowerCAmelCase_				(  __A,						__A,						__A							)  ->       List[Any]:







      '''simple docstring'''


      UpperCAmelCase__			=						arrow_file
      with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
            UpperCAmelCase__			=						ArrowReader.read_table(__A,						in_memory=__A							)
      assert table.shape == dataset.data.shape
      assert set(table.column_names							) == set(dataset.data.column_names							)
      assert dict(table.to_pydict()							) == dict(dataset.data.to_pydict()							)  # to_pydict returns OrderedDict




@pytest.mark.parametrize("in_memory",						[False, True]							)
def      lowerCAmelCase_				(  __A,						__A,						__A							)  ->       Tuple:







      '''simple docstring'''


      UpperCAmelCase__			=						arrow_file
      UpperCAmelCase__			=						ArrowReader("",						__A							)
      with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
            UpperCAmelCase__			=						reader.read_files([{"filename": filename}],						in_memory=__A							)
      assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
      UpperCAmelCase__			=						dataset_kwargs["arrow_table"]
      assert table.shape == dataset.data.shape
      assert set(table.column_names							) == set(dataset.data.column_names							)
      assert dict(table.to_pydict()							) == dict(dataset.data.to_pydict()							)  # to_pydict returns OrderedDict




def      lowerCAmelCase_				(  )  ->       Any:







      '''simple docstring'''


      assert ReadInstruction("train",						to=10,						unit="abs"							).to_spec() == "train[:10]"
      assert ReadInstruction("train",						from_=-80,						to=10,						unit="%"							).to_spec() == "train[-80%:10%]"

      UpperCAmelCase__			=						"train+test"
      assert ReadInstruction.from_spec(__A							).to_spec() == spec_train_test

      UpperCAmelCase__			=						"train[2:10]"
      assert ReadInstruction.from_spec(__A							).to_spec() == spec_train_abs

      UpperCAmelCase__			=						"train[15%:-20%]"
      assert ReadInstruction.from_spec(__A							).to_spec() == spec_train_pct

      UpperCAmelCase__			=						"train[:10%](closest)"
      assert ReadInstruction.from_spec(__A							).to_spec() == "train[:10%]"

      UpperCAmelCase__			=						"train[:10%](pct1_dropremainder)"
      assert ReadInstruction.from_spec(__A							).to_spec() == spec_train_pct_rounding

      UpperCAmelCase__			=						"train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"
      assert ReadInstruction.from_spec(__A							).to_spec() == spec_train_test_pct_rounding




def      lowerCAmelCase_				(  )  ->       int:







      '''simple docstring'''


      UpperCAmelCase__			=						"dummy"
      UpperCAmelCase__			=						[SplitInfo(name="train",						num_examples=100							)]
      UpperCAmelCase__			=						"train[:33%]"
      UpperCAmelCase__			=						"arrow"
      UpperCAmelCase__			=						"prefix"

      UpperCAmelCase__			=						make_file_instructions(__A,						__A,						__A,						__A,						__A							)
      assert isinstance(__A,						__A							)
      assert file_instructions.num_examples == 33
      assert file_instructions.file_instructions == [
          {"filename": os.path.join(__A,						f"""{name}-train.arrow"""							), "skip": 0, "take": 33}
      ]

      UpperCAmelCase__			=						[SplitInfo(name="train",						num_examples=100,						shard_lengths=[10] * 10							)]
      UpperCAmelCase__			=						make_file_instructions(__A,						__A,						__A,						__A,						__A							)
      assert isinstance(__A,						__A							)
      assert file_instructions.num_examples == 33
      assert file_instructions.file_instructions == [
          {"filename": os.path.join(__A,						f"""{name}-train-00000-of-00010.arrow"""							), "skip": 0, "take": -1},
          {"filename": os.path.join(__A,						f"""{name}-train-00001-of-00010.arrow"""							), "skip": 0, "take": -1},
          {"filename": os.path.join(__A,						f"""{name}-train-00002-of-00010.arrow"""							), "skip": 0, "take": -1},
          {"filename": os.path.join(__A,						f"""{name}-train-00003-of-00010.arrow"""							), "skip": 0, "take": 3},
      ]







@pytest.mark.parametrize("name, expected_exception",						[(None, TypeError), ("", ValueError)]							)
def      lowerCAmelCase_				(  __A,						__A							)  ->       Optional[Any]:







      '''simple docstring'''


      UpperCAmelCase__			=						[SplitInfo(name="train",						num_examples=100							)]
      UpperCAmelCase__			=						"train"
      UpperCAmelCase__			=						"arrow"
      UpperCAmelCase__			=						"prefix_path"
      with pytest.raises(__A							):
            UpperCAmelCase__			=						make_file_instructions(__A,						__A,						__A,						__A,						__A							)



