






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        _SCREAMING_SNAKE_CASE			(     __UpperCamelCase ):





	def 		_A					(						self							:   Any					,    __lowerCamelCase							:   int					,    __lowerCamelCase							:   Dict=False      ):
		UpperCamelCase	, UpperCamelCase	, UpperCamelCase	:Dict		=      (
		    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(__lowercase      )					,    """wb"""      ).close()
		UpperCamelCase	:Optional[int]		=      pa.Table.from_pydict({"""filename""": [Path(__lowercase      ).name] * 100}      )
		if take == -1:
			UpperCamelCase	:str		=      len(__lowercase      ) - skip
		if skip is not None and take is not None:
			UpperCamelCase	:Optional[Any]		=      pa_table.slice(__lowercase					,    __lowercase      )
		return pa_table

class        _SCREAMING_SNAKE_CASE			(     __UpperCamelCase ):





	def 		_A					(						self							:   int      ):
		UpperCamelCase	:Optional[int]		=      """my_name"""
		UpperCamelCase	:List[Any]		=      SplitInfo(name="""train"""					,    num_examples=100      )
		UpperCamelCase	:List[str]		=      SplitInfo(name="""test"""					,    num_examples=100      )
		UpperCamelCase	:Any		=      [train_info, test_info]
		UpperCamelCase	:int		=      SplitDict()
		split_dict.add(__lowercase      )
		split_dict.add(__lowercase      )
		UpperCamelCase	:Optional[int]		=      DatasetInfo(splits=__lowercase      )

		with tempfile.TemporaryDirectory() as tmp_dir:
			UpperCamelCase	:Optional[int]		=      ReaderTest(__lowercase					,    __lowercase      )

			UpperCamelCase	:Union[str, Any]		=      """test[:33%]"""
			UpperCamelCase	:List[Any]		=      Dataset(**reader.read(__lowercase					,    __lowercase					,    __lowercase      )      )
			self.assertEqual(dset["""filename"""][0]					,    F"""{name}-test"""      )
			self.assertEqual(dset.num_rows					,    33      )
			self.assertEqual(dset.num_columns					,    1      )

			UpperCamelCase	:Union[str, Any]		=      ["""train""", """test[:33%]"""]
			UpperCamelCase	:Any		=      [Split.TRAIN, ReadInstruction.from_spec("""test[:33%]"""      )]
			for instructions in [instructionsa, instructionsa]:
				UpperCamelCase	:Dict		=      [reader.read(__lowercase					,    __lowercase					,    __lowercase      ) for instr in instructions]
				UpperCamelCase	, UpperCamelCase	:str		=      (Dataset(**__lowercase      ) for dataset_kwargs in datasets_kwargs)
				self.assertEqual(train_dset["""filename"""][0]					,    F"""{name}-train"""      )
				self.assertEqual(train_dset.num_rows					,    100      )
				self.assertEqual(train_dset.num_columns					,    1      )
				self.assertIsInstance(train_dset.split					,    __lowercase      )
				self.assertEqual(str(train_dset.split      )					,    """train"""      )
				self.assertEqual(test_dset["""filename"""][0]					,    F"""{name}-test"""      )
				self.assertEqual(test_dset.num_rows					,    33      )
				self.assertEqual(test_dset.num_columns					,    1      )
				self.assertIsInstance(test_dset.split					,    __lowercase      )
				self.assertEqual(str(test_dset.split      )					,    """test[:33%]"""      )
				del train_dset, test_dset





	def 		_A					(						self							:   Union[str, Any]      ):
		UpperCamelCase	:Union[str, Any]		=      """my_name"""
		UpperCamelCase	:Optional[Any]		=      SplitInfo(name="""train"""					,    num_examples=1_000					,    shard_lengths=[100] * 10      )
		UpperCamelCase	:List[str]		=      [train_info]
		UpperCamelCase	:int		=      SplitDict()
		split_dict.add(__lowercase      )
		UpperCamelCase	:List[Any]		=      DatasetInfo(splits=__lowercase      )

		with tempfile.TemporaryDirectory() as tmp_dir:
			UpperCamelCase	:Any		=      ReaderTest(__lowercase					,    __lowercase      )

			UpperCamelCase	:List[Any]		=      """train[:33%]"""
			UpperCamelCase	:int		=      Dataset(**reader.read(__lowercase					,    __lowercase					,    __lowercase      )      )
			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					,    330      )
			self.assertEqual(dset.num_columns					,    1      )





	def 		_A					(						self							:   List[str]      ):
		UpperCamelCase	:str		=      SplitInfo(name="""train"""					,    num_examples=100      )
		UpperCamelCase	:str		=      SplitInfo(name="""test"""					,    num_examples=100      )
		UpperCamelCase	:Optional[Any]		=      SplitDict()
		split_dict.add(__lowercase      )
		split_dict.add(__lowercase      )
		UpperCamelCase	:Optional[int]		=      DatasetInfo(splits=__lowercase      )

		with tempfile.TemporaryDirectory() as tmp_dir:
			UpperCamelCase	:List[Any]		=      ReaderTest(__lowercase					,    __lowercase      )

			UpperCamelCase	:Any		=      [
			    {"""filename""": os.path.join(__lowercase					,    """train"""      )},
			    {"""filename""": os.path.join(__lowercase					,    """test"""      ), """skip""": 10, """take""": 10},
			]
			UpperCamelCase	:List[str]		=      Dataset(**reader.read_files(__lowercase					,    original_instructions="""train+test[10:20]"""      )      )
			self.assertEqual(dset.num_rows					,    110      )
			self.assertEqual(dset.num_columns					,    1      )
			del dset

@pytest.mark.parametrize("""in_memory"""      ,     [False, True]   )
def   SCREAMING_SNAKE_CASE_				(				__magic_name__   :    str      ,     __magic_name__   :    List[str]      ,     __magic_name__   :    str   )						->     Dict:






	"""simple docstring"""



	UpperCamelCase	:Optional[int]		=      arrow_file
	with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
		UpperCamelCase	:Union[str, Any]		=      ArrowReader.read_table(_SCREAMING_SNAKE_CASE      ,     in_memory=_SCREAMING_SNAKE_CASE   )
	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   SCREAMING_SNAKE_CASE_				(				__magic_name__   :    List[Any]      ,     __magic_name__   :    Optional[Any]      ,     __magic_name__   :    Union[str, Any]   )						->     List[str]:






	"""simple docstring"""



	UpperCamelCase	:Optional[Any]		=      arrow_file
	UpperCamelCase	:List[str]		=      ArrowReader(""""""      ,     _SCREAMING_SNAKE_CASE   )
	with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
		UpperCamelCase	:int		=      reader.read_files([{"""filename""": filename}]      ,     in_memory=_SCREAMING_SNAKE_CASE   )
	assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
	UpperCamelCase	:List[str]		=      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   SCREAMING_SNAKE_CASE_				(				)						->     Optional[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	:Optional[Any]		=      """train+test"""
	assert ReadInstruction.from_spec(_SCREAMING_SNAKE_CASE   ).to_spec() == spec_train_test

	UpperCamelCase	:Tuple		=      """train[2:10]"""
	assert ReadInstruction.from_spec(_SCREAMING_SNAKE_CASE   ).to_spec() == spec_train_abs

	UpperCamelCase	:str		=      """train[15%:-20%]"""
	assert ReadInstruction.from_spec(_SCREAMING_SNAKE_CASE   ).to_spec() == spec_train_pct

	UpperCamelCase	:Dict		=      """train[:10%](closest)"""
	assert ReadInstruction.from_spec(_SCREAMING_SNAKE_CASE   ).to_spec() == "train[:10%]"

	UpperCamelCase	:Any		=      """train[:10%](pct1_dropremainder)"""
	assert ReadInstruction.from_spec(_SCREAMING_SNAKE_CASE   ).to_spec() == spec_train_pct_rounding

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

def   SCREAMING_SNAKE_CASE_				(				)						->     Optional[Any]:






	"""simple docstring"""



	UpperCamelCase	:List[Any]		=      """dummy"""
	UpperCamelCase	:Any		=      [SplitInfo(name="""train"""      ,     num_examples=100   )]
	UpperCamelCase	:Tuple		=      """train[:33%]"""
	UpperCamelCase	:Dict		=      """arrow"""
	UpperCamelCase	:Any		=      """prefix"""

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

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

@pytest.mark.parametrize("""name, expected_exception"""      ,     [(None, TypeError), ("""""", ValueError)]   )
def   SCREAMING_SNAKE_CASE_				(				__magic_name__   :    List[Any]      ,     __magic_name__   :    Union[str, Any]   )						->     List[Any]:






	"""simple docstring"""



	UpperCamelCase	:Tuple		=      [SplitInfo(name="""train"""      ,     num_examples=100   )]
	UpperCamelCase	:Optional[int]		=      """train"""
	UpperCamelCase	:Tuple		=      """arrow"""
	UpperCamelCase	:int		=      """prefix_path"""
	with pytest.raises(_SCREAMING_SNAKE_CASE   ):
		UpperCamelCase	:int		=      make_file_instructions(_SCREAMING_SNAKE_CASE      ,     _SCREAMING_SNAKE_CASE      ,     _SCREAMING_SNAKE_CASE      ,     _SCREAMING_SNAKE_CASE      ,     _SCREAMING_SNAKE_CASE   )








"""simple docstring"""



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


a  :						Optional[Any]					       =							logging.get_logger(__name__)

a  :						int					       =							{
    '''facebook/opt-125m''': '''https://huggingface.co/facebook/opt-125m/blob/main/config.json''',
    '''facebook/opt-350m''': '''https://huggingface.co/facebook/opt-350m/blob/main/config.json''',
    '''facebook/opt-1.3b''': '''https://huggingface.co/facebook/opt-1.3b/blob/main/config.json''',
    '''facebook/opt-2.7b''': '''https://huggingface.co/facebook/opt-2.7b/blob/main/config.json''',
    '''facebook/opt-6.7b''': '''https://huggingface.co/facebook/opt-6.7b/blob/main/config.json''',
    '''facebook/opt-13b''': '''https://huggingface.co/facebook/opt-13b/blob/main/config.json''',
}


class 	_UpperCamelCase ( __UpperCamelCase							):



    '''simple docstring'''


    __lowercase    :   Optional[Any]											=						'opt'
    __lowercase    :   str											=						['past_key_values']


    def __init__(      self   ,			__lowercase=50272   ,			__lowercase=768   ,			__lowercase=12   ,			__lowercase=3072   ,			__lowercase=2048   ,			__lowercase=True   ,			__lowercase=False   ,			__lowercase=None   ,			__lowercase=0.1   ,			__lowercase=0.0   ,			__lowercase=12   ,			__lowercase="relu"   ,			__lowercase=0.0   ,			__lowercase=0.02   ,			__lowercase=True   ,			__lowercase=1   ,			__lowercase=2   ,			__lowercase=2   ,			__lowercase=True   ,			__lowercase=True   ,			**__lowercase   ,			):
     super().__init__(
         pad_token_id=__lowercase   ,			bos_token_id=__lowercase   ,			eos_token_id=__lowercase   ,			**__lowercase   ,			)
     UpperCAmelCase__ 						=				vocab_size
     UpperCAmelCase__ 						=				max_position_embeddings
     UpperCAmelCase__ 						=				num_attention_heads
     UpperCAmelCase__ 						=				word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
     UpperCAmelCase__ 						=				ffn_dim
     UpperCAmelCase__ 						=				hidden_size
     UpperCAmelCase__ 						=				num_hidden_layers
     UpperCAmelCase__ 						=				dropout
     UpperCAmelCase__ 						=				attention_dropout
     UpperCAmelCase__ 						=				activation_function
     UpperCAmelCase__ 						=				init_std
     UpperCAmelCase__ 						=				layerdrop
     UpperCAmelCase__ 						=				use_cache
     UpperCAmelCase__ 						=				do_layer_norm_before
     # We keep these variables at `True` for backward compatibility.
     UpperCAmelCase__ 						=				enable_bias
     UpperCAmelCase__ 						=				layer_norm_elementwise_affine

     # Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
     # with checkpoints that have been fine-tuned before transformers v4.20.1
     # see https://github.com/facebookresearch/metaseq/pull/164
     UpperCAmelCase__ 						=				_remove_final_layer_norm



