





from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase__          =logging.get_logger(__name__)

UpperCamelCase__          ={
    'nghuyong/ernie-1.0-base-zh': 'https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json',
    'nghuyong/ernie-2.0-base-en': 'https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json',
    'nghuyong/ernie-2.0-large-en': 'https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json',
    'nghuyong/ernie-3.0-base-zh': 'https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-medium-zh': 'https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-mini-zh': 'https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-micro-zh': 'https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-nano-zh': 'https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json',
    'nghuyong/ernie-gram-zh': 'https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json',
    'nghuyong/ernie-health-zh': 'https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json',
}





class 	lowerCAmelCase__(       __lowercase			):






       '''simple docstring'''


       __snake_case       	=			'ernie'




       def __init__(					self			,  __lowerCamelCase=3_0_5_2_2			,  __lowerCamelCase=7_6_8			,  __lowerCamelCase=1_2			,  __lowerCamelCase=1_2			,  __lowerCamelCase=3_0_7_2			,  __lowerCamelCase="gelu"			,  __lowerCamelCase=0.1			,  __lowerCamelCase=0.1			,  __lowerCamelCase=5_1_2			,  __lowerCamelCase=2			,  __lowerCamelCase=3			,  __lowerCamelCase=False			,  __lowerCamelCase=0.02			,  __lowerCamelCase=1E-12			,  __lowerCamelCase=0			,  __lowerCamelCase="absolute"			,  __lowerCamelCase=True			,  __lowerCamelCase=None			,  **__lowerCamelCase			,  )	->   Any:
            super().__init__(pad_token_id=__lowerCamelCase			,  **__lowerCamelCase							)

            _SCREAMING_SNAKE_CASE				:		Dict  			=							vocab_size
            _SCREAMING_SNAKE_CASE				:		Tuple  			=							hidden_size
            _SCREAMING_SNAKE_CASE				:		List[Any]  			=							num_hidden_layers
            _SCREAMING_SNAKE_CASE				:		List[Any]  			=							num_attention_heads
            _SCREAMING_SNAKE_CASE				:		int  			=							hidden_act
            _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							intermediate_size
            _SCREAMING_SNAKE_CASE				:		Any  			=							hidden_dropout_prob
            _SCREAMING_SNAKE_CASE				:		int  			=							attention_probs_dropout_prob
            _SCREAMING_SNAKE_CASE				:		List[Any]  			=							max_position_embeddings
            _SCREAMING_SNAKE_CASE				:		Dict  			=							type_vocab_size
            _SCREAMING_SNAKE_CASE				:		List[Any]  			=							task_type_vocab_size
            _SCREAMING_SNAKE_CASE				:		Any  			=							use_task_id
            _SCREAMING_SNAKE_CASE				:		Any  			=							initializer_range
            _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							layer_norm_eps
            _SCREAMING_SNAKE_CASE				:		Any  			=							position_embedding_type
            _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							use_cache
            _SCREAMING_SNAKE_CASE				:		Any  			=							classifier_dropout





class 	lowerCAmelCase__(       __lowercase			):






       '''simple docstring'''


       @property
       def 			UpperCamelCase_	(					self							)	->   Mapping[str, Mapping[int, str]]:
            if self.task == "multiple-choice":
                 _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							{0: "batch", 1: "choice", 2: "sequence"}
            else:
                 _SCREAMING_SNAKE_CASE				:		Any  			=							{0: "batch", 1: "sequence"}
            return OrderedDict(
                [
                    ("input_ids", dynamic_axis),
                    ("attention_mask", dynamic_axis),
                    ("token_type_ids", dynamic_axis),
                    ("task_type_ids", dynamic_axis),
                ]							)






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 	lowerCAmelCase__(       __lowercase			):






       '''simple docstring'''


       def 			UpperCamelCase_	(					self			,  __lowerCamelCase			,  __lowerCamelCase=False							)	->   List[Any]:
            _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							(
                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(__lowerCamelCase							)			,  "wb"							).close()
            _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							pa.Table.from_pydict({"filename": [Path(__lowerCamelCase							).name] * 1_0_0}							)
            if take == -1:
                 _SCREAMING_SNAKE_CASE				:		int  			=							len(__lowerCamelCase							) - skip
            if skip is not None and take is not None:
                 _SCREAMING_SNAKE_CASE				:		List[str]  			=							pa_table.slice(__lowerCamelCase			,  __lowerCamelCase							)
            return pa_table





class 	lowerCAmelCase__(       __lowercase			):






       '''simple docstring'''


       def 			UpperCamelCase_	(					self							)	->   List[Any]:
            _SCREAMING_SNAKE_CASE				:		Tuple  			=							"my_name"
            _SCREAMING_SNAKE_CASE				:		List[str]  			=							SplitInfo(name="train"			,  num_examples=1_0_0							)
            _SCREAMING_SNAKE_CASE				:		Tuple  			=							SplitInfo(name="test"			,  num_examples=1_0_0							)
            _SCREAMING_SNAKE_CASE				:		List[Any]  			=							[train_info, test_info]
            _SCREAMING_SNAKE_CASE				:		str  			=							SplitDict()
            split_dict.add(__lowerCamelCase							)
            split_dict.add(__lowerCamelCase							)
            _SCREAMING_SNAKE_CASE				:		str  			=							DatasetInfo(splits=__lowerCamelCase							)

            with tempfile.TemporaryDirectory() as tmp_dir:
                 _SCREAMING_SNAKE_CASE				:		Tuple  			=							ReaderTest(__lowerCamelCase			,  __lowerCamelCase							)

                 _SCREAMING_SNAKE_CASE				:		Dict  			=							"test[:33%]"
                 _SCREAMING_SNAKE_CASE				:		Tuple  			=							Dataset(**reader.read(__lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase							)							)
                 self.assertEqual(dset["filename"][0]			,  F"""{name}-test"""							)
                 self.assertEqual(dset.num_rows			,  3_3							)
                 self.assertEqual(dset.num_columns			,  1							)

                 _SCREAMING_SNAKE_CASE				:		List[str]  			=							["train", "test[:33%]"]
                 _SCREAMING_SNAKE_CASE				:		Tuple  			=							[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"							)]
                 for instructions in [instructionsa, instructionsa]:
                      _SCREAMING_SNAKE_CASE				:		List[Any]  			=							[reader.read(__lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase							) for instr in instructions]
                      _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE				:		Any  			=							(Dataset(**__lowerCamelCase							) 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			,  __lowerCamelCase							)
                      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			,  __lowerCamelCase							)
                      self.assertEqual(str(test_dset.split							)			,  "test[:33%]"							)
                      del train_dset, test_dset




       def 			UpperCamelCase_	(					self							)	->   int:
            _SCREAMING_SNAKE_CASE				:		List[str]  			=							"my_name"
            _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							SplitInfo(name="train"			,  num_examples=1_0_0_0			,  shard_lengths=[1_0_0] * 1_0							)
            _SCREAMING_SNAKE_CASE				:		str  			=							[train_info]
            _SCREAMING_SNAKE_CASE				:		Dict  			=							SplitDict()
            split_dict.add(__lowerCamelCase							)
            _SCREAMING_SNAKE_CASE				:		Tuple  			=							DatasetInfo(splits=__lowerCamelCase							)

            with tempfile.TemporaryDirectory() as tmp_dir:
                 _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							ReaderTest(__lowerCamelCase			,  __lowerCamelCase							)

                 _SCREAMING_SNAKE_CASE				:		int  			=							"train[:33%]"
                 _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							Dataset(**reader.read(__lowerCamelCase			,  __lowerCamelCase			,  __lowerCamelCase							)							)
                 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 			UpperCamelCase_	(					self							)	->   str:
            _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							SplitInfo(name="train"			,  num_examples=1_0_0							)
            _SCREAMING_SNAKE_CASE				:		Dict  			=							SplitInfo(name="test"			,  num_examples=1_0_0							)
            _SCREAMING_SNAKE_CASE				:		Tuple  			=							SplitDict()
            split_dict.add(__lowerCamelCase							)
            split_dict.add(__lowerCamelCase							)
            _SCREAMING_SNAKE_CASE				:		Any  			=							DatasetInfo(splits=__lowerCamelCase							)

            with tempfile.TemporaryDirectory() as tmp_dir:
                 _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							ReaderTest(__lowerCamelCase			,  __lowerCamelCase							)

                 _SCREAMING_SNAKE_CASE				:		List[Any]  			=							[
                     {"filename": os.path.join(__lowerCamelCase			,  "train"							)},
                     {"filename": os.path.join(__lowerCamelCase			,  "test"							), "skip": 1_0, "take": 1_0},
                 ]
                 _SCREAMING_SNAKE_CASE				:		Any  			=							Dataset(**reader.read_files(__lowerCamelCase			,  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__	(__lowerCamelCase,				__lowerCamelCase,				__lowerCamelCase		):
     _SCREAMING_SNAKE_CASE				:		Dict  			=							arrow_file
     with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
          _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							ArrowReader.read_table(__lowerCamelCase,				in_memory=__lowerCamelCase		)
     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__	(__lowerCamelCase,				__lowerCamelCase,				__lowerCamelCase		):
     _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							arrow_file
     _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							ArrowReader("",				__lowerCamelCase		)
     with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
          _SCREAMING_SNAKE_CASE				:		Dict  			=							reader.read_files([{"filename": filename}],				in_memory=__lowerCamelCase		)
     assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
     _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							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__	():
     assert ReadInstruction("train",				to=10,				unit="abs"		).to_spec() == "train[:10]"
     assert ReadInstruction("train",				from_=-80,				to=10,				unit="%"		).to_spec() == "train[-80%:10%]"

     _SCREAMING_SNAKE_CASE				:		str  			=							"train+test"
     assert ReadInstruction.from_spec(__lowerCamelCase		).to_spec() == spec_train_test

     _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							"train[2:10]"
     assert ReadInstruction.from_spec(__lowerCamelCase		).to_spec() == spec_train_abs

     _SCREAMING_SNAKE_CASE				:		List[Any]  			=							"train[15%:-20%]"
     assert ReadInstruction.from_spec(__lowerCamelCase		).to_spec() == spec_train_pct

     _SCREAMING_SNAKE_CASE				:		List[str]  			=							"train[:10%](closest)"
     assert ReadInstruction.from_spec(__lowerCamelCase		).to_spec() == "train[:10%]"

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

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






def 			lowerCamelCase__	():
     _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							"dummy"
     _SCREAMING_SNAKE_CASE				:		List[str]  			=							[SplitInfo(name="train",				num_examples=100		)]
     _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							"train[:33%]"
     _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							"arrow"
     _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							"prefix"

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

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






@pytest.mark.parametrize("name, expected_exception",				[(None, TypeError), ("", ValueError)]		)
def 			lowerCamelCase__	(__lowerCamelCase,				__lowerCamelCase		):
     _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							[SplitInfo(name="train",				num_examples=100		)]
     _SCREAMING_SNAKE_CASE				:		int  			=							"train"
     _SCREAMING_SNAKE_CASE				:		int  			=							"arrow"
     _SCREAMING_SNAKE_CASE				:		Tuple  			=							"prefix_path"
     with pytest.raises(__lowerCamelCase		):
          _SCREAMING_SNAKE_CASE				:		List[str]  			=							make_file_instructions(__lowerCamelCase,				__lowerCamelCase,				__lowerCamelCase,				__lowerCamelCase,				__lowerCamelCase		)