






'''simple docstring'''







import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


UpperCamelCase     :   int	      =		datasets.utils.logging.get_logger(__name__)

UpperCamelCase     :   List[str]	      =		['names', 'prefix']
UpperCamelCase     :   List[str]	      =		['warn_bad_lines', 'error_bad_lines', 'mangle_dupe_cols']
UpperCamelCase     :   Optional[int]	      =		['encoding_errors', 'on_bad_lines']
UpperCamelCase     :   Optional[int]	      =		['date_format']




@dataclass
class 		UpperCamelCase__     (datasets.BuilderConfig      ):




		'''simple docstring'''





		_UpperCamelCase						=       ","
		_UpperCamelCase						=       None
		_UpperCamelCase						=       "infer"
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       True
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       False
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       True
		_UpperCamelCase						=       True
		_UpperCamelCase						=       False
		_UpperCamelCase						=       True
		_UpperCamelCase						=       None
		_UpperCamelCase						=       "."
		_UpperCamelCase						=       None
		_UpperCamelCase						=       '"'
		_UpperCamelCase						=       0
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       None
		_UpperCamelCase						=       True
		_UpperCamelCase						=       True
		_UpperCamelCase						=       0
		_UpperCamelCase						=       True
		_UpperCamelCase						=       False
		_UpperCamelCase						=       None
		_UpperCamelCase						=       10000
		_UpperCamelCase						=       None
		_UpperCamelCase						=       "strict"
		_UpperCamelCase						=       "error"
		_UpperCamelCase						=       None






		def       UpperCamelCase_       (   self							):
								if self.delimiter is not None:
														lowerCamelCase__								=	self.delimiter
								if self.column_names is not None:
														lowerCamelCase__								=	self.column_names






		@property
		def       UpperCamelCase_       (   self							):
								lowerCamelCase__								=	{
								    """sep""": self.sep,
								    """header""": self.header,
								    """names""": self.names,
								    """index_col""": self.index_col,
								    """usecols""": self.usecols,
								    """prefix""": self.prefix,
								    """mangle_dupe_cols""": self.mangle_dupe_cols,
								    """engine""": self.engine,
								    """converters""": self.converters,
								    """true_values""": self.true_values,
								    """false_values""": self.false_values,
								    """skipinitialspace""": self.skipinitialspace,
								    """skiprows""": self.skiprows,
								    """nrows""": self.nrows,
								    """na_values""": self.na_values,
								    """keep_default_na""": self.keep_default_na,
								    """na_filter""": self.na_filter,
								    """verbose""": self.verbose,
								    """skip_blank_lines""": self.skip_blank_lines,
								    """thousands""": self.thousands,
								    """decimal""": self.decimal,
								    """lineterminator""": self.lineterminator,
								    """quotechar""": self.quotechar,
								    """quoting""": self.quoting,
								    """escapechar""": self.escapechar,
								    """comment""": self.comment,
								    """encoding""": self.encoding,
								    """dialect""": self.dialect,
								    """error_bad_lines""": self.error_bad_lines,
								    """warn_bad_lines""": self.warn_bad_lines,
								    """skipfooter""": self.skipfooter,
								    """doublequote""": self.doublequote,
								    """memory_map""": self.memory_map,
								    """float_precision""": self.float_precision,
								    """chunksize""": self.chunksize,
								    """encoding_errors""": self.encoding_errors,
								    """on_bad_lines""": self.on_bad_lines,
								    """date_format""": self.date_format,
								}

								# some kwargs must not be passed if they don't have a default value
								# some others are deprecated and we can also not pass them if they are the default value
								for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
														if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig() ,_lowerCAmelCase							):
																				del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
								if not (datasets.config.PANDAS_VERSION.major >= 2):
														for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
																				del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
								if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
														for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
																				del pd_read_csv_kwargs[pd_read_csv_parameter]

								return pd_read_csv_kwargs




class 		UpperCamelCase__     (datasets.ArrowBasedBuilder      ):




		'''simple docstring'''





		_UpperCamelCase						=       CsvConfig






		def       UpperCamelCase_       (   self							):
								return datasets.DatasetInfo(features=self.config.features							)






		def       UpperCamelCase_       (   self ,_lowerCAmelCase							):
								if not self.config.data_files:
														raise ValueError(F'''At least one data file must be specified, but got data_files={self.config.data_files}'''							)
								lowerCamelCase__								=	dl_manager.download_and_extract(self.config.data_files							)
								if isinstance(_lowerCAmelCase ,(str, list, tuple)							):
														lowerCamelCase__								=	data_files
														if isinstance(_lowerCAmelCase ,_lowerCAmelCase							):
																				lowerCamelCase__								=	[files]
														lowerCamelCase__								=	[dl_manager.iter_files(_lowerCAmelCase							) for file in files]
														return [datasets.SplitGenerator(name=datasets.Split.TRAIN ,gen_kwargs={"""files""": files}							)]
								lowerCamelCase__								=	[]
								for split_name, files in data_files.items():
														if isinstance(_lowerCAmelCase ,_lowerCAmelCase							):
																				lowerCamelCase__								=	[files]
														lowerCamelCase__								=	[dl_manager.iter_files(_lowerCAmelCase							) for file in files]
														splits.append(datasets.SplitGenerator(name=_lowerCAmelCase ,gen_kwargs={"""files""": files}							)							)
								return splits






		def       UpperCamelCase_       (   self ,_lowerCAmelCase							):
								if self.config.features is not None:
														lowerCamelCase__								=	self.config.features.arrow_schema
														if all(not require_storage_cast(_lowerCAmelCase							) for feature in self.config.features.values()							):
																				# cheaper cast
																				lowerCamelCase__								=	pa.Table.from_arrays([pa_table[field.name] for field in schema] ,schema=_lowerCAmelCase							)
														else:
																				# more expensive cast; allows str <-> int/float or str to Audio for example
																				lowerCamelCase__								=	table_cast(_lowerCAmelCase ,_lowerCAmelCase							)
								return pa_table






		def       UpperCamelCase_       (   self ,_lowerCAmelCase							):
								lowerCamelCase__								=	self.config.features.arrow_schema if self.config.features else None
								# dtype allows reading an int column as str
								lowerCamelCase__								=	(
								    {
								        name: dtype.to_pandas_dtype() if not require_storage_cast(_lowerCAmelCase							) else object
								        for name, dtype, feature in zip(schema.names ,schema.types ,self.config.features.values()							)
								    }
								    if schema is not None
								    else None
								)
								for file_idx, file in enumerate(itertools.chain.from_iterable(_lowerCAmelCase							)							):
														lowerCamelCase__								=	pd.read_csv(_lowerCAmelCase ,iterator=_lowerCAmelCase ,dtype=_lowerCAmelCase ,**self.config.pd_read_csv_kwargs							)
														try:
																				for batch_idx, df in enumerate(_lowerCAmelCase							):
																										lowerCamelCase__								=	pa.Table.from_pandas(_lowerCAmelCase							)
																										# Uncomment for debugging (will print the Arrow table size and elements)
																										# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
																										# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																										yield (file_idx, batch_idx), self._cast_table(_lowerCAmelCase							)
														except ValueError as e:
																				logger.error(F'''Failed to read file \'{file}\' with error {type(_lowerCAmelCase							)}: {e}'''							)
																				raise



# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase__     :		Tuple        = {
    """configuration_mgp_str""": ["""MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MgpstrConfig"""],
    """processing_mgp_str""": ["""MgpstrProcessor"""],
    """tokenization_mgp_str""": ["""MgpstrTokenizer"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__     :		Optional[int]        = [
         """MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """MgpstrModel""",
         """MgpstrPreTrainedModel""",
         """MgpstrForSceneTextRecognition""",
     ]

if TYPE_CHECKING:
     from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
     from .processing_mgp_str import MgpstrProcessor
     from .tokenization_mgp_str import MgpstrTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_mgp_str import (
              MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
              MgpstrForSceneTextRecognition,
              MgpstrModel,
              MgpstrPreTrainedModel,
          )
else:
     import sys

     lowerCamelCase__     :		List[Any]        = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






