


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   :    Optional[int]     =		datasets.utils.logging.get_logger(__name__)

UpperCAmelCase   :    Optional[int]     =		["""names""", """prefix"""]
UpperCAmelCase   :    List[Any]     =		["""warn_bad_lines""", """error_bad_lines""", """mangle_dupe_cols"""]
UpperCAmelCase   :    str     =		["""encoding_errors""", """on_bad_lines"""]
UpperCAmelCase   :    Tuple     =		["""date_format"""]







@dataclass
class        __lowercase       (							datasets.BuilderConfig  ):



		"""simple docstring"""

		UpperCamelCase     :					Dict			       =		","
		UpperCamelCase     :					Optional[Any]			       =		None
		UpperCamelCase     :					Tuple			       =		"infer"
		UpperCamelCase     :					List[str]			       =		None
		UpperCamelCase     :					Dict			       =		None
		UpperCamelCase     :					Optional[Any]			       =		None
		UpperCamelCase     :					Optional[int]			       =		None
		UpperCamelCase     :					int			       =		None
		UpperCamelCase     :					str			       =		True
		UpperCamelCase     :					List[Any]			       =		None
		UpperCamelCase     :					Tuple			       =		None
		UpperCamelCase     :					List[Any]			       =		None
		UpperCamelCase     :					Optional[int]			       =		None
		UpperCamelCase     :					int			       =		False
		UpperCamelCase     :					List[str]			       =		None
		UpperCamelCase     :					Union[str, Any]			       =		None
		UpperCamelCase     :					Tuple			       =		None
		UpperCamelCase     :					int			       =		True
		UpperCamelCase     :					Union[str, Any]			       =		True
		UpperCamelCase     :					Tuple			       =		False
		UpperCamelCase     :					Dict			       =		True
		UpperCamelCase     :					Dict			       =		None
		UpperCamelCase     :					Any			       =		"."
		UpperCamelCase     :					Tuple			       =		None
		UpperCamelCase     :					int			       =		"\""
		UpperCamelCase     :					Any			       =		0
		UpperCamelCase     :					Optional[Any]			       =		None
		UpperCamelCase     :					Optional[Any]			       =		None
		UpperCamelCase     :					List[Any]			       =		None
		UpperCamelCase     :					Optional[Any]			       =		None
		UpperCamelCase     :					List[Any]			       =		True
		UpperCamelCase     :					Tuple			       =		True
		UpperCamelCase     :					Optional[int]			       =		0
		UpperCamelCase     :					List[Any]			       =		True
		UpperCamelCase     :					Optional[int]			       =		False
		UpperCamelCase     :					List[Any]			       =		None
		UpperCamelCase     :					List[str]			       =		1_0_0_0_0
		UpperCamelCase     :					List[Any]			       =		None
		UpperCamelCase     :					int			       =		"strict"
		UpperCamelCase     :					Any			       =		"error"
		UpperCamelCase     :					Optional[Any]			       =		None







		def 					__A   ( self	)  -> str:







					'''simple docstring'''







					if self.delimiter is not None:
								lowerCamelCase    		=  self.delimiter
					if self.column_names is not None:
								lowerCamelCase    		=  self.column_names







		@property
		def 					__A   ( self	)  -> str:







					'''simple docstring'''







					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()		,      a_	):
											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        __lowercase       (							datasets.ArrowBasedBuilder  ):



		"""simple docstring"""

		UpperCamelCase     :					Optional[int]			       =		CsvConfig







		def 					__A   ( self	)  -> Union[str, Any]:







					'''simple docstring'''







					return datasets.DatasetInfo(features=self.config.features	)







		def 					__A   ( self		,      A	)  -> Any:







					'''simple docstring'''







					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(a_		,      (str, list, tuple)	):
								lowerCamelCase    		=  data_files
								if isinstance(a_		,      a_	):
											lowerCamelCase    		=  [files]
								lowerCamelCase    		=  [dl_manager.iter_files(a_	) 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(a_		,      a_	):
											lowerCamelCase    		=  [files]
								lowerCamelCase    		=  [dl_manager.iter_files(a_	) for file in files]
								splits.append(datasets.SplitGenerator(name=a_		,      gen_kwargs={"""files""": files}	)	)
					return splits







		def 					__A   ( self		,      A	)  -> pa.Table:







					'''simple docstring'''







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







		def 					__A   ( self		,      A	)  -> Union[str, Any]:







					'''simple docstring'''







					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(a_	) 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(a_	)	):
								lowerCamelCase    		=  pd.read_csv(a_		,      iterator=a_		,      dtype=a_		,      **self.config.pd_read_csv_kwargs	)
								try:
											for batch_idx, df in enumerate(a_	):
														lowerCamelCase    		=  pa.Table.from_pandas(a_	)
														# 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(a_	)
								except ValueError as e:
											logger.error(F'Failed to read file \'{file}\' with error {type(a_	)}: {e}'	)
											raise





'''simple docstring'''
import collections
import importlib.util
import os
import re
from pathlib import Path


lowerCAmelCase   : List[str]             =				"""src/transformers"""


# Matches is_xxx_available()
lowerCAmelCase   : List[str]             =				re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase   : str             =				re.compile(R"""^_import_structure\s+=\s+\{([^\}]+)\}""")
# Catches a line with a key-values pattern: "bla": ["foo", "bar"]
lowerCAmelCase   : Optional[int]             =				re.compile(R"""\s+\"\S*\":\s+\[([^\]]*)\]""")
# Catches a line if not is_foo_available
lowerCAmelCase   : Optional[int]             =				re.compile(R"""^\s*if\s+not\s+is\_[a-z_]*\_available\(\)""")
# Catches a line _import_struct["bla"].append("foo")
lowerCAmelCase   : str             =				re.compile(R"""^\s*_import_structure\[\"\S*\"\]\.append\(\"(\S*)\"\)""")
# Catches a line _import_struct["bla"].extend(["foo", "bar"]) or _import_struct["bla"] = ["foo", "bar"]
lowerCAmelCase   : List[Any]             =				re.compile(R"""^\s*_import_structure\[\S*\](?:\.extend\(|\s*=\s+)\[([^\]]*)\]""")
# Catches a line with an object between quotes and a comma:     "MyModel",
lowerCAmelCase   : Dict             =				re.compile("""^\s+\"([^\"]+)\",""")
# Catches a line with objects between brackets only:    ["foo", "bar"],
lowerCAmelCase   : Tuple             =				re.compile("""^\s+\[([^\]]+)\]""")
# Catches a line with from foo import bar, bla, boo
lowerCAmelCase   : Optional[int]             =				re.compile(R"""\s+from\s+\S*\s+import\s+([^\(\s].*)\n""")
# Catches a line with try:
lowerCAmelCase   : Optional[int]             =				re.compile(R"""^\s*try:""")
# Catches a line with else:
lowerCAmelCase   : Optional[int]             =				re.compile(R"""^\s*else:""")




def 	_A  (       A							)  ->				List[Any]:
	if _re_test_backend.search(A							) is None:
		return None
	lowercase						:		Union[str, Any]   					=		[b[0] for b in _re_backend.findall(A							)]
	backends.sort()
	return "_and_".join(A							)




def 	_A  (       A							)  ->				Optional[Any]:
	with open(A							,"r"							,encoding="utf-8"							,newline="\n"							) as f:
		lowercase						:		Tuple   					=		f.readlines()

	lowercase						:		List[str]   					=		0
	while line_index < len(A							) and not lines[line_index].startswith("_import_structure = {"							):
		line_index += 1

	# If this is a traditional init, just return.
	if line_index >= len(A							):
		return None

	# First grab the objects without a specific backend in _import_structure
	lowercase						:		Union[str, Any]   					=		[]
	while not lines[line_index].startswith("if TYPE_CHECKING"							) and find_backend(lines[line_index]							) is None:
		lowercase						:		Any   					=		lines[line_index]
		# If we have everything on a single line, let's deal with it.
		if _re_one_line_import_struct.search(A							):
			lowercase						:		int   					=		_re_one_line_import_struct.search(A							).groups()[0]
			lowercase						:		Union[str, Any]   					=		re.findall("\[([^\]]+)\]"							,A							)
			for imp in imports:
				objects.extend([obj[1:-1] for obj in imp.split(", "							)]							)
			line_index += 1
			continue
		lowercase						:		Optional[Any]   					=		_re_import_struct_key_value.search(A							)
		if single_line_import_search is not None:
			lowercase						:		List[Any]   					=		[obj[1:-1] for obj in single_line_import_search.groups()[0].split(", "							) if len(A							) > 0]
			objects.extend(A							)
		elif line.startswith(" " * 8 + "\""							):
			objects.append(line[9:-3]							)
		line_index += 1

	lowercase						:		Tuple   					=		{"none": objects}
	# Let's continue with backend-specific objects in _import_structure
	while not lines[line_index].startswith("if TYPE_CHECKING"							):
		# If the line is an if not is_backend_available, we grab all objects associated.
		lowercase						:		int   					=		find_backend(lines[line_index]							)
		# Check if the backend declaration is inside a try block:
		if _re_try.search(lines[line_index - 1]							) is None:
			lowercase						:		str   					=		None

		if backend is not None:
			line_index += 1

			# Scroll until we hit the else block of try-except-else
			while _re_else.search(lines[line_index]							) is None:
				line_index += 1

			line_index += 1

			lowercase						:		Any   					=		[]
			# Until we unindent, add backend objects to the list
			while len(lines[line_index]							) <= 1 or lines[line_index].startswith(" " * 4							):
				lowercase						:		List[Any]   					=		lines[line_index]
				if _re_import_struct_add_one.search(A							) is not None:
					objects.append(_re_import_struct_add_one.search(A							).groups()[0]							)
				elif _re_import_struct_add_many.search(A							) is not None:
					lowercase						:		Dict   					=		_re_import_struct_add_many.search(A							).groups()[0].split(", "							)
					lowercase						:		Any   					=		[obj[1:-1] for obj in imports if len(A							) > 0]
					objects.extend(A							)
				elif _re_between_brackets.search(A							) is not None:
					lowercase						:		Optional[Any]   					=		_re_between_brackets.search(A							).groups()[0].split(", "							)
					lowercase						:		Tuple   					=		[obj[1:-1] for obj in imports if len(A							) > 0]
					objects.extend(A							)
				elif _re_quote_object.search(A							) is not None:
					objects.append(_re_quote_object.search(A							).groups()[0]							)
				elif line.startswith(" " * 8 + "\""							):
					objects.append(line[9:-3]							)
				elif line.startswith(" " * 1_2 + "\""							):
					objects.append(line[1_3:-3]							)
				line_index += 1

			lowercase						:		Optional[int]   					=		objects
		else:
			line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
	lowercase						:		str   					=		[]
	while (
	    line_index < len(A							)
	    and find_backend(lines[line_index]							) is None
	    and not lines[line_index].startswith("else"							)
	):
		lowercase						:		int   					=		lines[line_index]
		lowercase						:		Any   					=		_re_import.search(A							)
		if single_line_import_search is not None:
			objects.extend(single_line_import_search.groups()[0].split(", "							)							)
		elif line.startswith(" " * 8							):
			objects.append(line[8:-2]							)
		line_index += 1

	lowercase						:		Optional[Any]   					=		{"none": objects}
	# Let's continue with backend-specific objects
	while line_index < len(A							):
		# If the line is an if is_backend_available, we grab all objects associated.
		lowercase						:		List[Any]   					=		find_backend(lines[line_index]							)
		# Check if the backend declaration is inside a try block:
		if _re_try.search(lines[line_index - 1]							) is None:
			lowercase						:		int   					=		None

		if backend is not None:
			line_index += 1

			# Scroll until we hit the else block of try-except-else
			while _re_else.search(lines[line_index]							) is None:
				line_index += 1

			line_index += 1

			lowercase						:		Optional[Any]   					=		[]
			# Until we unindent, add backend objects to the list
			while len(lines[line_index]							) <= 1 or lines[line_index].startswith(" " * 8							):
				lowercase						:		List[Any]   					=		lines[line_index]
				lowercase						:		Tuple   					=		_re_import.search(A							)
				if single_line_import_search is not None:
					objects.extend(single_line_import_search.groups()[0].split(", "							)							)
				elif line.startswith(" " * 1_2							):
					objects.append(line[1_2:-2]							)
				line_index += 1

			lowercase						:		Dict   					=		objects
		else:
			line_index += 1

	return import_dict_objects, type_hint_objects




def 	_A  (       A							,A							)  ->				List[str]:

	def find_duplicates(A							):
		return [k for k, v in collections.Counter(A							).items() if v > 1]

	if list(import_dict_objects.keys()							) != list(type_hint_objects.keys()							):
		return ["Both sides of the init do not have the same backends!"]

	lowercase						:		str   					=		[]
	for key in import_dict_objects.keys():
		lowercase						:		List[str]   					=		find_duplicates(import_dict_objects[key]							)
		if duplicate_imports:
			errors.append(F'''Duplicate _import_structure definitions for: {duplicate_imports}'''							)
		lowercase						:		List[Any]   					=		find_duplicates(type_hint_objects[key]							)
		if duplicate_type_hints:
			errors.append(F'''Duplicate TYPE_CHECKING objects for: {duplicate_type_hints}'''							)

		if sorted(set(import_dict_objects[key]							)							) != sorted(set(type_hint_objects[key]							)							):
			lowercase						:		Optional[int]   					=		"base imports" if key == "none" else F'''{key} backend'''
			errors.append(F'''Differences for {name}:'''							)
			for a in type_hint_objects[key]:
				if a not in import_dict_objects[key]:
					errors.append(F'''  {a} in TYPE_HINT but not in _import_structure.'''							)
			for a in import_dict_objects[key]:
				if a not in type_hint_objects[key]:
					errors.append(F'''  {a} in _import_structure but not in TYPE_HINT.'''							)
	return errors




def 	_A  (       )  ->				List[Any]:
	lowercase						:		Any   					=		[]
	for root, _, files in os.walk(A							):
		if "__init__.py" in files:
			lowercase						:		Optional[Any]   					=		os.path.join(A							,"__init__.py"							)
			lowercase						:		Tuple   					=		parse_init(A							)
			if objects is not None:
				lowercase						:		Tuple   					=		analyze_results(*A							)
				if len(A							) > 0:
					lowercase						:		Tuple   					=		F'''Problem in {fname}, both halves do not define the same objects.\n{errors[0]}'''
					failures.append("\n".join(A							)							)
	if len(A							) > 0:
		raise ValueError("\n\n".join(A							)							)




def 	_A  (       )  ->				Union[str, Any]:
	lowercase						:		Dict   					=		[]
	for path, directories, files in os.walk(A							):
		for folder in directories:
			# Ignore private modules
			if folder.startswith("_"							):
				directories.remove(A							)
				continue
			# Ignore leftovers from branches (empty folders apart from pycache)
			if len(list((Path(A							) / folder).glob("*.py"							)							)							) == 0:
				continue
			lowercase						:		str   					=		str((Path(A							) / folder).relative_to(A							)							)
			lowercase						:		Optional[Any]   					=		short_path.replace(os.path.sep							,"."							)
			submodules.append(A							)
		for fname in files:
			if fname == "__init__.py":
				continue
			lowercase						:		Tuple   					=		str((Path(A							) / fname).relative_to(A							)							)
			lowercase						:		int   					=		short_path.replace(".py"							,""							).replace(os.path.sep							,"."							)
			if len(submodule.split("."							)							) == 1:
				submodules.append(A							)
	return submodules


lowerCAmelCase   : Dict             =				[
    """convert_pytorch_checkpoint_to_tf2""",
    """modeling_flax_pytorch_utils""",
]




def 	_A  (       )  ->				Optional[int]:
	# This is to make sure the transformers module imported is the one in the repo.
	lowercase						:		int   					=		importlib.util.spec_from_file_location(
	    "transformers"							,os.path.join(A							,"__init__.py"							)							,submodule_search_locations=[PATH_TO_TRANSFORMERS]							,)
	lowercase						:		Optional[int]   					=		spec.loader.load_module()

	lowercase						:		Dict   					=		[
	    module
	    for module in get_transformers_submodules()
	    if module not in IGNORE_SUBMODULES and module not in transformers._import_structure.keys()
	]
	if len(A							) > 0:
		lowercase						:		Optional[int]   					=		"\n".join(F'''- {module}''' for module in module_not_registered							)
		raise ValueError(
		    "The following submodules are not properly registered in the main init of Transformers:\n"
		    F'''{list_of_modules}\n'''
		    "Make sure they appear somewhere in the keys of `_import_structure` with an empty list as value."							)


if __name__ == "__main__":
					check_all_inits()
					check_submodules()


