





import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from requests.exceptions import HTTPError

from transformers.utils import (
    CONFIG_NAME,
    FLAX_WEIGHTS_NAME,
    TF2_WEIGHTS_NAME,
    TRANSFORMERS_CACHE,
    WEIGHTS_NAME,
    cached_file,
    get_file_from_repo,
    has_file,
)


__A									=				"hf-internal-testing/tiny-random-bert"
__A									=				os.path.join(TRANSFORMERS_CACHE, "models--hf-internal-testing--tiny-random-bert")
__A									=				"9b8c223d42b2188cb49d29af482996f9d0f3e5a6"



class    _SCREAMING_SNAKE_CASE						(	unittest.TestCase    ):







 '''simple docstring'''

 def 							SCREAMING_SNAKE_CASE_					(self				:   List[str])       ->List[Any]:



   '''simple docstring'''



   lowerCamelCase__:      Any			  =cached_file(UpperCAmelCase_       , UpperCAmelCase_)
   # Should have downloaded the file in here
   self.assertTrue(os.path.isdir(UpperCAmelCase_))
   # Cache should contain at least those three subfolders:
   for subfolder in ["blobs", "refs", "snapshots"]:
     self.assertTrue(os.path.isdir(os.path.join(UpperCAmelCase_       , UpperCAmelCase_)))
   with open(os.path.join(UpperCAmelCase_       , "refs"       , "main")) as f:
     lowerCamelCase__:      List[Any]			  =f.read()
   self.assertEqual(UpperCAmelCase_       , os.path.join(UpperCAmelCase_       , "snapshots"       , UpperCAmelCase_       , UpperCAmelCase_))
   self.assertTrue(os.path.isfile(UpperCAmelCase_))

   # File is cached at the same place the second time.
   lowerCamelCase__:      Optional[Any]			  =cached_file(UpperCAmelCase_       , UpperCAmelCase_)
   self.assertEqual(UpperCAmelCase_       , UpperCAmelCase_)

   # Using a specific revision to test the full commit hash.
   lowerCamelCase__:      str			  =cached_file(UpperCAmelCase_       , UpperCAmelCase_       , revision="9b8c223")
   self.assertEqual(UpperCAmelCase_       , os.path.join(UpperCAmelCase_       , "snapshots"       , UpperCAmelCase_       , UpperCAmelCase_))

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



   '''simple docstring'''



   with self.assertRaisesRegex(UpperCAmelCase_       , "is not a valid model identifier"):
     lowerCamelCase__:      List[Any]			  =cached_file("tiny-random-bert"       , UpperCAmelCase_)

   with self.assertRaisesRegex(UpperCAmelCase_       , "is not a valid git identifier"):
     lowerCamelCase__:      List[str]			  =cached_file(UpperCAmelCase_       , UpperCAmelCase_       , revision="aaaa")

   with self.assertRaisesRegex(UpperCAmelCase_       , "does not appear to have a file named"):
     lowerCamelCase__:      Optional[Any]			  =cached_file(UpperCAmelCase_       , "conf")

 def 							SCREAMING_SNAKE_CASE_					(self				:   Optional[Any])       ->List[str]:



   '''simple docstring'''



   with self.assertRaisesRegex(UpperCAmelCase_       , "does not appear to have a file named"):
     lowerCamelCase__:      Dict			  =cached_file(UpperCAmelCase_       , "conf")

   with open(os.path.join(UpperCAmelCase_       , "refs"       , "main")) as f:
     lowerCamelCase__:      List[str]			  =f.read()
   self.assertTrue(os.path.isfile(os.path.join(UpperCAmelCase_       , ".no_exist"       , UpperCAmelCase_       , "conf")))

   lowerCamelCase__:      Union[str, Any]			  =cached_file(UpperCAmelCase_       , "conf"       , _raise_exceptions_for_missing_entries=UpperCAmelCase_)
   self.assertIsNone(UpperCAmelCase_)

   lowerCamelCase__:      Union[str, Any]			  =cached_file(UpperCAmelCase_       , "conf"       , local_files_only=UpperCAmelCase_       , _raise_exceptions_for_missing_entries=UpperCAmelCase_)
   self.assertIsNone(UpperCAmelCase_)

   lowerCamelCase__:      List[Any]			  =mock.Mock()
   lowerCamelCase__:      int			  =500
   lowerCamelCase__:      Union[str, Any]			  ={}
   lowerCamelCase__:      Any			  =HTTPError
   lowerCamelCase__:      List[Any]			  ={}

   # Under the mock environment we get a 500 error when trying to reach the tokenizer.
   with mock.patch("requests.Session.request"       , return_value=UpperCAmelCase_) as mock_head:
     lowerCamelCase__:      int			  =cached_file(UpperCAmelCase_       , "conf"       , _raise_exceptions_for_connection_errors=UpperCAmelCase_)
     self.assertIsNone(UpperCAmelCase_)
     # This check we did call the fake head request
     mock_head.assert_called()

 def 							SCREAMING_SNAKE_CASE_					(self				:   Optional[Any])       ->Tuple:



   '''simple docstring'''



   self.assertTrue(has_file("hf-internal-testing/tiny-bert-pt-only"       , UpperCAmelCase_))
   self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only"       , UpperCAmelCase_))
   self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only"       , UpperCAmelCase_))

 def 							SCREAMING_SNAKE_CASE_					(self				:   Dict)       ->List[str]:



   '''simple docstring'''



   self.assertIsNone(get_file_from_repo("bert-base-cased"       , "ahah.txt"))

   # The function raises if the repository does not exist.
   with self.assertRaisesRegex(UpperCAmelCase_       , "is not a valid model identifier"):
     get_file_from_repo("bert-base-case"       , UpperCAmelCase_)

   # The function raises if the revision does not exist.
   with self.assertRaisesRegex(UpperCAmelCase_       , "is not a valid git identifier"):
     get_file_from_repo("bert-base-cased"       , UpperCAmelCase_       , revision="ahaha")

   lowerCamelCase__:      List[str]			  =get_file_from_repo("bert-base-cased"       , UpperCAmelCase_)
   # The name is the cached name which is not very easy to test, so instead we load the content.
   lowerCamelCase__:      List[str]			  =json.loads(open(UpperCAmelCase_       , "r").read())
   self.assertEqual(config["hidden_size"]       , 768)







 def 							SCREAMING_SNAKE_CASE_					(self				:   List[str])       ->int:



   '''simple docstring'''



   with tempfile.TemporaryDirectory() as tmp_dir:
     lowerCamelCase__:      List[Any]			  =Path(UpperCAmelCase_) / "a.txt"
     filename.touch()
     self.assertEqual(get_file_from_repo(UpperCAmelCase_       , "a.txt")       , str(UpperCAmelCase_))

     self.assertIsNone(get_file_from_repo(UpperCAmelCase_       , "b.txt"))




"""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


_a       =							datasets.utils.logging.get_logger(__name__)

_a       =							['names', 'prefix']
_a       =							['warn_bad_lines', 'error_bad_lines', 'mangle_dupe_cols']
_a       =							['encoding_errors', 'on_bad_lines']
_a       =							['date_format']




@dataclass
class 					_lowerCAmelCase  (	datasets.BuilderConfig   ):







 """simple docstring"""







 __UpperCAmelCase	:					str   		=	","
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					Optional[Union[int, List[int], str]]   		=	"infer"
 __UpperCAmelCase	:					Optional[List[str]]   		=	None
 __UpperCAmelCase	:					Optional[List[str]]   		=	None
 __UpperCAmelCase	:					Optional[Union[int, str, List[int], List[str]]]   		=	None
 __UpperCAmelCase	:					Optional[Union[List[int], List[str]]]   		=	None
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					bool   		=	True
 __UpperCAmelCase	:					Optional[Literal["c", "python", "pyarrow"]]   		=	None
 __UpperCAmelCase	:					Dict[Union[int, str], Callable[[Any], Any]]   		=	None
 __UpperCAmelCase	:					Optional[list]   		=	None
 __UpperCAmelCase	:					Optional[list]   		=	None
 __UpperCAmelCase	:					bool   		=	False
 __UpperCAmelCase	:					Optional[Union[int, List[int]]]   		=	None
 __UpperCAmelCase	:					Optional[int]   		=	None
 __UpperCAmelCase	:					Optional[Union[str, List[str]]]   		=	None
 __UpperCAmelCase	:					bool   		=	True
 __UpperCAmelCase	:					bool   		=	True
 __UpperCAmelCase	:					bool   		=	False
 __UpperCAmelCase	:					bool   		=	True
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					str   		=	"."
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					str   		=	'"'
 __UpperCAmelCase	:					int   		=	0
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					bool   		=	True
 __UpperCAmelCase	:					bool   		=	True
 __UpperCAmelCase	:					int   		=	0
 __UpperCAmelCase	:					bool   		=	True
 __UpperCAmelCase	:					bool   		=	False
 __UpperCAmelCase	:					Optional[str]   		=	None
 __UpperCAmelCase	:					int   		=	1_0_0_0_0
 __UpperCAmelCase	:					Optional[datasets.Features]   		=	None
 __UpperCAmelCase	:					Optional[str]   		=	"strict"
 __UpperCAmelCase	:					Literal["error", "warn", "skip"]   		=	"error"
 __UpperCAmelCase	:					Optional[str]   		=	None


 def 					_lowercase (			self							:			Tuple	):
    if self.delimiter is not None:
       __lowercase								=						self.delimiter
    if self.column_names is not None:
       __lowercase								=						self.column_names



 @property
 def 					_lowercase (			self							:			Union[str, Any]	):
    __lowercase								=						{
        "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(),					UpperCAmelCase__	):
          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 					_lowerCAmelCase  (	datasets.ArrowBasedBuilder   ):







 """simple docstring"""







 __UpperCAmelCase	:					Tuple   		=	CsvConfig


 def 					_lowercase (			self							:			List[str]	):
    return datasets.DatasetInfo(features=self.config.features	)


 def 					_lowercase (			self							:			List[Any],					UpperCAmelCase__							:			Dict	):
    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}"""	)
    __lowercase								=						dl_manager.download_and_extract(self.config.data_files	)
    if isinstance(UpperCAmelCase__,					(str, list, tuple)	):
       __lowercase								=						data_files
       if isinstance(UpperCAmelCase__,					UpperCAmelCase__	):
          __lowercase								=						[files]
       __lowercase								=						[dl_manager.iter_files(UpperCAmelCase__	) for file in files]
       return [datasets.SplitGenerator(name=datasets.Split.TRAIN,					gen_kwargs={"files": files}	)]
    __lowercase								=						[]
    for split_name, files in data_files.items():
       if isinstance(UpperCAmelCase__,					UpperCAmelCase__	):
          __lowercase								=						[files]
       __lowercase								=						[dl_manager.iter_files(UpperCAmelCase__	) for file in files]
       splits.append(datasets.SplitGenerator(name=UpperCAmelCase__,					gen_kwargs={"files": files}	)	)
    return splits


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



 def 					_lowercase (			self							:			Optional[Any],					UpperCAmelCase__							:			List[str]	):
    __lowercase								=						self.config.features.arrow_schema if self.config.features else None
    # dtype allows reading an int column as str
    __lowercase								=						(
        {
            name: dtype.to_pandas_dtype() if not require_storage_cast(UpperCAmelCase__	) 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(UpperCAmelCase__	)	):
       __lowercase								=						pd.read_csv(UpperCAmelCase__,					iterator=UpperCAmelCase__,					dtype=UpperCAmelCase__,					**self.config.pd_read_csv_kwargs	)
       try:
          for batch_idx, df in enumerate(UpperCAmelCase__	):
             __lowercase								=						pa.Table.from_pandas(UpperCAmelCase__	)
             # 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(UpperCAmelCase__	)
       except ValueError as e:
          logger.error(F"""Failed to read file '{file}' with error {type(UpperCAmelCase__	)}: {e}"""	)
          raise




