


import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
__UpperCamelCase    		=       object()

# For specifying empty leaf dict `{}`
__UpperCamelCase    		=       object()
def        UpperCamelCase_(				_A   :Any				,     _A   :Union[str, Any]  )->		Tuple:
			UpperCamelCase__					=       tuple((re.compile(x + "$"  ) for x in qs)  )
			for i in range(len(_A  ) - len(_A  ) + 1  ):
						UpperCamelCase__					=       [x.match(_A  ) for x, y in zip(_A				,     ks[i:]  )]
						if matches and all(_A  ):
									return True
			return False
def        UpperCamelCase_(				_A   :Optional[Any]  )->		str:
			def replace(_A   :str				,     _A   :Dict  ):
						for rule, replacement in rules:
									if _match(_A				,     _A  ):
												return replacement
						return val

			return replace
def        UpperCamelCase_(				)->		List[Any]:
			return [
			    # embeddings
			    (("transformer", "wpe", "embedding"), P("mp"				,     _A  )),
			    (("transformer", "wte", "embedding"), P("mp"				,     _A  )),
			    # atention
			    (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(_A				,     "mp"  )),
			    (("attention", "out_proj", "kernel"), P("mp"				,     _A  )),
			    (("attention", "out_proj", "bias"), None),
			    # mlp
			    (("mlp", "c_fc", "kernel"), P(_A				,     "mp"  )),
			    (("mlp", "c_fc", "bias"), P("mp"  )),
			    (("mlp", "c_proj", "kernel"), P("mp"				,     _A  )),
			    (("mlp", "c_proj", "bias"), None),
			    # layer norms
			    ((r"ln_\d+", "bias"), None),
			    ((r"\d+", r"ln_\d+", "scale"), None),
			    (("ln_f", "bias"), None),
			    (("ln_f", "scale"), None),
			]







def        UpperCamelCase_(				_A   :Union[str, Any]  )->		str:
			UpperCamelCase__					=       _get_partition_rules()
			UpperCamelCase__					=       _replacement_rules(_A  )
			UpperCamelCase__					=       {k: _unmatched for k in flatten_dict(_A  )}
			UpperCamelCase__					=       {k: replace(_A				,     _A  ) for k, v in initd.items()}
			assert _unmatched not in result.values(), "Incomplete partition spec."
			return freeze(unflatten_dict(_A  )  )






import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil
@pytest.fixture
def        UpperCamelCase_(				_A   :Union[str, Any]  )->		int:
			UpperCamelCase__					=       tmp_path / "file.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        header1,header2\n        1,2\n        10,20\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :int  )->		Union[str, Any]:
			UpperCamelCase__					=       tmp_path / "malformed_file.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        header1,header2\n        1,2\n        10,20,\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :List[Any]				,     _A   :Dict  )->		Optional[Any]:
			UpperCamelCase__					=       tmp_path / "csv_with_image.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    F'''\
        image
        {image_file}
        '''  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :List[Any]  )->		Any:
			UpperCamelCase__					=       tmp_path / "csv_with_label.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        label\n        good\n        bad\n        good\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :Any  )->		int:
			UpperCamelCase__					=       tmp_path / "csv_with_int_list.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
def        UpperCamelCase_(				_A   :Optional[Any]				,     _A   :Optional[Any]				,     _A   :List[str]  )->		Union[str, Any]:
			UpperCamelCase__					=       Csv()
			UpperCamelCase__					=       csv._generate_tables([[csv_file, malformed_csv_file]]  )
			with pytest.raises(_A				,     match="Error tokenizing data"  ):
						for _ in generator:
									pass
			assert any(
			    record.levelname == "ERROR"
			    and "Failed to read file" in record.message
			    and os.path.basename(_A  ) in record.message
			    for record in caplog.records  )
@require_pil
def        UpperCamelCase_(				_A   :Any  )->		int:
			with open(_A				,     encoding="utf-8"  ) as f:
						UpperCamelCase__					=       f.read().splitlines()[1]
			UpperCamelCase__					=       Csv(encoding="utf-8"				,     features=Features({"image": Image()}  )  )
			UpperCamelCase__					=       csv._generate_tables([[csv_file_with_image]]  )
			UpperCamelCase__					=       pa.concat_tables([table for _, table in generator]  )
			assert pa_table.schema.field("image"  ).type == Image()()
			UpperCamelCase__					=       pa_table.to_pydict()["image"]
			assert generated_content == [{"path": image_file, "bytes": None}]
def        UpperCamelCase_(				_A   :Any  )->		Dict:
			with open(_A				,     encoding="utf-8"  ) as f:
						UpperCamelCase__					=       f.read().splitlines()[1:]
			UpperCamelCase__					=       Csv(encoding="utf-8"				,     features=Features({"label": ClassLabel(names=["good", "bad"]  )}  )  )
			UpperCamelCase__					=       csv._generate_tables([[csv_file_with_label]]  )
			UpperCamelCase__					=       pa.concat_tables([table for _, table in generator]  )
			assert pa_table.schema.field("label"  ).type == ClassLabel(names=["good", "bad"]  )()
			UpperCamelCase__					=       pa_table.to_pydict()["label"]
			assert generated_content == [ClassLabel(names=["good", "bad"]  ).straint(_A  ) for label in labels]







def        UpperCamelCase_(				_A   :Dict  )->		Optional[Any]:
			UpperCamelCase__					=       Csv(encoding="utf-8"				,     sep=","				,     converters={"int_list": lambda _A  : [int(_A  ) for i in x.split()]}  )
			UpperCamelCase__					=       csv._generate_tables([[csv_file_with_int_list]]  )
			UpperCamelCase__					=       pa.concat_tables([table for _, table in generator]  )
			assert pa.types.is_list(pa_table.schema.field("int_list"  ).type  )
			UpperCamelCase__					=       pa_table.to_pydict()["int_list"]
			assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]


