






"""simple docstring"""





import torch
from torch import autograd




class       _lowerCAmelCase						(			autograd.Function     ):







 """simple docstring"""







 @staticmethod
 def       _lowercase				(    UpperCAmelCase__							:    List[str],      UpperCAmelCase__							:    str,      UpperCAmelCase__							:    List[str],      UpperCAmelCase__							:    Any			):
    __lowercase			=		inputs.numel()
    __lowercase			=		int(0.005 * nb_elems			) + 1
    if sigmoid:
       __lowercase			=		(torch.sigmoid(UpperCAmelCase__			) > threshold).type(inputs.type()			)
    else:
       __lowercase			=		(inputs > threshold).type(inputs.type()			)
    if mask.sum() < nb_min:
       # We limit the pruning so that at least 0.5% (half a percent) of the weights are remaining
       __lowercase			=		inputs.flatten().kthvalue(max(nb_elems - nb_min,      1			)			).values
       __lowercase			=		(inputs > k_threshold).type(inputs.type()			)
    return mask



 @staticmethod
 def       _lowercase				(    UpperCAmelCase__							:    Any,      UpperCAmelCase__							:    Tuple			):
    return gradOutput, None, None







class       _lowerCAmelCase						(			autograd.Function     ):







 """simple docstring"""







 @staticmethod
 def       _lowercase				(    UpperCAmelCase__							:    int,      UpperCAmelCase__							:    Optional[int],      UpperCAmelCase__							:    Tuple			):
    __lowercase			=		inputs.clone()
    __lowercase	,__lowercase			=		inputs.flatten().sort(descending=UpperCAmelCase__			)
    __lowercase			=		int(threshold * inputs.numel()			)

    # flat_out and mask access the same memory.
    __lowercase			=		mask.flatten()
    __lowercase			=		0
    __lowercase			=		1
    return mask



 @staticmethod
 def       _lowercase				(    UpperCAmelCase__							:    List[Any],      UpperCAmelCase__							:    Optional[Any]			):
    return gradOutput, None







class       _lowerCAmelCase						(			A_     ):







 """simple docstring"""







 @staticmethod
 def       _lowercase				(    UpperCAmelCase__							:    Optional[int],      UpperCAmelCase__							:    Optional[int]			):
    __lowercase			=		inputs.clone()
    __lowercase	,__lowercase			=		inputs.abs().flatten().sort(descending=UpperCAmelCase__			)
    __lowercase			=		int(threshold * inputs.numel()			)

    # flat_out and mask access the same memory.
    __lowercase			=		mask.flatten()
    __lowercase			=		0
    __lowercase			=		1
    return mask







"""simple docstring"""





import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Value
from datasets.packaged_modules.json.json import Json




@pytest.fixture
def 						_A						(						UpperCamelCase_  : str)			->		Tuple:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file.jsonl"
   __lowercase			=		textwrap.dedent(
       "\\n        {\"col_1\": -1}\n        {\"col_1\": 1, \"col_2\": 2}\n        {\"col_1\": 10, \"col_2\": 20}\n        ")
   with open(UpperCamelCase_,    "w") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.fixture
def 						_A						(						UpperCamelCase_  : str)			->		Any:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file_utf16_encoded.jsonl"
   __lowercase			=		textwrap.dedent(
       "\\n        {\"col_1\": -1}\n        {\"col_1\": 1, \"col_2\": 2}\n        {\"col_1\": 10, \"col_2\": 20}\n        ")
   with open(UpperCamelCase_,    "w",    encoding="utf-16") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.fixture
def 						_A						(						UpperCamelCase_  : Optional[int])			->		Optional[Any]:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file_with_list_of_dicts.json"
   __lowercase			=		textwrap.dedent(
       "\\n        [\n            {\"col_1\": -1},\n            {\"col_1\": 1, \"col_2\": 2},\n            {\"col_1\": 10, \"col_2\": 20}\n        ]\n        ")
   with open(UpperCamelCase_,    "w") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.fixture
def 						_A						(						UpperCamelCase_  : str)			->		int:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file_with_list_of_dicts_field.json"
   __lowercase			=		textwrap.dedent(
       "\\n        {\n            \"field1\": 1,\n            \"field2\": \"aabb\",\n            \"field3\": [\n                {\"col_1\": -1},\n                {\"col_1\": 1, \"col_2\": 2},\n                {\"col_1\": 10, \"col_2\": 20}\n            ]\n        }\n        ")
   with open(UpperCamelCase_,    "w") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.mark.parametrize(
    "file_fixture, config_kwargs",    [
        ("jsonl_file", {}),
        ("jsonl_file_utf16_encoded", {"encoding": "utf-16"}),
        ("json_file_with_list_of_dicts", {}),
        ("json_file_with_list_of_dicts_field", {"field": "field3"}),
    ],    )
def 						_A						(						UpperCamelCase_  : Any,    UpperCamelCase_  : List[Any],    UpperCamelCase_  : Optional[Any])			->		List[Any]:
   '''simple docstring'''


   __lowercase			=		Json(**UpperCamelCase_)
   __lowercase			=		json._generate_tables([[request.getfixturevalue(UpperCamelCase_)]])
   __lowercase			=		pa.concat_tables([table for _, table in generator])
   assert pa_table.to_pydict() == {"col_1": [-1, 1, 10], "col_2": [None, 2, 20]}




@pytest.mark.parametrize(
    "file_fixture, config_kwargs",    [
        (
            "jsonl_file",
            {"features": Features({"col_1": Value("int64"), "col_2": Value("int64"), "missing_col": Value("string")})},
        ),
        (
            "json_file_with_list_of_dicts",
            {"features": Features({"col_1": Value("int64"), "col_2": Value("int64"), "missing_col": Value("string")})},
        ),
        (
            "json_file_with_list_of_dicts_field",
            {
                "field": "field3",
                "features": Features(
                    {"col_1": Value("int64"), "col_2": Value("int64"), "missing_col": Value("string")}),
            },
        ),
    ],    )
def 						_A						(						UpperCamelCase_  : Optional[int],    UpperCamelCase_  : int,    UpperCamelCase_  : str)			->		Optional[int]:
   '''simple docstring'''


   __lowercase			=		Json(**UpperCamelCase_)
   __lowercase			=		json._generate_tables([[request.getfixturevalue(UpperCamelCase_)]])
   __lowercase			=		pa.concat_tables([table for _, table in generator])
   assert pa_table.to_pydict() == {"col_1": [-1, 1, 10], "col_2": [None, 2, 20], "missing_col": [None, None, None]}




