"""simple docstring"""



import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


__lowercase		:		Optional[Any]														=							"http://www.mocksite.com/file1.txt"
__lowercase		:		Tuple														=							"\"text\": [\"foo\", \"foo\"]"
__lowercase		:		Tuple														=							"6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"



class      _A	:




    """simple docstring"""




    UpperCamelCase_	:					Any							=					2_0_0
    UpperCamelCase_	:					int							=					{'''Content-Length''': '''100'''}
    UpperCamelCase_	:					int							=					{}
    def  lowercase					(		self							:     Dict	,      **A_							:     Tuple    )    ->       Dict:
         return [bytes(A_	,      '''utf-8'''    )]






def    SCREAMING_SNAKE_CASE       (     *snake_case,      **snake_case):
     return MockResponse()





@pytest.mark.parametrize('''urls_type''',      [str, list, dict])
def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case,      snake_case):
     import requests

     monkeypatch.setattr(snake_case,      '''request''',      snake_case)

     __snake_case				=							URL
     if issubclass(snake_case,      snake_case):
          __snake_case				=							url
     elif issubclass(snake_case,      snake_case):
          __snake_case				=							[url]
     elif issubclass(snake_case,      snake_case):
          __snake_case				=							{'''train''': url}
     __snake_case				=							'''dummy'''
     __snake_case				=							'''downloads'''
     __snake_case				=							tmp_path
     __snake_case				=							DownloadConfig(
         cache_dir=os.path.join(snake_case,      snake_case),      use_etag=snake_case,      )
     __snake_case				=							DownloadManager(dataset_name=snake_case,      download_config=snake_case)
     __snake_case				=							dl_manager.download(snake_case)
     __snake_case				=							urls
     for downloaded_paths in [downloaded_paths]:
          if isinstance(snake_case,      snake_case):
               __snake_case				=							[downloaded_paths]
               __snake_case				=							[urls]
          elif isinstance(snake_case,      snake_case):
               assert "train" in downloaded_paths.keys()
               __snake_case				=							downloaded_paths.values()
               __snake_case				=							urls.values()
          assert downloaded_paths
          for downloaded_path, input_url in zip(snake_case,      snake_case):
               assert downloaded_path == dl_manager.downloaded_paths[input_url]
               __snake_case				=							Path(snake_case)
               __snake_case				=							downloaded_path.parts
               assert parts[-1] == HASH
               assert parts[-2] == cache_subdir
               assert downloaded_path.exists()
               __snake_case				=							downloaded_path.read_text()
               assert content == CONTENT
               __snake_case				=							downloaded_path.with_suffix('''.json''')
               assert metadata_downloaded_path.exists()
               __snake_case				=							json.loads(metadata_downloaded_path.read_text())
               assert metadata_content == {"url": URL, "etag": None}





@pytest.mark.parametrize('''paths_type''',      [str, list, dict])
def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case,      snake_case):
     __snake_case				=							str(snake_case)
     if issubclass(snake_case,      snake_case):
          __snake_case				=							filename
     elif issubclass(snake_case,      snake_case):
          __snake_case				=							[filename]
     elif issubclass(snake_case,      snake_case):
          __snake_case				=							{'''train''': filename}
     __snake_case				=							'''dummy'''
     __snake_case				=							xz_file.parent
     __snake_case				=							'''extracted'''
     __snake_case				=							DownloadConfig(
         cache_dir=snake_case,      use_etag=snake_case,      )
     __snake_case				=							DownloadManager(dataset_name=snake_case,      download_config=snake_case)
     __snake_case				=							dl_manager.extract(snake_case)
     __snake_case				=							paths
     for extracted_paths in [extracted_paths]:
          if isinstance(snake_case,      snake_case):
               __snake_case				=							[extracted_paths]
               __snake_case				=							[paths]
          elif isinstance(snake_case,      snake_case):
               assert "train" in extracted_paths.keys()
               __snake_case				=							extracted_paths.values()
               __snake_case				=							paths.values()
          assert extracted_paths
          for extracted_path, input_path in zip(snake_case,      snake_case):
               assert extracted_path == dl_manager.extracted_paths[input_path]
               __snake_case				=							Path(snake_case)
               __snake_case				=							extracted_path.parts
               assert parts[-1] == hash_url_to_filename(snake_case,      etag=snake_case)
               assert parts[-2] == extracted_subdir
               assert extracted_path.exists()
               __snake_case				=							extracted_path.read_text()
               __snake_case				=							text_file.read_text()
               assert extracted_file_content == expected_file_content





def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case):
     assert path.endswith('''.jsonl''')
     for num_items, line in enumerate(snake_case,      start=1):
          __snake_case				=							json.loads(line.decode('''utf-8'''))
          assert item.keys() == {"col_1", "col_2", "col_3"}
     assert num_items == 4





@pytest.mark.parametrize('''archive_jsonl''',      ['''tar_jsonl_path''', '''zip_jsonl_path'''])
def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case):
     __snake_case				=							request.getfixturevalue(snake_case)
     __snake_case				=							DownloadManager()
     for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(snake_case),      start=1):
          _test_jsonl(snake_case,      snake_case)
     assert num_jsonl == 2





@pytest.mark.parametrize('''archive_nested_jsonl''',      ['''tar_nested_jsonl_path''', '''zip_nested_jsonl_path'''])
def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case):
     __snake_case				=							request.getfixturevalue(snake_case)
     __snake_case				=							DownloadManager()
     for num_tar, (path, file) in enumerate(dl_manager.iter_archive(snake_case),      start=1):
          for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(snake_case),      start=1):
               _test_jsonl(snake_case,      snake_case)
     assert num_tar == 1
     assert num_jsonl == 2





def    SCREAMING_SNAKE_CASE       (     snake_case):
     __snake_case				=							DownloadManager()
     for num_file, file in enumerate(dl_manager.iter_files(snake_case),      start=1):
          assert os.path.basename(snake_case) == ("test.txt" if num_file == 1 else "train.txt")
     assert num_file == 2
"""simple docstring"""



import math
import random
from typing import Any

from .hill_climbing import SearchProblem





def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case = True,      snake_case = math.inf,      snake_case = -math.inf,      snake_case = math.inf,      snake_case = -math.inf,      snake_case = False,      snake_case = 1_00,      snake_case = 0.01,      snake_case = 1,      ):
     __snake_case				=							False
     __snake_case				=							search_prob
     __snake_case				=							start_temperate
     __snake_case				=							[]
     __snake_case				=							0
     __snake_case				=							None

     while not search_end:
          __snake_case				=							current_state.score()
          if best_state is None or current_score > best_state.score():
               __snake_case				=							current_state
          scores.append(snake_case)
          iterations += 1
          __snake_case				=							None
          __snake_case				=							current_state.get_neighbors()
          while (
              next_state is None and neighbors
          ):  # till we do not find a neighbor that we can move to
               __snake_case				=							random.randint(0,      len(snake_case) - 1)  # picking a random neighbor
               __snake_case				=							neighbors.pop(snake_case)
               __snake_case				=							picked_neighbor.score() - current_score

               if (
                   picked_neighbor.x > max_x
                   or picked_neighbor.x < min_x
                   or picked_neighbor.y > max_y
                   or picked_neighbor.y < min_y
               ):
                    continue  # neighbor outside our bounds

               if not find_max:
                    __snake_case				=							change * -1  # in case we are finding minimum
               if change > 0:  # improves the solution
                    __snake_case				=							picked_neighbor
               else:
                    __snake_case				=							(math.e) ** (
                        change / current_temp
                    )  # probability generation function
                    if random.random() < probability:  # random number within probability
                         __snake_case				=							picked_neighbor
          __snake_case				=							current_temp - (current_temp * rate_of_decrease)

          if current_temp < threshold_temp or next_state is None:
               # temperature below threshold, or could not find a suitable neighbor
               __snake_case				=							True
          else:
               __snake_case				=							next_state

     if visualization:
          from matplotlib import pyplot as plt

          plt.plot(range(snake_case),      snake_case)
          plt.xlabel('''Iterations''')
          plt.ylabel('''Function values''')
          plt.show()
     return best_state


if __name__ == "__main__":





       def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case):
            return (x**2) + (y**2)

       # starting the problem with initial coordinates (12, 47)
       __lowercase		:		Dict														=							SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
       __lowercase		:		Union[str, Any]														=							simulated_annealing(
           prob, find_max=False, max_x=100, min_x=5, max_y=50, min_y=-5, visualization=True
       )
       print(
           "The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 "
           F"""and 50 > y > - 5 found via hill climbing: {local_min.score()}"""
       )

       # starting the problem with initial coordinates (12, 47)
       __lowercase		:		Any														=							SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
       __lowercase		:		int														=							simulated_annealing(
           prob, find_max=True, max_x=100, min_x=5, max_y=50, min_y=-5, visualization=True
       )
       print(
           "The maximum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 "
           F"""and 50 > y > - 5 found via hill climbing: {local_min.score()}"""
       )





       def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case):
            return (3 * x**2) - (6 * y)

       __lowercase		:		List[str]														=							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
       __lowercase		:		Dict														=							simulated_annealing(prob, find_max=False, visualization=True)
       print(
           "The minimum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: "
           F"""{local_min.score()}"""
       )

       __lowercase		:		Any														=							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
       __lowercase		:		Tuple														=							simulated_annealing(prob, find_max=True, visualization=True)




       print(
           "The maximum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: "
           F"""{local_min.score()}"""
       )