'''simple docstring'''




import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


_a   :	List[Any] 							=   "__DUMMY_TRANSFORMERS_USER__"
_a   :	str 							=   "Dummy User"
_a   :	str 							=   "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"

_a   :	Optional[Any] 							=   "https://hub-ci.huggingface.co"
_a   :	List[str] 							=   CI_HUB_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
_a   :	List[Any] 							=   CI_HUB_ENDPOINT + "/{repo_id}/resolve/{revision}/{filename}"
_a   :	List[str] 							=   Path("~/.huggingface/hub_ci_token").expanduser()

@pytest.fixture
def _lowercase	(      lowerCamelCase__						)					->       Optional[Any]:





       """simple docstring"""


       monkeypatch.setattr(
           "huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"							,    lowerCamelCase__						)

@pytest.fixture
def _lowercase	(      lowerCamelCase__						)					->       int:





       """simple docstring"""


       monkeypatch.setattr("datasets.config.HF_ENDPOINT"							,    lowerCamelCase__						)
       monkeypatch.setattr("datasets.config.HUB_DATASETS_URL"							,    lowerCamelCase__						)

@pytest.fixture
def _lowercase	(      lowerCamelCase__						)					->       Optional[Any]:





       """simple docstring"""


       monkeypatch.setattr("huggingface_hub.hf_api.HfFolder.path_token"							,    lowerCamelCase__						)

@pytest.fixture
def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       Dict:





       """simple docstring"""


       HfFolder.save_token(lowerCamelCase__						)
       yield
       HfFolder.delete_token()

@pytest.fixture(scope="session"						)
def _lowercase	(      )					->       Union[str, Any]:





       """simple docstring"""


       return HfApi(endpoint=lowerCamelCase__						)

@pytest.fixture(scope="session"						)
def _lowercase	(      lowerCamelCase__						)					->       Tuple:





       """simple docstring"""


       __UpperCAmelCase  :				int       				=		HfFolder.get_token()
       HfFolder.save_token(lowerCamelCase__						)
       yield CI_HUB_USER_TOKEN
       if previous_token is not None:
              HfFolder.save_token(lowerCamelCase__						)

@pytest.fixture
def _lowercase	(      lowerCamelCase__						)					->       Optional[int]:





       """simple docstring"""


       def _cleanup_repo(lowerCamelCase__						):
              hf_api.delete_repo(lowerCamelCase__							,    token=lowerCamelCase__							,    repo_type="dataset"						)

       return _cleanup_repo

@pytest.fixture
def _lowercase	(      lowerCamelCase__						)					->       Optional[int]:





       """simple docstring"""


       @contextmanager
       def _temporary_repo(lowerCamelCase__						):
              try:
                     yield repo_id
              finally:
                     cleanup_repo(lowerCamelCase__						)

       return _temporary_repo

@pytest.fixture(scope="session"						)
def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       Any:





       """simple docstring"""


       __UpperCAmelCase  :				List[str]       				=		f"""repo_txt_data-{int(time.time() * 1_0e3						)}"""
       __UpperCAmelCase  :				int       				=		f"""{CI_HUB_USER}/{repo_name}"""
       hf_api.create_repo(lowerCamelCase__							,    token=lowerCamelCase__							,    repo_type="dataset"							,    private=lowerCamelCase__						)
       hf_api.upload_file(
           token=lowerCamelCase__							,    path_or_fileobj=str(lowerCamelCase__						)							,    path_in_repo="data/text_data.txt"							,    repo_id=lowerCamelCase__							,    repo_type="dataset"							,    )
       yield repo_id
       try:
              hf_api.delete_repo(lowerCamelCase__							,    token=lowerCamelCase__							,    repo_type="dataset"						)
       except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
              pass

@pytest.fixture()
def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       int:





       """simple docstring"""


       return hf_private_dataset_repo_txt_data_

@pytest.fixture(scope="session"						)
def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       str:





       """simple docstring"""


       __UpperCAmelCase  :				str       				=		f"""repo_zipped_txt_data-{int(time.time() * 1_0e3						)}"""
       __UpperCAmelCase  :				str       				=		f"""{CI_HUB_USER}/{repo_name}"""
       hf_api.create_repo(lowerCamelCase__							,    token=lowerCamelCase__							,    repo_type="dataset"							,    private=lowerCamelCase__						)
       hf_api.upload_file(
           token=lowerCamelCase__							,    path_or_fileobj=str(lowerCamelCase__						)							,    path_in_repo="data.zip"							,    repo_id=lowerCamelCase__							,    repo_type="dataset"							,    )
       yield repo_id
       try:
              hf_api.delete_repo(lowerCamelCase__							,    token=lowerCamelCase__							,    repo_type="dataset"						)
       except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
              pass

@pytest.fixture()
def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       Any:





       """simple docstring"""


       return hf_private_dataset_repo_zipped_txt_data_

@pytest.fixture(scope="session"						)
def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       List[str]:





       """simple docstring"""


       __UpperCAmelCase  :				List[str]       				=		f"""repo_zipped_img_data-{int(time.time() * 1_0e3						)}"""
       __UpperCAmelCase  :				int       				=		f"""{CI_HUB_USER}/{repo_name}"""
       hf_api.create_repo(lowerCamelCase__							,    token=lowerCamelCase__							,    repo_type="dataset"							,    private=lowerCamelCase__						)
       hf_api.upload_file(
           token=lowerCamelCase__							,    path_or_fileobj=str(lowerCamelCase__						)							,    path_in_repo="data.zip"							,    repo_id=lowerCamelCase__							,    repo_type="dataset"							,    )
       yield repo_id
       try:
              hf_api.delete_repo(lowerCamelCase__							,    token=lowerCamelCase__							,    repo_type="dataset"						)
       except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
              pass


@pytest.fixture()
def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       List[str]:





       """simple docstring"""


       return hf_private_dataset_repo_zipped_img_data_







'''simple docstring'''




from __future__ import annotations

import numpy as np
from numpy import floataa
from numpy.typing import NDArray

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    )					->       list[float]:





       """simple docstring"""


       __UpperCAmelCase				, __UpperCAmelCase  :				Union[str, Any]       				=		coefficient_matrix.shape
       __UpperCAmelCase				, __UpperCAmelCase  :				Any       				=		constant_matrix.shape

       if rowsa != colsa:
              __UpperCAmelCase  :				str       				=		f"""Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}"""
              raise ValueError(lowerCamelCase__						)

       if colsa != 1:
              __UpperCAmelCase  :				Optional[Any]       				=		f"""Constant matrix must be nx1 but received {rowsa}x{colsa}"""
              raise ValueError(lowerCamelCase__						)

       if rowsa != rowsa:
              __UpperCAmelCase  :				Optional[int]       				=		(
                  "Coefficient and constant matrices dimensions must be nxn and nx1 but "
                  f"""received {rowsa}x{colsa} and {rowsa}x{colsa}"""
              )
              raise ValueError(lowerCamelCase__						)

       if len(lowerCamelCase__						) != rowsa:
              __UpperCAmelCase  :				List[str]       				=		(
                  "Number of initial values must be equal to number of rows in coefficient "
                  f"""matrix but received {len(lowerCamelCase__						)} and {rowsa}"""
              )
              raise ValueError(lowerCamelCase__						)

       if iterations <= 0:
              raise ValueError("Iterations must be at least 1"						)

       __UpperCAmelCase  :				NDArray[floataa]       				=		np.concatenate(
           (coefficient_matrix, constant_matrix)							,    axis=1						)

       __UpperCAmelCase				, __UpperCAmelCase  :				Tuple       				=		table.shape

       strictly_diagonally_dominant(lowerCamelCase__						)

       # Iterates the whole matrix for given number of times
       for _ in range(lowerCamelCase__						):
              __UpperCAmelCase  :				int       				=		[]
              for row in range(lowerCamelCase__						):
                     __UpperCAmelCase  :				List[str]       				=		0
                     for col in range(lowerCamelCase__						):
                            if col == row:
                                   __UpperCAmelCase  :				int       				=		table[row][col]
                            elif col == cols - 1:
                                   __UpperCAmelCase  :				Any       				=		table[row][col]
                            else:
                                   temp += (-1) * table[row][col] * init_val[col]
                     __UpperCAmelCase  :				List[Any]       				=		(temp + val) / denom
                     new_val.append(lowerCamelCase__						)
              __UpperCAmelCase  :				str       				=		new_val

       return [float(lowerCamelCase__						) for i in new_val]

def _lowercase	(      lowerCamelCase__						)					->       bool:





       """simple docstring"""


       __UpperCAmelCase				, __UpperCAmelCase  :				Optional[int]       				=		table.shape

       __UpperCAmelCase  :				str       				=		True

       for i in range(0							,    lowerCamelCase__						):
              __UpperCAmelCase  :				Union[str, Any]       				=		0
              for j in range(0							,    cols - 1						):
                     if i == j:
                            continue
                     else:
                            total += table[i][j]

              if table[i][i] <= total:
                     raise ValueError("Coefficient matrix is not strictly diagonally dominant"						)

       return is_diagonally_dominant


# Test Cases
if __name__ == "__main__":
   import doctest

   doctest.testmod()






