





'''simple docstring'''

import numpy

# List of input, output pairs
a        =						(
    ((5, 2, 3), 15),
    ((6, 5, 9), 25),
    ((11, 12, 13), 41),
    ((1, 1, 1), 8),
    ((11, 12, 13), 41),
)
a        =						(((515, 22, 13), 555), ((61, 35, 49), 150))
a        =						[2, 4, 1, 5]
a        =						len(train_data)
a        =						0.009

def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase="train"      )						->					Union[str, Any]:

   '''simple docstring'''







   return calculate_hypothesis_value(__UpperCAmelCase							,	__UpperCAmelCase      ) - output(
       __UpperCAmelCase							,	__UpperCAmelCase      )

def 						__magic_name__       (							__UpperCAmelCase      )						->					List[Any]:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE      							=       0
   for i in range(len(__UpperCAmelCase      ) - 1      ):
      hyp_val += data_input_tuple[i] * parameter_vector[i + 1]
   hyp_val += parameter_vector[0]
   return hyp_val

def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase      )						->					Optional[int]:

   '''simple docstring'''







   if data_set == "train":
      return train_data[example_no][1]
   elif data_set == "test":
      return test_data[example_no][1]
   return None

def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase      )						->					str:

   '''simple docstring'''







   if data_set == "train":
      return _hypothesis_value(train_data[example_no][0]      )
   elif data_set == "test":
      return _hypothesis_value(test_data[example_no][0]      )
   return None

def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase=m      )						->					Optional[int]:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE      							=       0
   for i in range(__UpperCAmelCase      ):
      if index == -1:
         summation_value += _error(__UpperCAmelCase      )
      else:
         summation_value += _error(__UpperCAmelCase      ) * train_data[i][0][index]
   return summation_value

def 						__magic_name__       (							__UpperCAmelCase      )						->					Union[str, Any]:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE      							=       summation_of_cost_derivative(__UpperCAmelCase							,	__UpperCAmelCase      ) / m
   return cost_derivative_value

def 						__magic_name__       (							)						->					Any:

   '''simple docstring'''







   global parameter_vector
   # Tune these values to set a tolerance value for predicted output
   __SCREAMING_SNAKE_CASE      							=       0.0_0_0_0_0_2
   __SCREAMING_SNAKE_CASE      							=       0
   __SCREAMING_SNAKE_CASE      							=       0
   while True:
      j += 1
      __SCREAMING_SNAKE_CASE      							=       [0, 0, 0, 0]
      for i in range(0							,	len(__UpperCAmelCase      )      ):
         __SCREAMING_SNAKE_CASE      							=       get_cost_derivative(i - 1      )
         __SCREAMING_SNAKE_CASE      							=       (
             parameter_vector[i] - LEARNING_RATE * cost_derivative
         )
      if numpy.allclose(
          __UpperCAmelCase							,	__UpperCAmelCase							,	atol=__UpperCAmelCase							,	rtol=__UpperCAmelCase							,	):
         break
      __SCREAMING_SNAKE_CASE      							=       temp_parameter_vector
   print(("""Number of iterations:""", j)      )

def 						__magic_name__       (							)						->					str:

   '''simple docstring'''







   for i in range(len(__UpperCAmelCase      )      ):
      print(("""Actual output value:""", output(__UpperCAmelCase							,	"""test"""      ))      )
      print(("""Hypothesis output:""", calculate_hypothesis_value(__UpperCAmelCase							,	"""test"""      ))      )


if __name__ == "__main__":
    run_gradient_descent()
    print("\nTesting gradient descent for a linear hypothesis function.\n")
    test_gradient_descent()












'''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        =						"__DUMMY_TRANSFORMERS_USER__"
a        =						"Dummy User"
a        =						"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"

a        =						"https://hub-ci.huggingface.co"
a        =						CI_HUB_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
a        =						CI_HUB_ENDPOINT + "/{repo_id}/resolve/{revision}/{filename}"
a        =						Path("~/.huggingface/hub_ci_token").expanduser()

@pytest.fixture
def 						__magic_name__       (							__UpperCAmelCase      )						->					int:

   '''simple docstring'''







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

@pytest.fixture
def 						__magic_name__       (							__UpperCAmelCase      )						->					Optional[Any]:

   '''simple docstring'''







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

@pytest.fixture
def 						__magic_name__       (							__UpperCAmelCase      )						->					Optional[Any]:

   '''simple docstring'''







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

@pytest.fixture
def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase      )						->					Dict:

   '''simple docstring'''







   HfFolder.save_token(__UpperCAmelCase      )
   yield
   HfFolder.delete_token()

@pytest.fixture(scope="""session"""      )
def 						__magic_name__       (							)						->					Optional[Any]:

   '''simple docstring'''







   return HfApi(endpoint=__UpperCAmelCase      )

@pytest.fixture(scope="""session"""      )
def 						__magic_name__       (							__UpperCAmelCase      )						->					Dict:

   '''simple docstring'''







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

@pytest.fixture
def 						__magic_name__       (							__UpperCAmelCase      )						->					Dict:

   '''simple docstring'''







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

   return _cleanup_repo

@pytest.fixture
def 						__magic_name__       (							__UpperCAmelCase      )						->					int:

   '''simple docstring'''







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

   return _temporary_repo

@pytest.fixture(scope="""session"""      )
def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase							,	__UpperCAmelCase      )						->					Dict:

   '''simple docstring'''







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

@pytest.fixture()
def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase							,	__UpperCAmelCase      )						->					Optional[Any]:

   '''simple docstring'''







   return hf_private_dataset_repo_txt_data_

@pytest.fixture(scope="""session"""      )
def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase							,	__UpperCAmelCase      )						->					Dict:

   '''simple docstring'''







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

@pytest.fixture()
def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase							,	__UpperCAmelCase      )						->					Tuple:

   '''simple docstring'''







   return hf_private_dataset_repo_zipped_txt_data_

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

   '''simple docstring'''







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







@pytest.fixture()
def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase							,	__UpperCAmelCase      )						->					Dict:

   '''simple docstring'''







   return hf_private_dataset_repo_zipped_img_data_





