
import numpy

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


def 				a__ (				snake_case    ,       snake_case="train"				):





  """simple docstring"""
  return calculate_hypothesis_value(snake_case    ,       snake_case				) - output(
      snake_case    ,       snake_case				)


def 				a__ (				snake_case				):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE	:     int =						0
  for i in range(len(snake_case				) - 1				):
    hyp_val += data_input_tuple[i] * parameter_vector[i + 1]
  hyp_val += parameter_vector[0]
  return hyp_val


def 				a__ (				snake_case    ,       snake_case				):





  """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 				a__ (				snake_case    ,       snake_case				):





  """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 				a__ (				snake_case    ,       snake_case=m				):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE	:     List[str] =						0
  for i in range(snake_case				):
    if index == -1:
      summation_value += _error(snake_case				)
    else:
      summation_value += _error(snake_case				) * train_data[i][0][index]
  return summation_value


def 				a__ (				snake_case				):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE	:     Optional[int] =						summation_of_cost_derivative(snake_case    ,       snake_case				) / m
  return cost_derivative_value


def 				a__ (				):





  """simple docstring"""
  global parameter_vector
  # Tune these values to set a tolerance value for predicted output
  __SCREAMING_SNAKE_CASE	:     List[str] =						0.00_0002
  __SCREAMING_SNAKE_CASE	:     Any =						0
  __SCREAMING_SNAKE_CASE	:     str =						0
  while True:
    j += 1
    __SCREAMING_SNAKE_CASE	:     Optional[Any] =						[0, 0, 0, 0]
    for i in range(0    ,       len(snake_case				)				):
      __SCREAMING_SNAKE_CASE	:     Union[str, Any] =						get_cost_derivative(i - 1				)
      __SCREAMING_SNAKE_CASE	:     Optional[int] =						(
          parameter_vector[i] - LEARNING_RATE * cost_derivative
      )
    if numpy.allclose(
        snake_case    ,       snake_case    ,       atol=snake_case    ,       rtol=snake_case    ,       ):
      break
    __SCREAMING_SNAKE_CASE	:     Union[str, Any] =						temp_parameter_vector
  print(('''Number of iterations:''', j)				)


def 				a__ (				):





  """simple docstring"""







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


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

# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser




def       _snake_case	(   ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		int				      =    ArgumentParser("Accelerate CLI tool"   , usage="accelerate <command> [<args>]"   , allow_abbrev=lowerCAmelCase	)
		SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    parser.add_subparsers(help="accelerate command helpers"	)

		# Register commands
		get_config_parser(subparsers=lowerCAmelCase	)
		env_command_parser(subparsers=lowerCAmelCase	)
		launch_command_parser(subparsers=lowerCAmelCase	)
		tpu_command_parser(subparsers=lowerCAmelCase	)
		test_command_parser(subparsers=lowerCAmelCase	)

		# Let's go
		SCREAMING_SNAKE_CASE_  :		Dict				      =    parser.parse_args()

		if not hasattr(lowerCAmelCase   , "func"	):
				parser.print_help()
				exit(1	)

		# Run
		args.func(lowerCAmelCase	)


if __name__ == "__main__":
		main()
