




'''simple docstring'''


import numpy

# List of input, output pairs
_snake_case : Tuple  				=						(
    ((5, 2, 3), 15),
    ((6, 5, 9), 25),
    ((11, 12, 13), 41),
    ((1, 1, 1), 8),
    ((11, 12, 13), 41),
)
_snake_case : str  				=						(((515, 22, 13), 555), ((61, 35, 49), 150))
_snake_case : Optional[Any]  				=						[2, 4, 1, 5]
_snake_case : List[Any]  				=						len(train_data)
_snake_case : str  				=						0.009
def 						snake_case_       (UpperCamelCase			:    Any					,		UpperCamelCase			:    Tuple="train" ):





							'''simple docstring'''


							return calculate_hypothesis_value(UpperCamelCase					,		UpperCamelCase ) - output(
							    UpperCamelCase					,		UpperCamelCase )
def 						snake_case_       (UpperCamelCase			:    List[str] ):





							'''simple docstring'''


							_a      	=							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 						snake_case_       (UpperCamelCase			:    int					,		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 						snake_case_       (UpperCamelCase			:    str					,		UpperCamelCase			:    int ):





							'''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 						snake_case_       (UpperCamelCase			:    int					,		UpperCamelCase			:    Union[str, Any]=m ):





							'''simple docstring'''


							_a      	=							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 						snake_case_       (UpperCamelCase			:    Dict ):





							'''simple docstring'''


							_a      	=							summation_of_cost_derivative(UpperCamelCase					,		UpperCamelCase ) / m
							return cost_derivative_value
def 						snake_case_       ():





							'''simple docstring'''


							global parameter_vector
							# Tune these values to set a tolerance value for predicted output
							_a      	=							0.000002
							_a      	=							0
							_a      	=							0
							while True:
														j += 1
														_a      	=							[0, 0, 0, 0]
														for i in range(0					,		len(UpperCamelCase ) ):
																					_a      	=							get_cost_derivative(i - 1 )
																					_a      	=							(
																					    parameter_vector[i] - LEARNING_RATE * cost_derivative
																					)
														if numpy.allclose(
														    UpperCamelCase					,		UpperCamelCase					,		atol=UpperCamelCase					,		rtol=UpperCamelCase					,		):
																					break
														_a      	=							temp_parameter_vector
							print(('''Number of iterations:''', j) )
def 						snake_case_       ():





							'''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 os
import re
import shutil
import sys
import tempfile
import unittest

import black


_snake_case : str  				=						os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
_snake_case : List[str]  				=						'    \"""\n    Output class for the scheduler\'s step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"""\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n'

class      A       (						unittest.TestCase       ):







							def   __lowerCAmelCase     (    self			:    int   )     ->				List[Any]:


														"""simple docstring"""


														_a      	=							tempfile.mkdtemp()
														os.makedirs(os.path.join(self.diffusers_dir				,     '''schedulers/'''   )   )
														_a      	=							self.diffusers_dir
														shutil.copy(
														    os.path.join(lowerCAmelCase_				,     '''src/diffusers/schedulers/scheduling_ddpm.py'''   )				,     os.path.join(self.diffusers_dir				,     '''schedulers/scheduling_ddpm.py'''   )				,     )







							def   __lowerCAmelCase     (    self			:    Dict   )     ->				int:


														"""simple docstring"""


														_a      	=							'''src/diffusers'''
														shutil.rmtree(self.diffusers_dir   )







							def   __lowerCAmelCase     (    self			:    int				,     lowerCAmelCase_			:    str				,     lowerCAmelCase_			:    List[Any]				,     lowerCAmelCase_			:    Union[str, Any]				,     lowerCAmelCase_			:    str=None   )     ->				Union[str, Any]:


														"""simple docstring"""


														_a      	=							comment + F'\nclass {class_name}(nn.Module):\n' + class_code
														if overwrite_result is not None:
																					_a      	=							comment + F'\nclass {class_name}(nn.Module):\n' + overwrite_result
														_a      	=							black.Mode(target_versions={black.TargetVersion.PYaa}				,     line_length=1_19   )
														_a      	=							black.format_str(lowerCAmelCase_				,     mode=lowerCAmelCase_   )
														_a      	=							os.path.join(self.diffusers_dir				,     '''new_code.py'''   )
														with open(lowerCAmelCase_				,     '''w'''				,     newline='''\n'''   ) as f:
																					f.write(lowerCAmelCase_   )
														if overwrite_result is None:
																					self.assertTrue(len(check_copies.is_copy_consistent(lowerCAmelCase_   )   ) == 0   )
														else:
																					check_copies.is_copy_consistent(f.name				,     overwrite=lowerCAmelCase_   )
																					with open(lowerCAmelCase_				,     '''r'''   ) as f:
																												self.assertTrue(f.read()				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Optional[Any]   )     ->				Union[str, Any]:


														"""simple docstring"""


														_a      	=							check_copies.find_code_in_diffusers('''schedulers.scheduling_ddpm.DDPMSchedulerOutput'''   )
														self.assertEqual(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Dict   )     ->				Union[str, Any]:


														"""simple docstring"""


														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''				,     '''DDPMSchedulerOutput'''				,     REFERENCE_CODE + '''\n'''				,     )

														# With no empty line at the end
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''				,     '''DDPMSchedulerOutput'''				,     lowerCAmelCase_				,     )

														# Copy consistency with rename
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''				,     '''TestSchedulerOutput'''				,     re.sub('''DDPM'''				,     '''Test'''				,     lowerCAmelCase_   )				,     )

														# Copy consistency with a really long name
														_a      	=							'''TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason'''
														self.check_copy_consistency(
														    F'# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}'				,     F'{long_class_name}SchedulerOutput'				,     re.sub('''Bert'''				,     lowerCAmelCase_				,     lowerCAmelCase_   )				,     )

														# Copy consistency with overwrite
														self.check_copy_consistency(
														    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''				,     '''TestSchedulerOutput'''				,     lowerCAmelCase_				,     overwrite_result=re.sub('''DDPM'''				,     '''Test'''				,     lowerCAmelCase_   )				,     )

