
'''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    UpperCAmelCase							(  UpperCAmelCase__							:							List[str]       ,							UpperCAmelCase__							:							int="train"):
				return calculate_hypothesis_value(UpperCAmelCase__       ,							UpperCAmelCase__) - output(
				    UpperCAmelCase__       ,							UpperCAmelCase__)





def    UpperCAmelCase							(  UpperCAmelCase__							:							List[Any]):
				lowerCamelCase					:			Any									= 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    UpperCAmelCase							(  UpperCAmelCase__							:							Any       ,							UpperCAmelCase__							:							Optional[int]):
				if data_set == "train":
								return train_data[example_no][1]
				elif data_set == "test":
								return test_data[example_no][1]
				return None





def    UpperCAmelCase							(  UpperCAmelCase__							:							List[str]       ,							UpperCAmelCase__							:							Optional[int]):
				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    UpperCAmelCase							(  UpperCAmelCase__							:							List[str]       ,							UpperCAmelCase__							:							Union[str, Any]=m):
				lowerCamelCase					:			str									= 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    UpperCAmelCase							(  UpperCAmelCase__							:							Union[str, Any]):
				lowerCamelCase					:			Union[str, Any]									= summation_of_cost_derivative(UpperCAmelCase__       ,							UpperCAmelCase__) / m
				return cost_derivative_value





def    UpperCAmelCase							(  ):
				global parameter_vector
				# Tune these values to set a tolerance value for predicted output
				lowerCamelCase					:			List[Any]									= 0.0_0_0_0_0_2
				lowerCamelCase					:			List[Any]									= 0
				lowerCamelCase					:			Dict									= 0
				while True:
								j += 1
								lowerCamelCase					:			List[Any]									= [0, 0, 0, 0]
								for i in range(0       ,							len(UpperCAmelCase__)):
												lowerCamelCase					:			Optional[int]									= get_cost_derivative(i - 1)
												lowerCamelCase					:			Optional[Any]									= (
												    parameter_vector[i] - LEARNING_RATE * cost_derivative
												)
								if numpy.allclose(
								    UpperCAmelCase__       ,							UpperCAmelCase__       ,							atol=UpperCAmelCase__       ,							rtol=UpperCAmelCase__       ,							):
												break
								lowerCamelCase					:			List[Any]									= temp_parameter_vector
				print(('Number of iterations:', j))





def    UpperCAmelCase							(  ):
				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 warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A			      =      logging.get_logger(__name__)

A			      =      {
    'nvidia/segformer-b0-finetuned-ade-512-512': (
        'https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}




class     __snake_case		(   a__):
					_lowerCAmelCase			     =	'''segformer'''
					def __init__(     self,    A=3,    A=4,    A=[2, 2, 2, 2],    A=[8, 4, 2, 1],    A=[32, 64, 160, 256],    A=[7, 3, 3, 3],    A=[4, 2, 2, 2],    A=[1, 2, 5, 8],    A=[4, 4, 4, 4],    A="gelu",    A=0.0,    A=0.0,    A=0.1,    A=0.02,    A=0.1,    A=1e-6,    A=256,    A=255,    **A,    ):

									"""simple docstring"""


									super().__init__(**A      )

									if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
													warnings.warn(
													    'Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'
													    ' removed, as the behaviour will default to that of reshape_last_stage = True.',    A,    )

									lowerCamelCase					:			Tuple									= num_channels
									lowerCamelCase					:			Dict									= num_encoder_blocks
									lowerCamelCase					:			Dict									= depths
									lowerCamelCase					:			Any									= sr_ratios
									lowerCamelCase					:			List[Any]									= hidden_sizes
									lowerCamelCase					:			List[Any]									= patch_sizes
									lowerCamelCase					:			Tuple									= strides
									lowerCamelCase					:			int									= mlp_ratios
									lowerCamelCase					:			Dict									= num_attention_heads
									lowerCamelCase					:			Union[str, Any]									= hidden_act
									lowerCamelCase					:			Tuple									= hidden_dropout_prob
									lowerCamelCase					:			Optional[int]									= attention_probs_dropout_prob
									lowerCamelCase					:			List[str]									= classifier_dropout_prob
									lowerCamelCase					:			Union[str, Any]									= initializer_range
									lowerCamelCase					:			Union[str, Any]									= drop_path_rate
									lowerCamelCase					:			int									= layer_norm_eps
									lowerCamelCase					:			Any									= decoder_hidden_size
									lowerCamelCase					:			Optional[int]									= kwargs.get('reshape_last_stage',    A      )
									lowerCamelCase					:			Any									= semantic_loss_ignore_index





class     __snake_case		(   a__):
					_lowerCAmelCase			     =	version.parse('''1.11''')
					@property
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return OrderedDict(
									    [
									        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
									    ]      )
					@property
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return 1e-4




					@property
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return 12
