


def     __magic_name__  (      lowerCAmelCase_      ,					lowerCAmelCase_):
	'''simple docstring'''


	lowerCamelCase_			:							List[str]      =       (boundary[1] - boundary[0]) / steps
	lowerCamelCase_			:							Optional[Any]      =       boundary[0]
	lowerCamelCase_			:							int      =       boundary[1]
	lowerCamelCase_			:							List[Any]      =       make_points(SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_)
	lowerCamelCase_			:							Dict      =       0.0
	y += (h / 3.0) * f(SCREAMING_SNAKE_CASE_)
	lowerCamelCase_			:							Tuple      =       2
	for i in x_i:
		y += (h / 3) * (4 - 2 * (cnt % 2)) * f(SCREAMING_SNAKE_CASE_)
		cnt += 1
	y += (h / 3.0) * f(SCREAMING_SNAKE_CASE_)
	return y







def     __magic_name__  (      lowerCAmelCase_      ,					lowerCAmelCase_      ,					lowerCAmelCase_):
	'''simple docstring'''


	lowerCamelCase_			:							List[Any]      =       a + h
	while x < (b - h):
		yield x
		lowerCamelCase_			:							List[Any]      =       x + h







def     __magic_name__  (      lowerCAmelCase_):  # enter your function here
	'''simple docstring'''


	lowerCamelCase_			:							List[str]      =       (x - 0) * (x - 0)
	return y







def     __magic_name__  (      ):
	'''simple docstring'''


	lowerCamelCase_			:							List[Any]      =       0.0  # Lower bound of integration
	lowerCamelCase_			:							Optional[Any]      =       1.0  # Upper bound of integration
	lowerCamelCase_			:							str      =       10.0  # define number of steps or resolution
	lowerCamelCase_			:							List[Any]      =       [a, b]  # define boundary of integration
	lowerCamelCase_			:							List[str]      =       method_a(SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_)
	print(F"""y = {y}""")


if __name__ == "__main__":
							main()





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__magic_name__       					=      {'''configuration_detr''': ['''DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetrConfig''', '''DetrOnnxConfig''']}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      ['''DetrFeatureExtractor''']
							__magic_name__       					=      ['''DetrImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__magic_name__       					=      [
							    '''DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''DetrForObjectDetection''',
							    '''DetrForSegmentation''',
							    '''DetrModel''',
							    '''DetrPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_detr import DetrFeatureExtractor
														from .image_processing_detr import DetrImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_detr import (
														    DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DetrForObjectDetection,
														    DetrForSegmentation,
														    DetrModel,
														    DetrPreTrainedModel,
														)

else:
							import sys

							__magic_name__       					=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

