
"""simple docstring"""
def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_			)  ->      Optional[int]:


					'''simple docstring'''
					# "Simpson Rule"
					# int(f) = delta_x/2 * (b-a)/3*(f1 + 4f2 + 2f_3 + ... + fn)
					__a:    int		     =       (boundary[1] - boundary[0]) / steps
					__a:    List[Any]		     =       boundary[0]
					__a:    Optional[Any]		     =       boundary[1]
					__a:    Union[str, Any]		     =       make_points(lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)
					__a:    Any		     =       0.0
					y += (h / 3.0) * f(lowerCamelCase_			)
					__a:    List[Any]		     =       2
					for i in x_i:
										y += (h / 3) * (4 - 2 * (cnt % 2)) * f(lowerCamelCase_			)
										cnt += 1
					y += (h / 3.0) * f(lowerCamelCase_			)
					return y


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)  ->      Any:


					'''simple docstring'''
					__a:    List[Any]		     =       a + h
					while x < (b - h):
										yield x
										__a:    int		     =       x + h


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      Tuple:  # enter your function here


					'''simple docstring'''
					__a:    Dict		     =       (x - 0) * (x - 0)
					return y


def      lowerCamelCase_     (						)  ->      List[Any]:


					'''simple docstring'''
					__a:    Union[str, Any]		     =       0.0  # Lower bound of integration
					__a:    int		     =       1.0  # Upper bound of integration
					__a:    str		     =       10.0  # define number of steps or resolution
					__a:    List[str]		     =       [a, b]  # define boundary of integration
					__a:    List[str]		     =       method_a(lowerCamelCase_						,					lowerCamelCase_			)
					print(f"""y = {y}"""			)


if __name__ == "__main__":
			main()


"""simple docstring"""
from typing import TYPE_CHECKING

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


lowercase		:    Tuple			=       {
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    int			=       ['CodeGenTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Optional[int]			=       [
			    'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CodeGenForCausalLM',
			    'CodeGenModel',
			    'CodeGenPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
			from .tokenization_codegen import CodeGenTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_codegen_fast import CodeGenTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_codegen import (
						    CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CodeGenForCausalLM,
						    CodeGenModel,
						    CodeGenPreTrainedModel,
						)

else:
			import sys

			lowercase		:    Optional[Any]			=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
