





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCAmelCase			:List[str]	 =     {
    'configuration_open_llama': ['OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OpenLlamaConfig'],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase			:List[Any]	 =     ['LlamaTokenizer']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase			:Tuple	 =     ['LlamaTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase			:List[Any]	 =     [
							    'OpenLlamaForCausalLM',
							    'OpenLlamaModel',
							    'OpenLlamaPreTrainedModel',
							    'OpenLlamaForSequenceClassification',
							]


if TYPE_CHECKING:
							from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from transformers import LlamaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from transformers import LlamaTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_open_llama import (
														    OpenLlamaForCausalLM,
														    OpenLlamaForSequenceClassification,
														    OpenLlamaModel,
														    OpenLlamaPreTrainedModel,
														)


else:
							import sys

							__lowerCAmelCase			:Dict	 =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






def  A					(				UpperCAmelCase	,	UpperCAmelCase					):
					# "Simpson Rule"
					# int(f) = delta_x/2 * (b-a)/3*(f1 + 4f2 + 2f_3 + ... + fn)
					_snake_case							:       List[str]												= (boundary[1] - boundary[0]) / steps
					_snake_case							:       List[Any]												= boundary[0]
					_snake_case							:       Tuple												= boundary[1]
					_snake_case							:       str												= make_points(UpperCAmelCase	,	UpperCAmelCase	,	UpperCAmelCase					)
					_snake_case							:       str												= 0.0
					y += (h / 3.0) * f(UpperCAmelCase					)
					_snake_case							:       Tuple												= 2
					for i in x_i:
										y += (h / 3) * (4 - 2 * (cnt % 2)) * f(UpperCAmelCase					)
										cnt += 1
					y += (h / 3.0) * f(UpperCAmelCase					)
					return y







def  A					(				UpperCAmelCase	,	UpperCAmelCase	,	UpperCAmelCase					):
					_snake_case							:       Union[str, Any]												= a + h
					while x < (b - h):
										yield x
										_snake_case							:       Optional[Any]												= x + h







def  A					(				UpperCAmelCase					):  # enter your function here
					_snake_case							:       Dict												= (x - 0) * (x - 0)
					return y







def  A					(				):
					_snake_case							:       int												= 0.0  # Lower bound of integration
					_snake_case							:       Union[str, Any]												= 1.0  # Upper bound of integration
					_snake_case							:       List[str]												= 1_0.0  # define number of steps or resolution
					_snake_case							:       Optional[int]												= [a, b]  # define boundary of integration
					_snake_case							:       List[str]												= method_a(UpperCAmelCase	,	UpperCAmelCase					)
					print(F"""y = {y}"""					)


if __name__ == "__main__":
							main()