


'''simple docstring'''






from typing import TYPE_CHECKING

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


__UpperCAmelCase       							=				{
    '''configuration_conditional_detr''': [
        '''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConditionalDetrConfig''',
        '''ConditionalDetrOnnxConfig''',
    ]
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase       							=				['''ConditionalDetrFeatureExtractor''']
		__UpperCAmelCase       							=				['''ConditionalDetrImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase       							=				[
		    '''CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ConditionalDetrForObjectDetection''',
		    '''ConditionalDetrForSegmentation''',
		    '''ConditionalDetrModel''',
		    '''ConditionalDetrPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_conditional_detr import (
		    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ConditionalDetrConfig,
		    ConditionalDetrOnnxConfig,
		)

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
				from .image_processing_conditional_detr import ConditionalDetrImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_conditional_detr import (
				    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ConditionalDetrForObjectDetection,
				    ConditionalDetrForSegmentation,
				    ConditionalDetrModel,
				    ConditionalDetrPreTrainedModel,
				)

else:
		import sys

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



'''simple docstring'''






from collections.abc import Callable

import numpy as np


def    _snake_case  (	A					,       A					,       A					,       A					,       A			)		->       np.array:
							lowerCAmelCase__			  =      int(np.ceil((x_end - xa) / step_size			)			)
							lowerCAmelCase__			  =      np.zeros((n + 1,)			)
							lowerCAmelCase__			  =      ya
							lowerCAmelCase__			  =      xa

							for k in range(A			):
														lowerCAmelCase__			  =      y[k] + step_size * ode_func(A					,       y[k]			)
														lowerCAmelCase__			  =      y[k] + (
														    (step_size / 2) * (ode_func(A					,       y[k]			) + ode_func(x + step_size					,       A			))
														)
														x += step_size

							return y


if __name__ == "__main__":
		import doctest

		doctest.testmod()