





'''simple docstring'''




import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union


if TYPE_CHECKING:
  from ...processing_utils import ProcessorMixin
  from ...utils import TensorType

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


lowercase__   :				Optional[int]      =   logging.get_logger(__name__)

lowercase__   :				Optional[int]      =   {
    '''google/owlvit-base-patch32''': '''https://huggingface.co/google/owlvit-base-patch32/resolve/main/config.json''',
    '''google/owlvit-base-patch16''': '''https://huggingface.co/google/owlvit-base-patch16/resolve/main/config.json''',
    '''google/owlvit-large-patch14''': '''https://huggingface.co/google/owlvit-large-patch14/resolve/main/config.json''',
}


class 			SCREAMING_SNAKE_CASE   (a__							):
     lowerCAmelCase		      =	'''owlvit_text_model'''


     def __init__(						self						,     _UpperCAmelCase=4_9408						,     _UpperCAmelCase=512						,     _UpperCAmelCase=2048						,     _UpperCAmelCase=12						,     _UpperCAmelCase=8						,     _UpperCAmelCase=16						,     _UpperCAmelCase="quick_gelu"						,     _UpperCAmelCase=1e-5						,     _UpperCAmelCase=0.0						,     _UpperCAmelCase=0.02						,     _UpperCAmelCase=1.0						,     _UpperCAmelCase=0						,     _UpperCAmelCase=4_9406						,     _UpperCAmelCase=4_9407						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          super().__init__(pad_token_id=_UpperCAmelCase						,     bos_token_id=_UpperCAmelCase						,     eos_token_id=_UpperCAmelCase						,     **_UpperCAmelCase)

          __A						:			Optional[int]								=	vocab_size
          __A						:			List[str]								=	hidden_size
          __A						:			Any								=	intermediate_size
          __A						:			str								=	num_hidden_layers
          __A						:			int								=	num_attention_heads
          __A						:			Union[str, Any]								=	max_position_embeddings
          __A						:			Optional[int]								=	hidden_act
          __A						:			Optional[int]								=	layer_norm_eps
          __A						:			List[str]								=	attention_dropout
          __A						:			int								=	initializer_range
          __A						:			List[Any]								=	initializer_factor


     @classmethod
     def 							SCREAMING_SNAKE_CASE  (						cls						,     _UpperCAmelCase						,     **_UpperCAmelCase):

          '''simple docstring'''






          cls._set_token_in_kwargs(_UpperCAmelCase)

          __A			,__A						:			Dict								=	cls.get_config_dict(_UpperCAmelCase						,     **_UpperCAmelCase)

          # get the text config dict if we are loading from OwlViTConfig
          if config_dict.get('model_type') == "owlvit":
               __A						:			Dict								=	config_dict['text_config']

          if "model_type" in config_dict and hasattr(cls						,     'model_type') and config_dict["model_type"] != cls.model_type:
               logger.warning(
                   F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
                   F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.')

          return cls.from_dict(_UpperCAmelCase						,     **_UpperCAmelCase)




class 			SCREAMING_SNAKE_CASE   (a__							):
     lowerCAmelCase		      =	'''owlvit_vision_model'''


     def __init__(						self						,     _UpperCAmelCase=768						,     _UpperCAmelCase=3072						,     _UpperCAmelCase=12						,     _UpperCAmelCase=12						,     _UpperCAmelCase=3						,     _UpperCAmelCase=768						,     _UpperCAmelCase=32						,     _UpperCAmelCase="quick_gelu"						,     _UpperCAmelCase=1e-5						,     _UpperCAmelCase=0.0						,     _UpperCAmelCase=0.02						,     _UpperCAmelCase=1.0						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          super().__init__(**_UpperCAmelCase)

          __A						:			List[Any]								=	hidden_size
          __A						:			Optional[int]								=	intermediate_size
          __A						:			int								=	num_hidden_layers
          __A						:			List[str]								=	num_attention_heads
          __A						:			Dict								=	num_channels
          __A						:			Dict								=	image_size
          __A						:			Dict								=	patch_size
          __A						:			Tuple								=	hidden_act
          __A						:			int								=	layer_norm_eps
          __A						:			Optional[int]								=	attention_dropout
          __A						:			int								=	initializer_range
          __A						:			List[Any]								=	initializer_factor


     @classmethod
     def 							SCREAMING_SNAKE_CASE  (						cls						,     _UpperCAmelCase						,     **_UpperCAmelCase):

          '''simple docstring'''






          cls._set_token_in_kwargs(_UpperCAmelCase)

          __A			,__A						:			str								=	cls.get_config_dict(_UpperCAmelCase						,     **_UpperCAmelCase)

          # get the vision config dict if we are loading from OwlViTConfig
          if config_dict.get('model_type') == "owlvit":
               __A						:			Optional[int]								=	config_dict['vision_config']

          if "model_type" in config_dict and hasattr(cls						,     'model_type') and config_dict["model_type"] != cls.model_type:
               logger.warning(
                   F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
                   F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.')

          return cls.from_dict(_UpperCAmelCase						,     **_UpperCAmelCase)




class 			SCREAMING_SNAKE_CASE   (a__							):
     lowerCAmelCase		      =	'''owlvit'''
     lowerCAmelCase		      =	True


     def __init__(						self						,     _UpperCAmelCase=None						,     _UpperCAmelCase=None						,     _UpperCAmelCase=512						,     _UpperCAmelCase=2.6592						,     _UpperCAmelCase=True						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          super().__init__(**_UpperCAmelCase)

          if text_config is None:
               __A						:			str								=	{}
               logger.info('text_config is None. Initializing the OwlViTTextConfig with default values.')

          if vision_config is None:
               __A						:			int								=	{}
               logger.info('vision_config is None. initializing the OwlViTVisionConfig with default values.')

          __A						:			Dict								=	OwlViTTextConfig(**_UpperCAmelCase)
          __A						:			List[str]								=	OwlViTVisionConfig(**_UpperCAmelCase)

          __A						:			Dict								=	projection_dim
          __A						:			Optional[int]								=	logit_scale_init_value
          __A						:			Optional[Any]								=	return_dict
          __A						:			str								=	1.0


     @classmethod
     def 							SCREAMING_SNAKE_CASE  (						cls						,     _UpperCAmelCase						,     **_UpperCAmelCase):

          '''simple docstring'''






          cls._set_token_in_kwargs(_UpperCAmelCase)

          __A			,__A						:			int								=	cls.get_config_dict(_UpperCAmelCase						,     **_UpperCAmelCase)

          if "model_type" in config_dict and hasattr(cls						,     'model_type') and config_dict["model_type"] != cls.model_type:
               logger.warning(
                   F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
                   F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.')

          return cls.from_dict(_UpperCAmelCase						,     **_UpperCAmelCase)


     @classmethod
     def 							SCREAMING_SNAKE_CASE  (						cls						,     _UpperCAmelCase						,     _UpperCAmelCase						,     **_UpperCAmelCase):

          '''simple docstring'''






          __A						:			int								=	{}
          __A						:			str								=	text_config
          __A						:			Any								=	vision_config

          return cls.from_dict(_UpperCAmelCase						,     **_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						:			Any								=	copy.deepcopy(self.__dict__)
          __A						:			List[Any]								=	self.text_config.to_dict()
          __A						:			Tuple								=	self.vision_config.to_dict()
          __A						:			int								=	self.__class__.model_type
          return output




class 			SCREAMING_SNAKE_CASE   (a__							):


     @property
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          return OrderedDict(
              [
                  ('input_ids', {0: 'batch', 1: 'sequence'}),
                  ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
                  ('attention_mask', {0: 'batch', 1: 'sequence'}),
              ])


     @property
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          return OrderedDict(
              [
                  ('logits_per_image', {0: 'batch'}),
                  ('logits_per_text', {0: 'batch'}),
                  ('text_embeds', {0: 'batch'}),
                  ('image_embeds', {0: 'batch'}),
              ])


     @property
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          return 1e-4


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase						,     _UpperCAmelCase = -1						,     _UpperCAmelCase = -1						,     _UpperCAmelCase = None						,     ):

          '''simple docstring'''






          __A						:			List[str]								=	super().generate_dummy_inputs(
              processor.tokenizer						,     batch_size=_UpperCAmelCase						,     seq_length=_UpperCAmelCase						,     framework=_UpperCAmelCase)
          __A						:			Union[str, Any]								=	super().generate_dummy_inputs(
              processor.image_processor						,     batch_size=_UpperCAmelCase						,     framework=_UpperCAmelCase)
          return {**text_input_dict, **image_input_dict}


     @property
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          return 14






'''simple docstring'''




from math import pi, sqrt, tan






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if side_length < 0:
          raise ValueError('surface_area_cube() only accepts non-negative values'      )
     return 6 * side_length**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if length < 0 or breadth < 0 or height < 0:
          raise ValueError('surface_area_cuboid() only accepts non-negative values'      )
     return 2 * ((length * breadth) + (breadth * height) + (length * height))






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if radius < 0:
          raise ValueError('surface_area_sphere() only accepts non-negative values'      )
     return 4 * pi * radius**2






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if radius < 0:
          raise ValueError('surface_area_hemisphere() only accepts non-negative values'      )
     return 3 * pi * radius**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius < 0 or height < 0:
          raise ValueError('surface_area_cone() only accepts non-negative values'      )
     return pi * radius * (radius + (height**2 + radius**2) ** 0.5)






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius_a < 0 or radius_a < 0 or height < 0:
          raise ValueError(
              'surface_area_conical_frustum() only accepts non-negative values'      )
     __A						:			Union[str, Any]								=	(height**2 + (radius_a - radius_a) ** 2) ** 0.5
     return pi * ((slant_height * (radius_a + radius_a)) + radius_a**2 + radius_a**2)






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius < 0 or height < 0:
          raise ValueError('surface_area_cylinder() only accepts non-negative values'      )
     return 2 * pi * radius * (height + radius)






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if torus_radius < 0 or tube_radius < 0:
          raise ValueError('surface_area_torus() only accepts non-negative values'      )
     if torus_radius < tube_radius:
          raise ValueError(
              'surface_area_torus() does not support spindle or self intersecting tori'      )
     return 4 * pow(__snake_case			,							2      ) * torus_radius * tube_radius






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if length < 0 or width < 0:
          raise ValueError('area_rectangle() only accepts non-negative values'      )
     return length * width






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if side_length < 0:
          raise ValueError('area_square() only accepts non-negative values'      )
     return side_length**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if base < 0 or height < 0:
          raise ValueError('area_triangle() only accepts non-negative values'      )
     return (base * height) / 2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if sidea < 0 or sidea < 0 or sidea < 0:
          raise ValueError('area_triangle_three_sides() only accepts non-negative values'      )
     elif sidea + sidea < sidea or sidea + sidea < sidea or sidea + sidea < sidea:
          raise ValueError('Given three sides do not form a triangle'      )
     __A						:			int								=	(sidea + sidea + sidea) / 2
     __A						:			Tuple								=	sqrt(
         semi_perimeter
         * (semi_perimeter - sidea)
         * (semi_perimeter - sidea)
         * (semi_perimeter - sidea)      )
     return area






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if base < 0 or height < 0:
          raise ValueError('area_parallelogram() only accepts non-negative values'      )
     return base * height






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if basea < 0 or basea < 0 or height < 0:
          raise ValueError('area_trapezium() only accepts non-negative values'      )
     return 1 / 2 * (basea + basea) * height






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if radius < 0:
          raise ValueError('area_circle() only accepts non-negative values'      )
     return pi * radius**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius_x < 0 or radius_y < 0:
          raise ValueError('area_ellipse() only accepts non-negative values'      )
     return pi * radius_x * radius_y






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if diagonal_a < 0 or diagonal_a < 0:
          raise ValueError('area_rhombus() only accepts non-negative values'      )
     return 1 / 2 * diagonal_a * diagonal_a






def 	_lowerCAmelCase      (  __snake_case  :			int			,							__snake_case  :			float      )					->					float:
     if not isinstance(__snake_case			,							__snake_case      ) or sides < 3:
          raise ValueError(
              'area_reg_polygon() only accepts integers greater than or \
equal to three as number of sides'      )
     elif length < 0:
          raise ValueError(
              'area_reg_polygon() only accepts non-negative values as \
length of a side'      )
     return (sides * length**2) / (4 * tan(pi / sides      ))
     return (sides * length**2) / (4 * tan(pi / sides      ))


if __name__ == "__main__":
  import doctest

  doctest.testmod(verbose=True)  # verbose so we can see methods missing tests

  print('''[DEMO] Areas of various geometric shapes: \n''')
  print(f"""Rectangle: {area_rectangle(10, 20) = }""")
  print(f"""Square: {area_square(10) = }""")
  print(f"""Triangle: {area_triangle(10, 10) = }""")
  print(f"""Triangle: {area_triangle_three_sides(5, 12, 13) = }""")
  print(f"""Parallelogram: {area_parallelogram(10, 20) = }""")
  print(f"""Rhombus: {area_rhombus(10, 20) = }""")
  print(f"""Trapezium: {area_trapezium(10, 20, 30) = }""")
  print(f"""Circle: {area_circle(20) = }""")
  print(f"""Ellipse: {area_ellipse(10, 20) = }""")
  print('''\nSurface Areas of various geometric shapes: \n''')
  print(f"""Cube: {surface_area_cube(20) = }""")
  print(f"""Cuboid: {surface_area_cuboid(10, 20, 30) = }""")
  print(f"""Sphere: {surface_area_sphere(20) = }""")
  print(f"""Hemisphere: {surface_area_hemisphere(20) = }""")
  print(f"""Cone: {surface_area_cone(10, 20) = }""")
  print(f"""Conical Frustum: {surface_area_conical_frustum(10, 20, 30) = }""")
  print(f"""Cylinder: {surface_area_cylinder(10, 20) = }""")
  print(f"""Torus: {surface_area_torus(20, 10) = }""")
  print(f"""Equilateral Triangle: {area_reg_polygon(3, 10) = }""")
  print(f"""Square: {area_reg_polygon(4, 10) = }""")
  print(f"""Reqular Pentagon: {area_reg_polygon(5, 10) = }""")