


'''simple docstring'''


from __future__ import annotations

import random

from matplotlib import animation
from matplotlib import pyplot as plt

# Frame rate of the animation
UpperCAmelCase_	:     Union[str, Any]							     =	20

# Time between time steps in seconds
UpperCAmelCase_	:     str							     =	INTERVAL / 1000





class 					lowercase__						:





							'''simple docstring'''


							def __init__(					self					,      __snake_case					,      __snake_case					,      __snake_case					,      __snake_case					,      __snake_case = 1.0					,      __snake_case = 1.0					,      __snake_case = "blue"					,      ):
											_SCREAMING_SNAKE_CASE				: str  	=   position_x
											_SCREAMING_SNAKE_CASE				: Dict  	=   position_y
											_SCREAMING_SNAKE_CASE				: Any  	=   velocity_x
											_SCREAMING_SNAKE_CASE				: Tuple  	=   velocity_y
											_SCREAMING_SNAKE_CASE				: Optional[int]  	=   mass
											_SCREAMING_SNAKE_CASE				: int  	=   size
											_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   color






							@property
							def UpperCAmelCase_			(					self						):
											return self.position_x, self.position_y






							@property
							def UpperCAmelCase_			(					self						):
											return self.velocity_x, self.velocity_y






							def UpperCAmelCase_			(					self					,      __snake_case					,      __snake_case					,      __snake_case						):
											self.velocity_x += force_x * delta_time
											self.velocity_y += force_y * delta_time






							def UpperCAmelCase_			(					self					,      __snake_case						):
											self.position_x += self.velocity_x * delta_time
											self.position_y += self.velocity_y * delta_time





class 					lowercase__						:





							'''simple docstring'''


							def __init__(					self					,      __snake_case					,      __snake_case = 1.0					,      __snake_case = 1.0					,      __snake_case = 0.0					,      ):
											_SCREAMING_SNAKE_CASE				: Tuple  	=   bodies
											_SCREAMING_SNAKE_CASE				: Dict  	=   gravitation_constant
											_SCREAMING_SNAKE_CASE				: int  	=   time_factor
											_SCREAMING_SNAKE_CASE				: Optional[int]  	=   softening_factor






							def __len__(					self						):
											return len(self.bodies						)






							def UpperCAmelCase_			(					self					,      __snake_case						):
											for bodya in self.bodies:
															_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   0.0
															_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   0.0
															for bodya in self.bodies:
																			if bodya != bodya:
																							_SCREAMING_SNAKE_CASE				: Any  	=   bodya.position_x - bodya.position_x
																							_SCREAMING_SNAKE_CASE				: str  	=   bodya.position_y - bodya.position_y

																							# Calculation of the distance using Pythagoras's theorem
																							# Extra factor due to the softening technique
																							_SCREAMING_SNAKE_CASE				: Optional[int]  	=   (dif_x**2 + dif_y**2 + self.softening_factor) ** (
																							    1 / 2
																							)

																							# Newton's law of universal gravitation.
																							force_x += (
																							    self.gravitation_constant * bodya.mass * dif_x / distance**3
																							)
																							force_y += (
																							    self.gravitation_constant * bodya.mass * dif_y / distance**3
																							)

            # Update the body's velocity once all the force components have been added
															bodya.update_velocity(__snake_case					,      __snake_case					,      delta_time * self.time_factor						)

											# Update the positions only after all the velocities have been updated
											for body in self.bodies:
															body.update_position(delta_time * self.time_factor						)







def     snake_case_     (						SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__  ):







				"""simple docstring"""





				body_system.update_system(SCREAMING_SNAKE_CASE__  )

				# Update the positions of the patches
				for patch, body in zip(SCREAMING_SNAKE_CASE__							,   body_system.bodies  ):
								_SCREAMING_SNAKE_CASE				: Any  	=   (body.position_x, body.position_y)







def     snake_case_     (						SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__ = -1							,   SCREAMING_SNAKE_CASE__ = 1							,   SCREAMING_SNAKE_CASE__ = -1							,   SCREAMING_SNAKE_CASE__ = 1							,   ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: Optional[int]  	=   plt.figure()
				fig.canvas.set_window_title(SCREAMING_SNAKE_CASE__  )
				_SCREAMING_SNAKE_CASE				: int  	=   plt.axes(
				    xlim=(x_start, x_end)							,   ylim=(y_start, y_end)  )  # Set section to be plotted
				plt.gca().set_aspect("""equal"""  )  # Fix aspect ratio

				# Each body is drawn as a patch by the plt-function
				_SCREAMING_SNAKE_CASE				: Dict  	=   [
				    plt.Circle((body.position_x, body.position_y)							,   body.size							,   fc=body.color  )
				    for body in body_system.bodies
				]

				for patch in patches:
								ax.add_patch(SCREAMING_SNAKE_CASE__  )

				# Function called at each step of the animation
				def update(SCREAMING_SNAKE_CASE__  ) -> list[plt.Circle]:
								update_step(SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__  )
								return patches

				_SCREAMING_SNAKE_CASE				: List[str]  	=   animation.FuncAnimation(  # noqa: F841
				    SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   interval=SCREAMING_SNAKE_CASE__							,   blit=SCREAMING_SNAKE_CASE__  )

				plt.show()







def     snake_case_     (						):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: Tuple  	=   0.9_7_0_0_4_3_6
				_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   -0.2_4_3_0_8_7_5_3
				_SCREAMING_SNAKE_CASE				: Tuple  	=   0.4_6_6_2_0_3_6_8_5
				_SCREAMING_SNAKE_CASE				: List[str]  	=   0.4_3_2_3_6_5_7_3

				_SCREAMING_SNAKE_CASE				: Any  	=   [
				    Body(SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   size=0.2							,   color="""red"""  ),
				    Body(-position_x							,   -position_y							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   size=0.2							,   color="""green"""  ),
				    Body(0							,   0							,   -2 * velocity_x							,   -2 * velocity_y							,   size=0.2							,   color="""blue"""  ),
				]
				return BodySystem(SCREAMING_SNAKE_CASE__							,   time_factor=3  )







def     snake_case_     (						):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: str  	=   7.34_76E22
				_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   5.9_72E24
				_SCREAMING_SNAKE_CASE				: Tuple  	=   1022
				_SCREAMING_SNAKE_CASE				: int  	=   3_8439_9000
				_SCREAMING_SNAKE_CASE				: Dict  	=   6.6_74E-11

				# Calculation of the respective velocities so that total impulse is zero,
				# i.e. the two bodies together don't move
				_SCREAMING_SNAKE_CASE				: int  	=   earth_mass * velocity_dif / (earth_mass + moon_mass)
				_SCREAMING_SNAKE_CASE				: int  	=   moon_velocity - velocity_dif

				_SCREAMING_SNAKE_CASE				: str  	=   Body(-earth_moon_distance							,   0							,   0							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   1000_0000							,   """grey"""  )
				_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   Body(0							,   0							,   0							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   5000_0000							,   """blue"""  )
				return BodySystem([earth, moon]							,   SCREAMING_SNAKE_CASE__							,   time_factor=100_0000  )







def     snake_case_     (						):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: Optional[int]  	=   []
				for _ in range(10  ):
								_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   random.uniform(-0.5							,   0.5  )
								_SCREAMING_SNAKE_CASE				: Tuple  	=   random.uniform(-0.5							,   0.5  )

								# Bodies are created pairwise with opposite velocities so that the
								# total impulse remains zero
								bodies.append(
								    Body(
								        random.uniform(-0.5							,   0.5  )							,   random.uniform(-0.5							,   0.5  )							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   size=0.0_5							,   )  )
								bodies.append(
								    Body(
								        random.uniform(-0.5							,   0.5  )							,   random.uniform(-0.5							,   0.5  )							,   -velocity_x							,   -velocity_y							,   size=0.0_5							,   )  )
				return BodySystem(SCREAMING_SNAKE_CASE__							,   0.0_1							,   10							,   0.1  )


if __name__ == "__main__":
				plot('Figure-8 solution to the 3-body-problem', example_a(), -2, 2, -2, 2)
				plot(
				    'Moon\'s orbit around the earth',
				    example_a(),
				    -4_3000_0000,
				    4_3000_0000,
				    -4_3000_0000,
				    4_3000_0000,
				)
				plot('Random system with many bodies', example_a(), -1.5, 1.5, -1.5, 1.5)








'''simple docstring'''


import argparse
import copy
import json
import multiprocessing
import os
import time

from create_dummy_models import COMPOSITE_MODELS, create_tiny_models
from huggingface_hub import ModelFilter, hf_api

import transformers
from transformers import AutoFeatureExtractor, AutoImageProcessor, AutoTokenizer
from transformers.image_processing_utils import BaseImageProcessor







def     snake_case_     (						):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: str  	=   set()
				# Each auto modeling files contains multiple mappings. Let's get them in a dynamic way.
				for module_name in ["modeling_auto", "modeling_tf_auto", "modeling_flax_auto"]:
								_SCREAMING_SNAKE_CASE				: Any  	=   getattr(transformers.models.auto							,   SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__  )
								if module is None:
												continue
								# all mappings in a single auto modeling file
								_SCREAMING_SNAKE_CASE				: str  	=   [
								    x
								    for x in dir(SCREAMING_SNAKE_CASE__  )
								    if x.endswith("""_MAPPING_NAMES"""  )
								    and (x.startswith("""MODEL_"""  ) or x.startswith("""TF_MODEL_"""  ) or x.startswith("""FLAX_MODEL_"""  ))
								]
								for name in mapping_names:
												_SCREAMING_SNAKE_CASE				: Optional[int]  	=   getattr(SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__  )
												if mapping is not None:
																for v in mapping.values():
																				if isinstance(SCREAMING_SNAKE_CASE__							,   (list, tuple)  ):
																								model_names.update(SCREAMING_SNAKE_CASE__  )
																				elif isinstance(SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__  ):
																								model_names.add(SCREAMING_SNAKE_CASE__  )

				return sorted(SCREAMING_SNAKE_CASE__  )







def     snake_case_     (						):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   set(get_all_model_names()  )

				with open("""tests/utils/tiny_model_summary.json"""  ) as fp:
								_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   json.load(SCREAMING_SNAKE_CASE__  )
				_SCREAMING_SNAKE_CASE				: str  	=   set()
				for model_base_name in tiny_model_info:
								tiny_models_names.update(tiny_model_info[model_base_name]["""model_classes"""]  )

				# Remove a tiny model name if one of its framework implementation hasn't yet a tiny version on the Hub.
				_SCREAMING_SNAKE_CASE				: str  	=   model_names.difference(SCREAMING_SNAKE_CASE__  )
				for model_name in copy.copy(SCREAMING_SNAKE_CASE__  ):
								if not model_name.startswith("""TF"""  ) and f"""TF{model_name}""" in not_on_hub:
												tiny_models_names.remove(SCREAMING_SNAKE_CASE__  )
								elif model_name.startswith("""TF"""  ) and model_name[2:] in not_on_hub:
												tiny_models_names.remove(SCREAMING_SNAKE_CASE__  )

				return sorted(SCREAMING_SNAKE_CASE__  )







def     snake_case_     (						SCREAMING_SNAKE_CASE__  ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: Optional[int]  	=   COMPOSITE_MODELS.values()

				# All tiny model base names on Hub
				_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   get_all_model_names()
				_SCREAMING_SNAKE_CASE				: Optional[int]  	=   hf_api.list_models(
				    filter=ModelFilter(
				        author="""hf-internal-testing"""							,   )  )
				_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   set()
				for x in models:
								_SCREAMING_SNAKE_CASE				: Tuple  	=   x.modelId
								_SCREAMING_SNAKE_CASE	, _SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   model.split("""/"""  )
								if not model.startswith("""tiny-random-"""  ):
												continue
								_SCREAMING_SNAKE_CASE				: List[Any]  	=   model.replace("""tiny-random-"""							,   """"""  )
								if not model[0].isupper():
												continue
								if model not in model_names and model not in special_models:
												continue
								_models.add(SCREAMING_SNAKE_CASE__  )

				_SCREAMING_SNAKE_CASE				: Optional[int]  	=   sorted(_models  )
				# All tiny model names on Hub
				_SCREAMING_SNAKE_CASE				: Dict  	=   {}
				for model in models:
								_SCREAMING_SNAKE_CASE				: str  	=   f"""hf-internal-testing/tiny-random-{model}"""
								_SCREAMING_SNAKE_CASE				: List[Any]  	=   model.split("""-"""  )[0]
								try:
												_SCREAMING_SNAKE_CASE				: Tuple  	=   hf_api.repo_info(SCREAMING_SNAKE_CASE__  )
												_SCREAMING_SNAKE_CASE				: Optional[int]  	=   {
												    """tokenizer_classes""": set(),
												    """processor_classes""": set(),
												    """model_classes""": set(),
												    """sha""": repo_info.sha,
												}
								except Exception:
												continue
								try:
												time.sleep(1  )
												_SCREAMING_SNAKE_CASE				: Optional[int]  	=   AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE__  )
												content["tokenizer_classes"].add(tokenizer_fast.__class__.__name__  )
								except Exception:
												pass
								try:
												time.sleep(1  )
												_SCREAMING_SNAKE_CASE				: int  	=   AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE__							,   use_fast=SCREAMING_SNAKE_CASE__  )
												content["tokenizer_classes"].add(tokenizer_slow.__class__.__name__  )
								except Exception:
												pass
								try:
												time.sleep(1  )
												_SCREAMING_SNAKE_CASE				: str  	=   AutoImageProcessor.from_pretrained(SCREAMING_SNAKE_CASE__  )
												content["processor_classes"].add(img_p.__class__.__name__  )
								except Exception:
												pass
								try:
												time.sleep(1  )
												_SCREAMING_SNAKE_CASE				: Any  	=   AutoFeatureExtractor.from_pretrained(SCREAMING_SNAKE_CASE__  )
												if not isinstance(SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__  ):
																content["processor_classes"].add(feat_p.__class__.__name__  )
								except Exception:
												pass
								try:
												time.sleep(1  )
												_SCREAMING_SNAKE_CASE				: int  	=   getattr(SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__  )
												_SCREAMING_SNAKE_CASE				: Tuple  	=   model_class.from_pretrained(SCREAMING_SNAKE_CASE__  )
												content["model_classes"].add(m.__class__.__name__  )
								except Exception:
												pass
								try:
												time.sleep(1  )
												_SCREAMING_SNAKE_CASE				: List[Any]  	=   getattr(SCREAMING_SNAKE_CASE__							,   f"""TF{model}"""  )
												_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   model_class.from_pretrained(SCREAMING_SNAKE_CASE__  )
												content["model_classes"].add(m.__class__.__name__  )
								except Exception:
												pass

								_SCREAMING_SNAKE_CASE				: List[Any]  	=   sorted(content["""tokenizer_classes"""]  )
								_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   sorted(content["""processor_classes"""]  )
								_SCREAMING_SNAKE_CASE				: List[Any]  	=   sorted(content["""model_classes"""]  )

								_SCREAMING_SNAKE_CASE				: List[Any]  	=   content
								with open(os.path.join(SCREAMING_SNAKE_CASE__							,   """hub_tiny_model_summary.json"""  )							,   """w"""  ) as fp:
												json.dump(SCREAMING_SNAKE_CASE__							,   SCREAMING_SNAKE_CASE__							,   ensure_ascii=SCREAMING_SNAKE_CASE__							,   indent=4  )


if __name__ == "__main__":
				UpperCAmelCase_	:     Any							     =	argparse.ArgumentParser()
				parser.add_argument('--num_workers', default=1, type=int, help='The number of workers to run.')
				UpperCAmelCase_	:     Optional[int]							     =	parser.parse_args()

				# This has to be `spawn` to avoid hanging forever!
				multiprocessing.set_start_method('spawn')

				UpperCAmelCase_	:     Any							     =	'tiny_models'
				UpperCAmelCase_	:     Tuple							     =	True
				UpperCAmelCase_	:     Tuple							     =	None
				UpperCAmelCase_	:     Optional[int]							     =	get_tiny_model_names_from_repo()
				UpperCAmelCase_	:     Dict							     =	True
				UpperCAmelCase_	:     str							     =	True
				UpperCAmelCase_	:     Optional[int]							     =	'hf-internal-testing'

				create_tiny_models(
				    output_path,
				    all,
				    model_types,
				    models_to_skip,
				    no_check,
				    upload,
				    organization,
				    token=os.environ.get('TOKEN', None),
				    num_workers=args.num_workers,
				)




