






import os
import sys
from pathlib import Path

import torch

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, require_torch_multi_gpu
from utils import load_json


a 			=							torch.cuda.is_available()
a 			=							[' Sam ate lunch today.', 'Sams lunch ingredients.']
a 			=							['A very interesting story about what I ate for lunch.', 'Avocado, celery, turkey, coffee']
a 			=							{
    'max_tokens_per_batch': None,
    'supervise_forward': True,
    'normalize_hidden': True,
    'label_smoothing': 0.2,
    'eval_max_gen_length': None,
    'eval_beams': 1,
    'val_metric': 'loss',
    'save_top_k': 1,
    'adafactor': True,
    'early_stopping_patience': 2,
    'logger_name': 'default',
    'length_penalty': 0.5,
    'cache_dir': '',
    'task': 'summarization',
    'num_workers': 2,
    'alpha_hid': 0,
    'freeze_embeds': True,
    'enc_only': False,
    'tgt_suffix': '',
    'resume_from_checkpoint': None,
    'sortish_sampler': True,
    'student_decoder_layers': 1,
    'val_check_interval': 1.0,
    'output_dir': '',
    'fp16': False,  # TODO(SS): set this to CUDA_AVAILABLE if ci installs apex or start using native amp
    'no_teacher': False,
    'fp16_opt_level': 'O1',
    'gpus': 1 if CUDA_AVAILABLE else 0,
    'n_tpu_cores': 0,
    'max_grad_norm': 1.0,
    'do_train': True,
    'do_predict': True,
    'accumulate_grad_batches': 1,
    'server_ip': '',
    'server_port': '',
    'seed': 42,
    'model_name_or_path': 'sshleifer/bart-tiny-random',
    'config_name': '',
    'tokenizer_name': 'facebook/bart-large',
    'do_lower_case': False,
    'learning_rate': 0.3,
    'lr_scheduler': 'linear',
    'weight_decay': 0.0,
    'adam_epsilon': 1e-08,
    'warmup_steps': 0,
    'max_epochs': 1,
    'train_batch_size': 2,
    'eval_batch_size': 2,
    'max_source_length': 12,
    'max_target_length': 12,
    'val_max_target_length': 12,
    'test_max_target_length': 12,
    'fast_dev_run': False,
    'no_cache': False,
    'n_train': -1,
    'n_val': -1,
    'n_test': -1,
    'student_encoder_layers': 1,
    'freeze_encoder': False,
    'auto_scale_batch_size': False,
    'overwrite_output_dir': False,
    'student': None,
}
def    a__    (	A		,					A       ):
   lowercase__    :						int       =			'''\n'''.join(A       )
   Path(A       ).open("""w"""       ).writelines(A       )
def    a__    (	A       ):





   for split in ["train", "val", "test"]:
      _dump_articles(os.path.join(A		,					F'''{split}.source'''       )		,					A       )
      _dump_articles(os.path.join(A		,					F'''{split}.target'''       )		,					A       )
   return tmp_dir






class 							__snake_case(       __UpperCamelCase   ):



 @classmethod
 def     UpperCAmelCase     (						cls : str						):

    """simple docstring"""






    return cls



 @require_torch_multi_gpu
 def     UpperCAmelCase     (						self : Optional[int]						):

    """simple docstring"""






    lowercase__    :						Any       =			{
        '''no_teacher''': True,
        '''freeze_encoder''': True,
        '''gpus''': 2,
        '''overwrite_output_dir''': True,
        '''sortish_sampler''': True,
    }
    self._test_distiller_cli_fork(UpperCAmelCase__			,		check_contents=UpperCAmelCase__						)







 def     UpperCAmelCase     (						self : Union[str, Any]			,		UpperCAmelCase__ : Tuple			,		UpperCAmelCase__ : Tuple=True						):

    """simple docstring"""






    lowercase__    :						Dict       =			{
        '''label_smoothing''': 0.0,
        '''early_stopping_patience''': -1,
        '''train_batch_size''': 1,
        '''eval_batch_size''': 2,
        '''max_epochs''': 2,
        '''alpha_mlm''': 0.2,
        '''alpha_ce''': 0.8,
        '''do_predict''': True,
        '''model_name_or_path''': '''sshleifer/tinier_bart''',
        '''teacher''': CHEAP_ARGS['''model_name_or_path'''],
        '''val_check_interval''': 0.5,
    }
    default_updates.update(UpperCAmelCase__						)
    lowercase__    :						dict       =			CHEAP_ARGS.copy()
    lowercase__    :						str       =			make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()						)
    lowercase__    :						Any       =			self.get_auto_remove_tmp_dir()
    args_d.update(data_dir=UpperCAmelCase__			,		output_dir=UpperCAmelCase__			,		**UpperCAmelCase__						)

    def convert(UpperCAmelCase__ : Any			,		UpperCAmelCase__ : Dict						):
       if k in ["tgt_suffix", "server_ip", "server_port", "out", "n_tpu_cores"]:
          return ""
       if v is False or v is None:
          return ""
       if v is True:  # or len(str(v))==0:
          return f'''--{k}'''
       return f'''--{k}={v}'''

    lowercase__    :						Optional[int]       =			[x for x in (convert(UpperCAmelCase__			,		UpperCAmelCase__						) for k, v in args_d.items()) if len(UpperCAmelCase__						)]
    lowercase__    :						List[Any]       =			[sys.executable, f'''{self.test_file_dir}/distillation.py'''] + cli_args
    execute_subprocess_async(UpperCAmelCase__			,		env=self.get_env()						)

    lowercase__    :						List[Any]       =			os.listdir(UpperCAmelCase__						)
    lowercase__    :						Dict       =			{os.path.basename(UpperCAmelCase__						) for p in contents}
    lowercase__    :						List[Any]       =			[p for p in contents if p.endswith("""ckpt"""						)]
    assert len(UpperCAmelCase__						) > 0

    self.assertIn("""test_generations.txt"""			,		UpperCAmelCase__						)
    self.assertIn("""test_results.txt"""			,		UpperCAmelCase__						)

    # get the following from the module, (we don't have access to `model` here)
    lowercase__    :						List[Any]       =			os.path.join(UpperCAmelCase__			,		"""metrics.json"""						)
    lowercase__    :						str       =			'''rouge2'''

    lowercase__    :						str       =			load_json(UpperCAmelCase__						)
    # {'test': [{'test_avg_loss': 10.63731575012207, 'test_avg_rouge1': 0.0, 'test_avg_rouge2': 0.0, 'test_avg_rougeL': 0.0, 'test_avg_gen_time': 0.1822289228439331, 'test_avg_gen_len': 142.0, 'step_count': 1}]}
    print(UpperCAmelCase__						)
    lowercase__    :						Tuple       =			metrics['''val'''][-1]
    self.assertGreaterEqual(last_step_stats["""val_avg_gen_time"""]			,		0.01						)
    self.assertIsInstance(last_step_stats[f'''val_avg_{val_metric}''']			,		UpperCAmelCase__						)
    self.assertEqual(len(metrics["""test"""]						)			,		1						)
    lowercase__    :						Dict       =			int(args_d["""max_epochs"""] * (1 / args_d["""val_check_interval"""]) / 2 + 1						)
    self.assertEqual(len(metrics["""val"""]						)			,		UpperCAmelCase__						)










from math import radians as angle_to_radians
from math import sin

# Acceleration Constant on Earth (unit m/s^2)
__lowerCamelCase						= 9.8_06_65






def    UpperCamelCase__  (   UpperCAmelCase    ,	UpperCAmelCase     )     ->		None:







							"""simple docstring"""





							if not isinstance(UpperCAmelCase    ,	(int, float)     ):
														raise TypeError('''Invalid velocity. Should be a positive number.'''     )

							if not isinstance(UpperCAmelCase    ,	(int, float)     ):
														raise TypeError('''Invalid angle. Range is 1-90 degrees.'''     )

							# Ensure valid angle
							if angle > 90 or angle < 1:
														raise ValueError('''Invalid angle. Range is 1-90 degrees.'''     )

							# Ensure valid velocity
							if init_velocity < 0:
														raise ValueError('''Invalid velocity. Should be a positive number.'''     )






def    UpperCamelCase__  (   UpperCAmelCase    ,	UpperCAmelCase     )     ->		float:







							"""simple docstring"""





							check_args(UpperCAmelCase    ,	UpperCAmelCase     )
							_a  :    Dict			=						angle_to_radians(2 * angle     )
							return round(init_velocity**2 * sin(UpperCAmelCase     ) / g    ,	2     )






def    UpperCamelCase__  (   UpperCAmelCase    ,	UpperCAmelCase     )     ->		float:







							"""simple docstring"""





							check_args(UpperCAmelCase    ,	UpperCAmelCase     )
							_a  :    Union[str, Any]			=						angle_to_radians(UpperCAmelCase     )
							return round(init_velocity**2 * sin(UpperCAmelCase     ) ** 2 / (2 * g)    ,	2     )






def    UpperCamelCase__  (   UpperCAmelCase    ,	UpperCAmelCase     )     ->		float:







							"""simple docstring"""





							check_args(UpperCAmelCase    ,	UpperCAmelCase     )
							_a  :    str			=						angle_to_radians(UpperCAmelCase     )
							return round(2 * init_velocity * sin(UpperCAmelCase     ) / g    ,	2     )






def    UpperCamelCase__  (   )     ->		None:







							"""simple docstring"""





							_a		,					_a  :    Any			=						25, 20
							assert horizontal_distance(UpperCAmelCase    ,	UpperCAmelCase     ) == 4_0.9_7
							assert max_height(UpperCAmelCase    ,	UpperCAmelCase     ) == 3.7_3
							assert total_time(UpperCAmelCase    ,	UpperCAmelCase     ) == 1.7_4


if __name__ == "__main__":
						from doctest import testmod

						testmod()

						# Get input from user
						__lowerCamelCase						= float(input('Initial Velocity: ').strip())

						# Get input from user
						__lowerCamelCase						= float(input('angle: ').strip())

						# Print results
						print()
						print('Results: ')
						print(F'''Horizontal Distance: {horizontal_distance(init_vel, angle)!s} [m]''')
						print(F'''Maximum Height: {max_height(init_vel, angle)!s} [m]''')
						print(F'''Total Time: {total_time(init_vel, angle)!s} [s]''')