'''simple docstring'''

import logging
from pathlib import Path

import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json



def 							UpperCamelCase__			(			a__      ):


						'''simple docstring'''






						_lowerCAmelCase										=filter(lambda a__      : p.requires_grad			,      model.parameters()      )
						_lowerCAmelCase										=sum([np.prod(p.size()      ) for p in model_parameters]      )
						return params


lowercase_     		= logging.getLogger(__name__)



def 							UpperCamelCase__			(			a__			,      a__      ):


						'''simple docstring'''






						if metric == "rouge2":
												_lowerCAmelCase										='{val_avg_rouge2:.4f}-{step_count}'
						elif metric == "bleu":
												_lowerCAmelCase										='{val_avg_bleu:.4f}-{step_count}'
						elif metric == "em":
												_lowerCAmelCase										='{val_avg_em:.4f}-{step_count}'
						elif metric == "loss":
												_lowerCAmelCase										='{val_avg_loss:.4f}-{step_count}'
						else:
												raise NotImplementedError(
												    F'''seq2seq callbacks only support rouge2 and bleu, got {metric}, You can make your own by adding to this'''
												    ' function.'      )

						_lowerCAmelCase										=ModelCheckpoint(
						    dirpath=a__			,      filename=a__			,      monitor=F'''val_{metric}'''			,      mode='max'			,      save_top_k=1			,      every_n_epochs=1			,      )

						return checkpoint_callback



def 							UpperCamelCase__			(			a__			,      a__      ):


						'''simple docstring'''






						return EarlyStopping(
						    monitor=F'''val_{metric}'''			,      mode='min' if 'loss' in metric else 'max'			,      patience=a__			,      verbose=a__			,      )


class   SCREAMING_SNAKE_CASE			(						pl.Callback):







		"""simple docstring"""






		def 		UpperCamelCase__       (   self		,						__A		,						__A				) ->     Any:
								_lowerCAmelCase										={F'''lr_group_{i}''': param['lr'] for i, param in enumerate(pl_module.trainer.optimizers[0].param_groups				)}
								pl_module.logger.log_metrics(__A				)






		@rank_zero_only
		def 		UpperCamelCase__       (   self		,						__A		,						__A		,						__A		,						__A=True				) ->     None:
								logger.info(F'''***** {type_path} results at step {trainer.global_step:05d} *****'''				)
								_lowerCAmelCase										=trainer.callback_metrics
								trainer.logger.log_metrics({k: v for k, v in metrics.items() if k not in ['log', 'progress_bar', 'preds']}				)
								# Log results
								_lowerCAmelCase										=Path(pl_module.hparams.output_dir				)
								if type_path == "test":
														_lowerCAmelCase										=od / 'test_results.txt'
														_lowerCAmelCase										=od / 'test_generations.txt'
								else:
														# this never gets hit. I prefer not to save intermediate generations, and results are in metrics.json
														# If people want this it will be easy enough to add back.
														_lowerCAmelCase										=od / F'''{type_path}_results/{trainer.global_step:05d}.txt'''
														_lowerCAmelCase										=od / F'''{type_path}_generations/{trainer.global_step:05d}.txt'''
														results_file.parent.mkdir(exist_ok=__A				)
														generations_file.parent.mkdir(exist_ok=__A				)
								with open(__A		,						'a+'				) as writer:
														for key in sorted(__A				):
																				if key in ["log", "progress_bar", "preds"]:
																										continue
																				_lowerCAmelCase										=metrics[key]
																				if isinstance(__A		,						torch.Tensor				):
																										_lowerCAmelCase										=val.item()
																				_lowerCAmelCase										=F'''{key}: {val:.6f}\n'''
																				writer.write(__A				)

								if not save_generations:
														return

								if "preds" in metrics:
														_lowerCAmelCase										='\n'.join(metrics['preds']				)
														generations_file.open('w+'				).write(__A				)






		@rank_zero_only
		def 		UpperCamelCase__       (   self		,						__A		,						__A				) ->     Dict:
								try:
														_lowerCAmelCase										=pl_module.model.model.num_parameters()
								except AttributeError:
														_lowerCAmelCase										=pl_module.model.num_parameters()

								_lowerCAmelCase										=count_trainable_parameters(__A				)
								# mp stands for million parameters
								trainer.logger.log_metrics({'n_params': npars, 'mp': npars / 1E6, 'grad_mp': n_trainable_pars / 1E6}				)






		@rank_zero_only
		def 		UpperCamelCase__       (   self		,						__A		,						__A				) ->     Optional[int]:
								save_json(pl_module.metrics		,						pl_module.metrics_save_path				)
								return self._write_logs(__A		,						__A		,						'test'				)






		@rank_zero_only
		def 		UpperCamelCase__       (   self		,						__A		,						__A				) ->     Optional[Any]:
								save_json(pl_module.metrics		,						pl_module.metrics_save_path				)
								# Uncommenting this will save val generations
								# return self._write_logs(trainer, pl_module, "valid")






'''simple docstring'''

lowercase_     		= {
    '''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
    '''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',
    '''O''': '''---''', '''P''': '''.--.''', '''Q''': '''--.-''', '''R''': '''.-.''', '''S''': '''...''', '''T''': '''-''', '''U''': '''..-''',
    '''V''': '''...-''', '''W''': '''.--''', '''X''': '''-..-''', '''Y''': '''-.--''', '''Z''': '''--..''', '''1''': '''.----''',
    '''2''': '''..---''', '''3''': '''...--''', '''4''': '''....-''', '''5''': '''.....''', '''6''': '''-....''', '''7''': '''--...''',
    '''8''': '''---..''', '''9''': '''----.''', '''0''': '''-----''', '''&''': '''.-...''', '''@''': '''.--.-.''',
    ''':''': '''---...''', ''',''': '''--..--''', '''.''': '''.-.-.-''', '''\'''': '''.----.''', '''"''': '''.-..-.''',
    '''?''': '''..--..''', '''/''': '''-..-.''', '''=''': '''-...-''', '''+''': '''.-.-.''', '''-''': '''-....-''',
    '''(''': '''-.--.''', ''')''': '''-.--.-''', '''!''': '''-.-.--''', ''' ''': '''/'''
}  # Exclamation mark is not in ITU-R recommendation
# fmt: on
lowercase_     		= {value: key for key, value in MORSE_CODE_DICT.items()}



def 							UpperCamelCase__			(			a__      ):


						'''simple docstring'''






						return " ".join(MORSE_CODE_DICT[char] for char in message.upper()      )



def 							UpperCamelCase__			(			a__      ):


						'''simple docstring'''






						return "".join(REVERSE_DICT[char] for char in message.split()      )



def 							UpperCamelCase__			(			):


						'''simple docstring'''






						_lowerCAmelCase										='Morse code here!'
						print(a__      )
						_lowerCAmelCase										=encrypt(a__      )
						print(a__      )
						_lowerCAmelCase										=decrypt(a__      )
						print(a__      )


if __name__ == "__main__":
							main()





