'''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 							lowerCamelCase			(   UpperCAmelCase__ :      Optional[int]				)    ->   Dict:
							lowercase_      :    List[str]       		= filter(lambda UpperCAmelCase__				: p.requires_grad   ,   model.parameters()				)
							lowercase_      :    Dict       		= sum([np.prod(p.size()				) for p in model_parameters]				)
							return params


_lowercase		:				Dict	       =		logging.getLogger(__name__)




def 							lowerCamelCase			(   UpperCAmelCase__ :      Any   ,   UpperCAmelCase__ :      Optional[Any]				)    ->   Union[str, Any]:
							if metric == "rouge2":
														lowercase_      :    Optional[int]       		= """{val_avg_rouge2:.4f}-{step_count}"""
							elif metric == "bleu":
														lowercase_      :    str       		= """{val_avg_bleu:.4f}-{step_count}"""
							elif metric == "em":
														lowercase_      :    List[Any]       		= """{val_avg_em:.4f}-{step_count}"""
							elif metric == "loss":
														lowercase_      :    List[str]       		= """{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."""				)

							lowercase_      :    Dict       		= ModelCheckpoint(
							    dirpath=UpperCAmelCase__   ,   filename=UpperCAmelCase__   ,   monitor=F'''val_{metric}'''   ,   mode="""max"""   ,   save_top_k=1   ,   every_n_epochs=1   ,   )

							return checkpoint_callback




def 							lowerCamelCase			(   UpperCAmelCase__ :      str   ,   UpperCAmelCase__ :      Optional[int]				)    ->   Tuple:
							return EarlyStopping(
							    monitor=F'''val_{metric}'''   ,   mode="""min""" if """loss""" in metric else """max"""   ,   patience=UpperCAmelCase__   ,   verbose=UpperCAmelCase__   ,   )





class 					__magic_name__		(					pl.Callback):







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Dict       ,    lowercase_       :						List[Any]       ,    lowercase_       :						List[str]					):
										lowercase_      :    str       		= {f'''lr_group_{i}''': param["""lr"""] for i, param in enumerate(pl_module.trainer.optimizers[0].param_groups					)}
										pl_module.logger.log_metrics(lowercase_					)







			@rank_zero_only
			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]       ,    lowercase_       :						pl.Trainer       ,    lowercase_       :						pl.LightningModule       ,    lowercase_       :						str       ,    lowercase_       :						Dict=True					):
										logger.info(f'''***** {type_path} results at step {trainer.global_step:05d} *****'''					)
										lowercase_      :    List[str]       		= 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
										lowercase_      :    Any       		= Path(pl_module.hparams.output_dir					)
										if type_path == "test":
																	lowercase_      :    List[Any]       		= od / """test_results.txt"""
																	lowercase_      :    List[Any]       		= 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.
																	lowercase_      :    Tuple       		= od / f'''{type_path}_results/{trainer.global_step:05d}.txt'''
																	lowercase_      :    str       		= od / f'''{type_path}_generations/{trainer.global_step:05d}.txt'''
																	results_file.parent.mkdir(exist_ok=lowercase_					)
																	generations_file.parent.mkdir(exist_ok=lowercase_					)
										with open(lowercase_       ,    """a+"""					) as writer:
																	for key in sorted(lowercase_					):
																								if key in ["log", "progress_bar", "preds"]:
																															continue
																								lowercase_      :    List[str]       		= metrics[key]
																								if isinstance(lowercase_       ,    torch.Tensor					):
																															lowercase_      :    Any       		= val.item()
																								lowercase_      :    Optional[int]       		= f'''{key}: {val:.6f}\n'''
																								writer.write(lowercase_					)

										if not save_generations:
																	return

										if "preds" in metrics:
																	lowercase_      :    List[str]       		= """\n""".join(metrics["""preds"""]					)
																	generations_file.open("""w+"""					).write(lowercase_					)







			@rank_zero_only
			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]       ,    lowercase_       :						str       ,    lowercase_       :						List[str]					):
										try:
																	lowercase_      :    List[Any]       		= pl_module.model.model.num_parameters()
										except AttributeError:
																	lowercase_      :    List[Any]       		= pl_module.model.num_parameters()

										lowercase_      :    Optional[Any]       		= count_trainable_parameters(lowercase_					)
										# 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 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple       ,    lowercase_       :						pl.Trainer       ,    lowercase_       :						pl.LightningModule					):
										save_json(pl_module.metrics       ,    pl_module.metrics_save_path					)
										return self._write_logs(lowercase_       ,    lowercase_       ,    """test"""					)







			@rank_zero_only
			def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple       ,    lowercase_       :						pl.Trainer       ,    lowercase_       :						int					):
										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'''




from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    str       		= tau * frequency / samplerate
							lowercase_      :    Tuple       		= sin(UpperCAmelCase__				)
							lowercase_      :    int       		= cos(UpperCAmelCase__				)
							lowercase_      :    Any       		= _sin / (2 * q_factor)

							lowercase_      :    Dict       		= (1 - _cos) / 2
							lowercase_      :    Optional[int]       		= 1 - _cos

							lowercase_      :    Dict       		= 1 + alpha
							lowercase_      :    List[Any]       		= -2 * _cos
							lowercase_      :    Union[str, Any]       		= 1 - alpha

							lowercase_      :    List[Any]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    str       		= tau * frequency / samplerate
							lowercase_      :    Optional[int]       		= sin(UpperCAmelCase__				)
							lowercase_      :    Dict       		= cos(UpperCAmelCase__				)
							lowercase_      :    Optional[int]       		= _sin / (2 * q_factor)

							lowercase_      :    Dict       		= (1 + _cos) / 2
							lowercase_      :    str       		= -1 - _cos

							lowercase_      :    Dict       		= 1 + alpha
							lowercase_      :    Optional[Any]       		= -2 * _cos
							lowercase_      :    List[Any]       		= 1 - alpha

							lowercase_      :    Union[str, Any]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    int       		= tau * frequency / samplerate
							lowercase_      :    int       		= sin(UpperCAmelCase__				)
							lowercase_      :    Union[str, Any]       		= cos(UpperCAmelCase__				)
							lowercase_      :    str       		= _sin / (2 * q_factor)

							lowercase_      :    str       		= _sin / 2
							lowercase_      :    Any       		= 0
							lowercase_      :    Optional[Any]       		= -ba

							lowercase_      :    Dict       		= 1 + alpha
							lowercase_      :    Union[str, Any]       		= -2 * _cos
							lowercase_      :    Union[str, Any]       		= 1 - alpha

							lowercase_      :    Tuple       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    List[str]       		= tau * frequency / samplerate
							lowercase_      :    Any       		= sin(UpperCAmelCase__				)
							lowercase_      :    List[Any]       		= cos(UpperCAmelCase__				)
							lowercase_      :    Optional[Any]       		= _sin / (2 * q_factor)

							lowercase_      :    Any       		= 1 - alpha
							lowercase_      :    Optional[Any]       		= -2 * _cos
							lowercase_      :    Optional[int]       		= 1 + alpha

							lowercase_      :    Dict       		= IIRFilter(2				)
							filt.set_coefficients([ba, ba, ba]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)   ,   )    ->   IIRFilter:
							lowercase_      :    Dict       		= tau * frequency / samplerate
							lowercase_      :    Tuple       		= sin(UpperCAmelCase__				)
							lowercase_      :    List[Any]       		= cos(UpperCAmelCase__				)
							lowercase_      :    List[Any]       		= _sin / (2 * q_factor)
							lowercase_      :    Any       		= 10 ** (gain_db / 40)

							lowercase_      :    List[str]       		= 1 + alpha * big_a
							lowercase_      :    List[Any]       		= -2 * _cos
							lowercase_      :    Dict       		= 1 - alpha * big_a
							lowercase_      :    str       		= 1 + alpha / big_a
							lowercase_      :    List[str]       		= -2 * _cos
							lowercase_      :    Tuple       		= 1 - alpha / big_a

							lowercase_      :    Any       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)   ,   )    ->   IIRFilter:
							lowercase_      :    Dict       		= tau * frequency / samplerate
							lowercase_      :    Union[str, Any]       		= sin(UpperCAmelCase__				)
							lowercase_      :    Any       		= cos(UpperCAmelCase__				)
							lowercase_      :    Any       		= _sin / (2 * q_factor)
							lowercase_      :    Any       		= 10 ** (gain_db / 40)
							lowercase_      :    Any       		= (big_a + 1) - (big_a - 1) * _cos
							lowercase_      :    int       		= (big_a + 1) + (big_a - 1) * _cos
							lowercase_      :    Tuple       		= (big_a - 1) - (big_a + 1) * _cos
							lowercase_      :    Optional[Any]       		= (big_a - 1) + (big_a + 1) * _cos
							lowercase_      :    int       		= 2 * sqrt(UpperCAmelCase__				) * alpha

							lowercase_      :    Tuple       		= big_a * (pmc + aaa)
							lowercase_      :    List[str]       		= 2 * big_a * mpc
							lowercase_      :    Union[str, Any]       		= big_a * (pmc - aaa)
							lowercase_      :    Optional[int]       		= ppmc + aaa
							lowercase_      :    Optional[int]       		= -2 * pmpc
							lowercase_      :    Any       		= ppmc - aaa

							lowercase_      :    Optional[int]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)   ,   )    ->   IIRFilter:
							lowercase_      :    str       		= tau * frequency / samplerate
							lowercase_      :    int       		= sin(UpperCAmelCase__				)
							lowercase_      :    int       		= cos(UpperCAmelCase__				)
							lowercase_      :    Dict       		= _sin / (2 * q_factor)
							lowercase_      :    Union[str, Any]       		= 10 ** (gain_db / 40)
							lowercase_      :    Union[str, Any]       		= (big_a + 1) - (big_a - 1) * _cos
							lowercase_      :    Optional[int]       		= (big_a + 1) + (big_a - 1) * _cos
							lowercase_      :    Any       		= (big_a - 1) - (big_a + 1) * _cos
							lowercase_      :    str       		= (big_a - 1) + (big_a + 1) * _cos
							lowercase_      :    Optional[int]       		= 2 * sqrt(UpperCAmelCase__				) * alpha

							lowercase_      :    Tuple       		= big_a * (ppmc + aaa)
							lowercase_      :    List[Any]       		= -2 * big_a * pmpc
							lowercase_      :    Optional[Any]       		= big_a * (ppmc - aaa)
							lowercase_      :    Optional[Any]       		= pmc + aaa
							lowercase_      :    int       		= 2 * mpc
							lowercase_      :    Tuple       		= pmc - aaa

							lowercase_      :    Union[str, Any]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt





