






"""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 import save_json



def    lowerCAmelCase							(       __UpperCamelCase					):




  """simple docstring"""







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


lowercase_								=	logging.getLogger(__name__)


class    snake_case						(				pl.Callback		):


   '''simple docstring'''

   def 							_SCREAMING_SNAKE_CASE							(      self					:	str,			_lowerCamelCase					:	Any,			_lowerCamelCase					:	Union[str, Any]    ):

     '''simple docstring'''
     __A		     =					{f'lr_group_{i}': param['''lr'''] for i, param in enumerate(pl_module.trainer.optimizers[0].param_groups    )}
     pl_module.logger.log_metrics(_lowerCamelCase    )


   @rank_zero_only
   def 							_SCREAMING_SNAKE_CASE							(      self					:	Optional[int],			_lowerCamelCase					:	pl.Trainer,			_lowerCamelCase					:	pl.LightningModule,			_lowerCamelCase					:	str,			_lowerCamelCase					:	Dict=True    ):

     '''simple docstring'''
     logger.info(f'***** {type_path} results at step {trainer.global_step:05d} *****'    )
     __A		     =					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
     __A		     =					Path(pl_module.hparams.output_dir    )
     if type_path == "test":
       __A		     =					od / '''test_results.txt'''
       __A		     =					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.
       __A		     =					od / f'{type_path}_results/{trainer.global_step:05d}.txt'
       __A		     =					od / f'{type_path}_generations/{trainer.global_step:05d}.txt'
       results_file.parent.mkdir(exist_ok=_lowerCamelCase    )
       generations_file.parent.mkdir(exist_ok=_lowerCamelCase    )
     with open(_lowerCamelCase,			'''a+'''    ) as writer:
       for key in sorted(_lowerCamelCase    ):
         if key in ["log", "progress_bar", "preds"]:
           continue
         __A		     =					metrics[key]
         if isinstance(_lowerCamelCase,			torch.Tensor    ):
           __A		     =					val.item()
         __A		     =					f'{key}: {val:.6f}\n'
         writer.write(_lowerCamelCase    )

     if not save_generations:
       return

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


   @rank_zero_only
   def 							_SCREAMING_SNAKE_CASE							(      self					:	Tuple,			_lowerCamelCase					:	Union[str, Any],			_lowerCamelCase					:	Union[str, Any]    ):

     '''simple docstring'''
     try:
       __A		     =					pl_module.model.model.num_parameters()
     except AttributeError:
       __A		     =					pl_module.model.num_parameters()

     __A		     =					count_trainable_parameters(_lowerCamelCase    )
     # 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					:	Any,			_lowerCamelCase					:	pl.Trainer,			_lowerCamelCase					:	pl.LightningModule    ):

     '''simple docstring'''
     save_json(pl_module.metrics,			pl_module.metrics_save_path    )
     return self._write_logs(_lowerCamelCase,			_lowerCamelCase,			'''test'''    )






   @rank_zero_only
   def 							_SCREAMING_SNAKE_CASE							(      self					:	str,			_lowerCamelCase					:	pl.Trainer,			_lowerCamelCase					:	str    ):

     '''simple docstring'''
     save_json(pl_module.metrics,			pl_module.metrics_save_path    )
     # Uncommenting this will save val generations
     # return self._write_logs(trainer, pl_module, "valid")





def    lowerCAmelCase							(       __UpperCamelCase						,			__UpperCamelCase						,			__UpperCamelCase=1						,			__UpperCamelCase=False					):




  """simple docstring"""







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

  __A		     =					ModelCheckpoint(
      dirpath=__UpperCamelCase						,			filename=__UpperCamelCase						,			monitor=f'val_{metric}'						,			mode='''min''' if '''loss''' in metric else '''max'''						,			save_top_k=__UpperCamelCase						,			)
  return checkpoint_callback





def    lowerCAmelCase							(       __UpperCamelCase						,			__UpperCamelCase					):




  """simple docstring"""







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





def  __lowerCamelCase						(		lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__      ):
       if hue < 0 or hue > 3_6_0:
              raise Exception('hue should be between 0 and 360'      )

       if saturation < 0 or saturation > 1:
              raise Exception('saturation should be between 0 and 1'      )

       if value < 0 or value > 1:
              raise Exception('value should be between 0 and 1'      )

       lowerCAmelCase__	      =   value * saturation
       lowerCAmelCase__	      =   hue / 6_0
       lowerCAmelCase__	      =   chroma * (1 - abs(hue_section % 2 - 1      ))
       lowerCAmelCase__	      =   value - chroma

       if hue_section >= 0 and hue_section <= 1:
              lowerCAmelCase__	      =   round(2_5_5 * (chroma + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (second_largest_component + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (match_value)      )
       elif hue_section > 1 and hue_section <= 2:
              lowerCAmelCase__	      =   round(2_5_5 * (second_largest_component + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (chroma + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (match_value)      )
       elif hue_section > 2 and hue_section <= 3:
              lowerCAmelCase__	      =   round(2_5_5 * (match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (chroma + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (second_largest_component + match_value)      )
       elif hue_section > 3 and hue_section <= 4:
              lowerCAmelCase__	      =   round(2_5_5 * (match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (second_largest_component + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (chroma + match_value)      )
       elif hue_section > 4 and hue_section <= 5:
              lowerCAmelCase__	      =   round(2_5_5 * (second_largest_component + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (chroma + match_value)      )
       else:
              lowerCAmelCase__	      =   round(2_5_5 * (chroma + match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (match_value)      )
              lowerCAmelCase__	      =   round(2_5_5 * (second_largest_component + match_value)      )

       return [red, green, blue]






def  __lowerCamelCase						(		lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__      ):
       if red < 0 or red > 2_5_5:
              raise Exception('red should be between 0 and 255'      )

       if green < 0 or green > 2_5_5:
              raise Exception('green should be between 0 and 255'      )

       if blue < 0 or blue > 2_5_5:
              raise Exception('blue should be between 0 and 255'      )

       lowerCAmelCase__	      =   red / 2_5_5
       lowerCAmelCase__	      =   green / 2_5_5
       lowerCAmelCase__	      =   blue / 2_5_5
       lowerCAmelCase__	      =   max(lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__      )
       lowerCAmelCase__	      =   value - min(lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__      )
       lowerCAmelCase__	      =   0 if value == 0 else chroma / value

       if chroma == 0:
              lowerCAmelCase__	      =   0.0
       elif value == float_red:
              lowerCAmelCase__	      =   6_0 * (0 + (float_green - float_blue) / chroma)
       elif value == float_green:
              lowerCAmelCase__	      =   6_0 * (2 + (float_blue - float_red) / chroma)
       else:
              lowerCAmelCase__	      =   6_0 * (4 + (float_red - float_green) / chroma)

       lowerCAmelCase__	      =   (hue + 3_6_0) % 3_6_0

       return [hue, saturation, value]






def  __lowerCamelCase						(		lowerCAmelCase__      ,    lowerCAmelCase__      ):
       lowerCAmelCase__	      =   abs(hsv_a[0] - hsv_a[0]      ) < 0.2
       lowerCAmelCase__	      =   abs(hsv_a[1] - hsv_a[1]      ) < 0.0_0_2
       lowerCAmelCase__	      =   abs(hsv_a[2] - hsv_a[2]      ) < 0.0_0_2

       return check_hue and check_saturation and check_value
