'''simple docstring'''




import argparse
import re
from typing import Dict

import torch
from datasets import Audio, Dataset, load_dataset, load_metric

from transformers import AutoFeatureExtractor, pipeline

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       Dict     				=					args.log_outputs
     lowercase_					:       Optional[int]     				=					'''_'''.join(args.dataset.split('/'							) + [args.config, args.split]							)

     # load metric
     lowercase_					:       Optional[Any]     				=					load_metric('wer'							)
     lowercase_					:       Union[str, Any]     				=					load_metric('cer'							)

     # compute metrics
     lowercase_					:       Union[str, Any]     				=					wer.compute(references=result['target']  ,       predictions=result['prediction']							)
     lowercase_					:       List[Any]     				=					cer.compute(references=result['target']  ,       predictions=result['prediction']							)

     # print & log results
     lowercase_					:       Optional[Any]     				=					f'''WER: {wer_result}\nCER: {cer_result}'''
     print(SCREAMING_SNAKE_CASE_							)

     with open(f'''{dataset_id}_eval_results.txt'''  ,       'w'							) as f:
          f.write(SCREAMING_SNAKE_CASE_							)

     # log all results in text file. Possibly interesting for analysis
     if log_outputs is not None:
          lowercase_					:       Optional[int]     				=					f'''log_{dataset_id}_predictions.txt'''
          lowercase_					:       Optional[int]     				=					f'''log_{dataset_id}_targets.txt'''

          with open(SCREAMING_SNAKE_CASE_  ,       'w'							) as p, open(SCREAMING_SNAKE_CASE_  ,       'w'							) as t:
               # mapping function to write output
               def write_to_file(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
                    p.write(f'''{i}''' + '\n'							)
                    p.write(batch['prediction'] + '\n'							)
                    t.write(f'''{i}''' + '\n'							)
                    t.write(batch['target'] + '\n'							)

               result.map(SCREAMING_SNAKE_CASE_  ,       with_indices=SCREAMING_SNAKE_CASE_							)

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       List[Any]     				=					'''[,?.!\-\;\:"“%‘”�—’…–]'''  # noqa: W605 IMPORTANT: this should correspond to the chars that were ignored during training

     lowercase_					:       Optional[Any]     				=					re.sub(SCREAMING_SNAKE_CASE_  ,       ''  ,       text.lower()							)

     # In addition, we can normalize the target text, e.g. removing new lines characters etc...
     # note that order is important here!
     lowercase_					:       List[str]     				=					['''\n\n''', '''\n''', '''   ''', '''  ''']

     for t in token_sequences_to_ignore:
          lowercase_					:       Optional[int]     				=					''' '''.join(text.split(SCREAMING_SNAKE_CASE_							)							)

     return text

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       Dict     				=					load_dataset(args.dataset  ,       args.config  ,       split=args.split  ,       use_auth_token=SCREAMING_SNAKE_CASE_							)

     # for testing: only process the first two examples as a test
     # dataset = dataset.select(range(10))

     # load processor
     lowercase_					:       int     				=					AutoFeatureExtractor.from_pretrained(args.model_id							)
     lowercase_					:       Optional[Any]     				=					feature_extractor.sampling_rate

     # resample audio
     lowercase_					:       Tuple     				=					dataset.cast_column('audio'  ,       Audio(sampling_rate=SCREAMING_SNAKE_CASE_							)							)

     # load eval pipeline
     if args.device is None:
          lowercase_					:       Union[str, Any]     				=					0 if torch.cuda.is_available() else -1
     lowercase_					:       Optional[int]     				=					pipeline('automatic-speech-recognition'  ,       model=args.model_id  ,       device=args.device							)

     # map function to decode audio
     def map_to_pred(SCREAMING_SNAKE_CASE_							):
          lowercase_					:       List[str]     				=					asr(
              batch['audio']['array']  ,       chunk_length_s=args.chunk_length_s  ,       stride_length_s=args.stride_length_s							)

          lowercase_					:       List[Any]     				=					prediction['''text''']
          lowercase_					:       List[Any]     				=					normalize_text(batch['sentence']							)
          return batch

     # run inference on all examples
     lowercase_					:       str     				=					dataset.map(SCREAMING_SNAKE_CASE_  ,       remove_columns=dataset.column_names							)

     # compute and log_results
     # do not change function below
     log_results(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							)


if __name__ == "__main__":
 _A     :   Any								=   argparse.ArgumentParser()

 parser.add_argument(
     '--model_id', type=str, required=True, help='Model identifier. Should be loadable with 🤗 Transformers'
 )
 parser.add_argument(
     '--dataset',
     type=str,
     required=True,
     help='Dataset name to evaluate the `model_id`. Should be loadable with 🤗 Datasets',
 )
 parser.add_argument(
     '--config', type=str, required=True, help='Config of the dataset. *E.g.* `\'en\'`  for Common Voice'
 )
 parser.add_argument('--split', type=str, required=True, help='Split of the dataset. *E.g.* `\'test\'`')
 parser.add_argument(
     '--chunk_length_s', type=float, default=None, help='Chunk length in seconds. Defaults to 5 seconds.'
 )
 parser.add_argument(
     '--stride_length_s', type=float, default=None, help='Stride of the audio chunks. Defaults to 1 second.'
 )
 parser.add_argument(
     '--log_outputs', action='store_true', help='If defined, write outputs to log file for analysis.'
 )
 parser.add_argument(
     '--device',
     type=int,
     default=None,
     help='The device to run the pipeline on. -1 for CPU (default), 0 for the first GPU and so on.',
 )
 _A     :   Any								=   parser.parse_args()

 main(args)





'''simple docstring'''




import os
import string
import sys


_A								=   1 << 8

_A								=   {
    'tab': ord('\t'),
    'newline': ord('\r'),
    'esc': 2_7,
    'up': 6_5 + ARROW_KEY_FLAG,
    'down': 6_6 + ARROW_KEY_FLAG,
    'right': 6_7 + ARROW_KEY_FLAG,
    'left': 6_8 + ARROW_KEY_FLAG,
    'mod_int': 9_1,
    'undefined': sys.maxsize,
    'interrupt': 3,
    'insert': 5_0,
    'delete': 5_1,
    'pg_up': 5_3,
    'pg_down': 5_4,
}

_A								=   KEYMAP['up']
_A								=   KEYMAP['left']

if sys.platform == "win32":
 _A								=   []
 _A								=   {
     b'\xe0H': KEYMAP['up'] - ARROW_KEY_FLAG,
     b'\x00H': KEYMAP['up'] - ARROW_KEY_FLAG,
     b'\xe0P': KEYMAP['down'] - ARROW_KEY_FLAG,
     b'\x00P': KEYMAP['down'] - ARROW_KEY_FLAG,
     b'\xe0M': KEYMAP['right'] - ARROW_KEY_FLAG,
     b'\x00M': KEYMAP['right'] - ARROW_KEY_FLAG,
     b'\xe0K': KEYMAP['left'] - ARROW_KEY_FLAG,
     b'\x00K': KEYMAP['left'] - ARROW_KEY_FLAG,
 }

for i in range(1_0):
 _A								=   ord(str(i))

def _UpperCamelCase   (       ):
     if os.name == "nt":
          import msvcrt

          lowercase_					:       Optional[Any]     				=					'mbcs'
          # Flush the keyboard buffer
          while msvcrt.kbhit():
               msvcrt.getch()
          if len(SCREAMING_SNAKE_CASE_							) == 0:
               # Read the keystroke
               lowercase_					:       int     				=					msvcrt.getch()

               # If it is a prefix char, get second part
               if ch in (b"\x00", b"\xe0"):
                    lowercase_					:       int     				=					ch + msvcrt.getch()
                    # Translate actual Win chars to bullet char types
                    try:
                         lowercase_					:       List[Any]     				=					chr(WIN_KEYMAP[cha]							)
                         WIN_CH_BUFFER.append(chr(KEYMAP['mod_int']							)							)
                         WIN_CH_BUFFER.append(SCREAMING_SNAKE_CASE_							)
                         if ord(SCREAMING_SNAKE_CASE_							) in (
                             KEYMAP["insert"] - 1 << 9,
                             KEYMAP["delete"] - 1 << 9,
                             KEYMAP["pg_up"] - 1 << 9,
                             KEYMAP["pg_down"] - 1 << 9,
                         ):
                              WIN_CH_BUFFER.append(chr(126							)							)
                         lowercase_					:       Optional[int]     				=					chr(KEYMAP['esc']							)
                    except KeyError:
                         lowercase_					:       Tuple     				=					cha[1]
               else:
                    lowercase_					:       Tuple     				=					ch.decode(SCREAMING_SNAKE_CASE_							)
          else:
               lowercase_					:       Dict     				=					WIN_CH_BUFFER.pop(0							)
     elif os.name == "posix":
          import termios
          import tty

          lowercase_					:       int     				=					sys.stdin.fileno()
          lowercase_					:       Union[str, Any]     				=					termios.tcgetattr(SCREAMING_SNAKE_CASE_							)
          try:
               tty.setraw(SCREAMING_SNAKE_CASE_							)
               lowercase_					:       Any     				=					sys.stdin.read(1							)
          finally:
               termios.tcsetattr(SCREAMING_SNAKE_CASE_  ,       termios.TCSADRAIN  ,       SCREAMING_SNAKE_CASE_							)
     return ch






def _UpperCamelCase   (       ):
     lowercase_					:       Union[str, Any]     				=					get_raw_chars()
     if ord(SCREAMING_SNAKE_CASE_							) in [KEYMAP["interrupt"], KEYMAP["newline"]]:
          return char

     elif ord(SCREAMING_SNAKE_CASE_							) == KEYMAP["esc"]:
          lowercase_					:       Any     				=					get_raw_chars()
          if ord(SCREAMING_SNAKE_CASE_							) == KEYMAP["mod_int"]:
               lowercase_					:       Dict     				=					get_raw_chars()
               if ord(SCREAMING_SNAKE_CASE_							) >= KEYMAP["arrow_begin"] - ARROW_KEY_FLAG and ord(SCREAMING_SNAKE_CASE_							) <= KEYMAP["arrow_end"] - ARROW_KEY_FLAG:
                    return chr(ord(SCREAMING_SNAKE_CASE_							) + ARROW_KEY_FLAG							)
               else:
                    return KEYMAP["undefined"]
          else:
               return get_raw_chars()

     else:
          if char in string.printable:
               return char
          else:
               return KEYMAP["undefined"]




