



"""simple docstring"""
import argparse
import os
import re


A:   List[Any]								=		"src/transformers"

# Pattern that looks at the indentation in a line.
A:   List[str]								=		re.compile(R"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
A:   str								=		re.compile(R"^\s*\"([^\"]+)\":")
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
A:   Tuple								=		re.compile(R"^\s*_import_structure\[\"([^\"]+)\"\]")
# Pattern that matches `"key",` and puts `key` in group 0.
A:   Optional[Any]								=		re.compile(R"^\s*\"([^\"]+)\",\s*$")
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
A:   str								=		re.compile(R"\[([^\]]+)\]")

def       _snake_case						(						UpperCamelCase						:		Optional[int]						):
 UpperCAmelCase	:					int	=	_re_indent.search(UpperCamelCase						)
 return "" if search is None else search.groups()[0]

def       _snake_case						(						UpperCamelCase						:		Optional[int]			,		UpperCamelCase						:		str=""			,		UpperCamelCase						:		List[Any]=None			,		UpperCamelCase						:		Optional[Any]=None						):
 UpperCAmelCase	:					Any	=	0
 UpperCAmelCase	:					int	=	code.split("""\n"""						)
 if start_prompt is not None:
  while not lines[index].startswith(UpperCamelCase						):
   index += 1
  UpperCAmelCase	:					Tuple	=	["""\n""".join(lines[:index]						)]
 else:
  UpperCAmelCase	:					Any	=	[]

 # We split into blocks until we get to the `end_prompt` (or the end of the block).
 UpperCAmelCase	:					Dict	=	[lines[index]]
 index += 1
 while index < len(UpperCamelCase						) and (end_prompt is None or not lines[index].startswith(UpperCamelCase						)):
  if len(lines[index]						) > 0 and get_indent(lines[index]						) == indent_level:
   if len(UpperCamelCase						) > 0 and get_indent(current_block[-1]						).startswith(indent_level + """ """						):
    current_block.append(lines[index]						)
    blocks.append("""\n""".join(UpperCamelCase						)						)
    if index < len(UpperCamelCase						) - 1:
     UpperCAmelCase	:					Optional[int]	=	[lines[index + 1]]
     index += 1
    else:
     UpperCAmelCase	:					Tuple	=	[]
   else:
    blocks.append("""\n""".join(UpperCamelCase						)						)
    UpperCAmelCase	:					Tuple	=	[lines[index]]
  else:
   current_block.append(lines[index]						)
  index += 1

 # Adds current block if it's nonempty.
 if len(UpperCamelCase						) > 0:
  blocks.append("""\n""".join(UpperCamelCase						)						)

 # Add final block after end_prompt if provided.
 if end_prompt is not None and index < len(UpperCamelCase						):
  blocks.append("""\n""".join(lines[index:]						)						)

 return blocks

def       _snake_case						(						UpperCamelCase						:		Optional[Any]						):

 def _inner(UpperCamelCase						:		Optional[Any]						):
  return key(UpperCamelCase						).lower().replace("""_"""			,		""""""						)

 return _inner

def       _snake_case						(						UpperCamelCase						:		str			,		UpperCamelCase						:		Optional[int]=None						):

 # If no key is provided, we use a noop.
 def noop(UpperCamelCase						:		List[str]						):
  return x

 if key is None:
  UpperCAmelCase	:					Dict	=	noop
 # Constants are all uppercase, they go first.
 UpperCAmelCase	:					List[Any]	=	[obj for obj in objects if key(UpperCamelCase						).isupper()]
 # Classes are not all uppercase but start with a capital, they go second.
 UpperCAmelCase	:					Dict	=	[obj for obj in objects if key(UpperCamelCase						)[0].isupper() and not key(UpperCamelCase						).isupper()]
 # Functions begin with a lowercase, they go last.
 UpperCAmelCase	:					Any	=	[obj for obj in objects if not key(UpperCamelCase						)[0].isupper()]

 UpperCAmelCase	:					str	=	ignore_underscore(UpperCamelCase						)
 return sorted(UpperCamelCase			,		key=UpperCamelCase						) + sorted(UpperCamelCase			,		key=UpperCamelCase						) + sorted(UpperCamelCase			,		key=UpperCamelCase						)

def       _snake_case						(						UpperCamelCase						:		str						):

 # This inner function sort imports between [ ].
 def _replace(UpperCamelCase						:		int						):
  UpperCAmelCase	:					List[Any]	=	match.groups()[0]
  if "," not in imports:
   return F"[{imports}]"
  UpperCAmelCase	:					Optional[int]	=	[part.strip().replace("""\""""			,		""""""						) for part in imports.split(""","""						)]
  # We will have a final empty element if the line finished with a comma.
  if len(keys[-1]						) == 0:
   UpperCAmelCase	:					Union[str, Any]	=	keys[:-1]
  return "[" + ", ".join([F"\"{k}\"" for k in sort_objects(UpperCamelCase						)]						) + "]"

 UpperCAmelCase	:					Optional[Any]	=	import_statement.split("""\n"""						)
 if len(UpperCamelCase						) > 3:
  # Here we have to sort internal imports that are on several lines (one per name):
  # key: [
  #     "object1",
  #     "object2",
  #     ...
  # ]

  # We may have to ignore one or two lines on each side.
  UpperCAmelCase	:					Union[str, Any]	=	2 if lines[1].strip() == """[""" else 1
  UpperCAmelCase	:					str	=	[(i, _re_strip_line.search(UpperCamelCase						).groups()[0]) for i, line in enumerate(lines[idx:-idx]						)]
  UpperCAmelCase	:					Union[str, Any]	=	sort_objects(UpperCamelCase			,		key=lambda UpperCamelCase						: x[1]						)
  UpperCAmelCase	:					Any	=	[lines[x[0] + idx] for x in sorted_indices]
  return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]						)
 elif len(UpperCamelCase						) == 3:
  # Here we have to sort internal imports that are on one separate line:
  # key: [
  #     "object1", "object2", ...
  # ]
  if _re_bracket_content.search(lines[1]						) is not None:
   UpperCAmelCase	:					Optional[Any]	=	_re_bracket_content.sub(_replace			,		lines[1]						)
  else:
   UpperCAmelCase	:					Union[str, Any]	=	[part.strip().replace("""\""""			,		""""""						) for part in lines[1].split(""","""						)]
   # We will have a final empty element if the line finished with a comma.
   if len(keys[-1]						) == 0:
    UpperCAmelCase	:					int	=	keys[:-1]
   UpperCAmelCase	:					List[Any]	=	get_indent(lines[1]						) + """, """.join([F"\"{k}\"" for k in sort_objects(UpperCamelCase						)]						)
  return "\n".join(UpperCamelCase						)
 else:
  # Finally we have to deal with imports fitting on one line
  UpperCAmelCase	:					Dict	=	_re_bracket_content.sub(_replace			,		UpperCamelCase						)
  return import_statement

def       _snake_case						(						UpperCamelCase						:		List[Any]			,		UpperCamelCase						:		Tuple=True						):
 with open(UpperCamelCase			,		encoding="""utf-8"""						) as f:
  UpperCAmelCase	:					Optional[int]	=	f.read()

 if "_import_structure" not in code:
  return

 # Blocks of indent level 0
 UpperCAmelCase	:					Union[str, Any]	=	split_code_in_indented_blocks(
     UpperCamelCase			,		start_prompt="""_import_structure = {"""			,		end_prompt="""if TYPE_CHECKING:"""						)

 # We ignore block 0 (everything untils start_prompt) and the last block (everything after end_prompt).
 for block_idx in range(1			,		len(UpperCamelCase						) - 1						):
  # Check if the block contains some `_import_structure`s thingy to sort.
  UpperCAmelCase	:					List[str]	=	main_blocks[block_idx]
  UpperCAmelCase	:					Dict	=	block.split("""\n"""						)

  # Get to the start of the imports.
  UpperCAmelCase	:					Tuple	=	0
  while line_idx < len(UpperCamelCase						) and "_import_structure" not in block_lines[line_idx]:
   # Skip dummy import blocks
   if "import dummy" in block_lines[line_idx]:
    UpperCAmelCase	:					Any	=	len(UpperCamelCase						)
   else:
    line_idx += 1
  if line_idx >= len(UpperCamelCase						):
   continue

  # Ignore beginning and last line: they don't contain anything.
  UpperCAmelCase	:					List[str]	=	"""\n""".join(block_lines[line_idx:-1]						)
  UpperCAmelCase	:					Optional[int]	=	get_indent(block_lines[1]						)
  # Slit the internal block into blocks of indent level 1.
  UpperCAmelCase	:					List[Any]	=	split_code_in_indented_blocks(UpperCamelCase			,		indent_level=UpperCamelCase						)
  # We have two categories of import key: list or _import_structure[key].append/extend
  UpperCAmelCase	:					Optional[Any]	=	_re_direct_key if """_import_structure = {""" in block_lines[0] else _re_indirect_key
  # Grab the keys, but there is a trap: some lines are empty or just comments.
  UpperCAmelCase	:					Optional[int]	=	[(pattern.search(UpperCamelCase						).groups()[0] if pattern.search(UpperCamelCase						) is not None else None) for b in internal_blocks]
  # We only sort the lines with a key.
  UpperCAmelCase	:					Dict	=	[(i, key) for i, key in enumerate(UpperCamelCase						) if key is not None]
  UpperCAmelCase	:					List[Any]	=	[x[0] for x in sorted(UpperCamelCase			,		key=lambda UpperCamelCase						: x[1]						)]

  # We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
  UpperCAmelCase	:					Dict	=	0
  UpperCAmelCase	:					Dict	=	[]
  for i in range(len(UpperCamelCase						)						):
   if keys[i] is None:
    reorderded_blocks.append(internal_blocks[i]						)
   else:
    UpperCAmelCase	:					Tuple	=	sort_objects_in_import(internal_blocks[sorted_indices[count]]						)
    reorderded_blocks.append(UpperCamelCase						)
    count += 1

        # And we put our main block back together with its first and last line.
  UpperCAmelCase	:					Optional[int]	=	"""\n""".join(block_lines[:line_idx] + reorderded_blocks + [block_lines[-1]]						)

 if code != "\n".join(UpperCamelCase						):
  if check_only:
   return True
  else:
   print(F"Overwriting {file}."						)
   with open(UpperCamelCase			,		"""w"""			,		encoding="""utf-8"""						) as f:
    f.write("""\n""".join(UpperCamelCase						)						)

def       _snake_case						(						UpperCamelCase						:		Union[str, Any]=True						):
 UpperCAmelCase	:					str	=	[]
 for root, _, files in os.walk(UpperCamelCase						):
  if "__init__.py" in files:
   UpperCAmelCase	:					Optional[Any]	=	sort_imports(os.path.join(UpperCamelCase			,		"""__init__.py"""						)			,		check_only=UpperCamelCase						)
   if result:
    UpperCAmelCase	:					Union[str, Any]	=	[os.path.join(UpperCamelCase			,		"""__init__.py"""						)]
 if len(UpperCamelCase						) > 0:
  raise ValueError(F"Would overwrite {len(UpperCamelCase						)} files, run `make style`."						)


if __name__ == "__main__":
      A:   Optional[Any]								=		argparse.ArgumentParser()
      parser.add_argument("--check_only", action="store_true", help="Whether to only check or fix style.")
      A:   int								=		parser.parse_args()

      sort_imports_in_all_inits(check_only=args.check_only)





"""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       _snake_case						(						UpperCamelCase						:		Dataset			,		UpperCamelCase						:		Dict[str, str]						):
 UpperCAmelCase	:					Any	=	args.log_outputs
 UpperCAmelCase	:					Any	=	"""_""".join(args.dataset.split("""/"""						) + [args.config, args.split]						)

 # load metric
 UpperCAmelCase	:					List[Any]	=	load_metric("""wer"""						)
 UpperCAmelCase	:					Any	=	load_metric("""cer"""						)

 # compute metrics
 UpperCAmelCase	:					int	=	wer.compute(references=result["""target"""]			,		predictions=result["""prediction"""]						)
 UpperCAmelCase	:					str	=	cer.compute(references=result["""target"""]			,		predictions=result["""prediction"""]						)

 # print & log results
 UpperCAmelCase	:					Tuple	=	F"WER: {wer_result}\nCER: {cer_result}"
 print(UpperCamelCase						)

 with open(F"{dataset_id}_eval_results.txt"			,		"""w"""						) as f:
  f.write(UpperCamelCase						)

 # log all results in text file. Possibly interesting for analysis
 if log_outputs is not None:
  UpperCAmelCase	:					str	=	F"log_{dataset_id}_predictions.txt"
  UpperCAmelCase	:					Tuple	=	F"log_{dataset_id}_targets.txt"

  with open(UpperCamelCase			,		"""w"""						) as p, open(UpperCamelCase			,		"""w"""						) as t:
   # mapping function to write output
   def write_to_file(UpperCamelCase						:		List[Any]			,		UpperCamelCase						:		List[Any]						):
    p.write(F"{i}" + """\n"""						)
    p.write(batch["""prediction"""] + """\n"""						)
    t.write(F"{i}" + """\n"""						)
    t.write(batch["""target"""] + """\n"""						)

   result.map(UpperCamelCase			,		with_indices=UpperCamelCase						)

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

 UpperCAmelCase	:					Dict	=	re.sub(UpperCamelCase			,		""""""			,		text.lower()						)

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

 for t in token_sequences_to_ignore:
  UpperCAmelCase	:					Optional[Any]	=	""" """.join(text.split(UpperCamelCase						)						)

 return text

def       _snake_case						(						UpperCamelCase						:		Tuple						):
 # load dataset
 UpperCAmelCase	:					Union[str, Any]	=	load_dataset(args.dataset			,		args.config			,		split=args.split			,		use_auth_token=UpperCamelCase						)

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

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

 # resample audio
 UpperCAmelCase	:					List[str]	=	dataset.cast_column("""audio"""			,		Audio(sampling_rate=UpperCamelCase						)						)

 # load eval pipeline
 if args.device is None:
  UpperCAmelCase	:					Optional[int]	=	0 if torch.cuda.is_available() else -1
 UpperCAmelCase	:					Tuple	=	pipeline("""automatic-speech-recognition"""			,		model=args.model_id			,		device=args.device						)

 # map function to decode audio
 def map_to_pred(UpperCamelCase						:		Any						):
  UpperCAmelCase	:					Any	=	asr(
      batch["""audio"""]["""array"""]			,		chunk_length_s=args.chunk_length_s			,		stride_length_s=args.stride_length_s						)

  UpperCAmelCase	:					Tuple	=	prediction["""text"""]
  UpperCAmelCase	:					List[str]	=	normalize_text(batch["""sentence"""]						)
  return batch

 # run inference on all examples
 UpperCAmelCase	:					int	=	dataset.map(UpperCamelCase			,		remove_columns=dataset.column_names						)

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


if __name__ == "__main__":
      A:   List[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:   Union[str, Any]								=		parser.parse_args()

      main(args)
