




import argparse
import collections
import os
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_UpperCAmelCase	:						Optional[Any]			=     "src/transformers"
_UpperCAmelCase	:						List[str]			=     "docs/source/en"
_UpperCAmelCase	:						Union[str, Any]			=     "."



def       UpperCAmelCase__  (     lowerCamelCase,			lowerCamelCase,			lowerCamelCase   ):
  with open(lowerCamelCase,			"r",			encoding="utf-8",			newline="\n"   ) as f:
    lowercase    :Optional[int]      	=						f.readlines()
  # Find the start prompt.
  lowercase    :str      	=						0
  while not lines[start_index].startswith(lowerCamelCase   ):
    start_index += 1
  start_index += 1

  lowercase    :int      	=						start_index
  while not lines[end_index].startswith(lowerCamelCase   ):
    end_index += 1
  end_index -= 1

  while len(lines[start_index]   ) <= 1:
    start_index += 1
  while len(lines[end_index]   ) <= 1:
    end_index -= 1
  end_index += 1
  return "".join(lines[start_index:end_index]   ), start_index, end_index, lines


# Add here suffixes that are used to identify models, separated by |
_UpperCAmelCase	:						Dict			=     "Model|Encoder|Decoder|ForConditionalGeneration"
# Regexes that match TF/Flax/PT model names.
_UpperCAmelCase	:						Dict			=     re.compile(r"TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")
_UpperCAmelCase	:						List[Any]			=     re.compile(r"Flax(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")
# Will match any TF or Flax model too so need to be in an else branch afterthe two previous regexes.
_UpperCAmelCase	:						str			=     re.compile(r"(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")


# This is to make sure the transformers module imported is the one in the repo.
_UpperCAmelCase	:						Any			=     direct_transformers_import(TRANSFORMERS_PATH)



def       UpperCAmelCase__  (     lowerCamelCase   ):
  lowercase    :Any      	=						re.finditer(".+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)",			lowerCamelCase   )
  return [m.group(0   ) for m in matches]



def       UpperCAmelCase__  (     lowerCamelCase,			lowerCamelCase   ):
  lowercase    :Union[str, Any]      	=						2 if text == "✅" or text == "❌" else len(lowerCamelCase   )
  lowercase    :int      	=						(width - text_length) // 2
  lowercase    :List[Any]      	=						width - text_length - left_indent
  return " " * left_indent + text + " " * right_indent



def       UpperCAmelCase__  (     ):
  lowercase    :int      	=						transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
  lowercase    :Union[str, Any]      	=						{
      name: config_maping_names[code]
      for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
      if code in config_maping_names
  }
  lowercase    :str      	=						{name: config.replace("Config",			""   ) for name, config in model_name_to_config.items()}

  # Dictionaries flagging if each model prefix has a slow/fast tokenizer, backend in PT/TF/Flax.
  lowercase    :Dict      	=						collections.defaultdict(lowerCamelCase   )
  lowercase    :Optional[int]      	=						collections.defaultdict(lowerCamelCase   )
  lowercase    :Tuple      	=						collections.defaultdict(lowerCamelCase   )
  lowercase    :List[Any]      	=						collections.defaultdict(lowerCamelCase   )
  lowercase    :Any      	=						collections.defaultdict(lowerCamelCase   )

  # Let's lookup through all transformers object (once).
  for attr_name in dir(lowerCamelCase   ):
    lowercase    :Dict      	=						None
    if attr_name.endswith("Tokenizer"   ):
      lowercase    :Optional[int]      	=						slow_tokenizers
      lowercase    :Tuple      	=						attr_name[:-9]
    elif attr_name.endswith("TokenizerFast"   ):
      lowercase    :str      	=						fast_tokenizers
      lowercase    :List[Any]      	=						attr_name[:-13]
    elif _re_tf_models.match(lowerCamelCase   ) is not None:
      lowercase    :List[str]      	=						tf_models
      lowercase    :Union[str, Any]      	=						_re_tf_models.match(lowerCamelCase   ).groups()[0]
    elif _re_flax_models.match(lowerCamelCase   ) is not None:
      lowercase    :Tuple      	=						flax_models
      lowercase    :Optional[Any]      	=						_re_flax_models.match(lowerCamelCase   ).groups()[0]
    elif _re_pt_models.match(lowerCamelCase   ) is not None:
      lowercase    :List[str]      	=						pt_models
      lowercase    :Optional[Any]      	=						_re_pt_models.match(lowerCamelCase   ).groups()[0]

    if lookup_dict is not None:
      while len(lowerCamelCase   ) > 0:
        if attr_name in model_name_to_prefix.values():
          lowercase    :Dict      	=						True
          break
        # Try again after removing the last word in the name
        lowercase    :Optional[int]      	=						"".join(camel_case_split(lowerCamelCase   )[:-1]   )

    # Let's build that table!
  lowercase    :str      	=						list(model_name_to_config.keys()   )
  model_names.sort(key=str.lower   )
  lowercase    :Dict      	=						["Model", "Tokenizer slow", "Tokenizer fast", "PyTorch support", "TensorFlow support", "Flax Support"]
  # We'll need widths to properly display everything in the center (+2 is to leave one extra space on each side).
  lowercase    :Tuple      	=						[len(lowerCamelCase   ) + 2 for c in columns]
  lowercase    :List[Any]      	=						max([len(lowerCamelCase   ) for name in model_names]   ) + 2

  # Build the table per se
  lowercase    :Optional[Any]      	=						"|" + "|".join([_center_text(lowerCamelCase,			lowerCamelCase   ) for c, w in zip(lowerCamelCase,			lowerCamelCase   )]   ) + "|\n"
  # Use ":-----:" format to center-aligned table cell texts
  table += "|" + "|".join([":" + "-" * (w - 2) + ":" for w in widths]   ) + "|\n"

  lowercase    :Tuple      	=						{True: "✅", False: "❌"}
  for name in model_names:
    lowercase    :Dict      	=						model_name_to_prefix[name]
    lowercase    :Dict      	=						[
        name,
        check[slow_tokenizers[prefix]],
        check[fast_tokenizers[prefix]],
        check[pt_models[prefix]],
        check[tf_models[prefix]],
        check[flax_models[prefix]],
    ]
    table += "|" + "|".join([_center_text(lowerCamelCase,			lowerCamelCase   ) for l, w in zip(lowerCamelCase,			lowerCamelCase   )]   ) + "|\n"
  return table



def       UpperCAmelCase__  (     lowerCamelCase=False   ):
  lowercase	,    lowercase	,    lowercase	,    lowercase    :List[str]      	=						_find_text_in_file(
      filename=os.path.join(lowerCamelCase,			"index.md"   ),			start_prompt="<!--This table is updated automatically from the auto modules",			end_prompt="<!-- End table-->",			)
  lowercase    :Tuple      	=						get_model_table_from_auto_modules()

  if current_table != new_table:
    if overwrite:
      with open(os.path.join(lowerCamelCase,			"index.md"   ),			"w",			encoding="utf-8",			newline="\n"   ) as f:
        f.writelines(lines[:start_index] + [new_table] + lines[end_index:]   )
    else:
      raise ValueError(
          "The model table in the `index.md` has not been updated. Run `make fix-copies` to fix this."   )


if __name__ == "__main__":
     _UpperCAmelCase	:						List[str]			=     argparse.ArgumentParser()
     parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
     _UpperCAmelCase	:						str			=     parser.parse_args()

     check_model_table(args.fix_and_overwrite)









import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment




@require_huggingface_suite
class    __lowerCAmelCase       (							unittest.TestCase):






       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]				):
         lowercase    :List[str]      	=						inspect.getfile(accelerate.test_utils				)
         lowercase    :List[Any]      	=						os.path.sep.join(
             mod_file.split(os.path.sep				)[:-1] + ["scripts", "external_deps", "test_metrics.py"]				)

         from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

         lowercase    :str      	=						test_metrics






       @require_cpu
       def 					SCREAMING_SNAKE_CASE    (   self:					Tuple				):
         debug_launcher(self.test_metrics.main       ,					num_processes=1				)






       @require_cpu
       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         debug_launcher(self.test_metrics.main				)






       @require_single_gpu
       def 					SCREAMING_SNAKE_CASE    (   self:					List[Any]				):
         self.test_metrics.main()






       @require_multi_gpu
       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         print(F"Found {torch.cuda.device_count()} devices."				)
         lowercase    :str      	=						["torchrun", F"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
         with patch_environment(omp_num_threads=1				):
           execute_subprocess_async(_lowerCAmelCase       ,					env=os.environ.copy()				)



