

import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowerCamelCase           =					'src/diffusers'

# Matches is_xxx_available()
lowerCamelCase           =					re.compile(r'''is\_([a-z_]*)_available\(\)''')
# Matches from xxx import bla
lowerCamelCase           =					re.compile(r'''\s+from\s+\S*\s+import\s+([^\(\s].*)\n''')


lowerCamelCase           =					'\n{0} = None\n'

lowerCamelCase           =					'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n'


lowerCamelCase           =					'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'




def 			UpperCAmelCase__				(			_A      : Any							):





  '''simple docstring'''







  a__  =_re_backend.findall(_SCREAMING_SNAKE_CASE							)
  if len(_SCREAMING_SNAKE_CASE							) == 0:
    return None

  return "_and_".join(_SCREAMING_SNAKE_CASE							)




def 			UpperCAmelCase__				(			):





  '''simple docstring'''







  with open(os.path.join(_SCREAMING_SNAKE_CASE	,      '''__init__.py'''							)	,      '''r'''	,      encoding='''utf-8'''	,      newline='''\n'''							) as f:
    a__  =f.readlines()

  # Get to the point we do the actual imports for type checking
  a__  =0
  a__  ={}
  # Go through the end of the file
  while line_index < len(_SCREAMING_SNAKE_CASE							):
    # If the line contains is_backend_available, we grab all objects associated with the `else` block
    a__  =find_backend(lines[line_index]							)
    if backend is not None:
      while not lines[line_index].startswith('''else:'''							):
        line_index += 1
      line_index += 1
      a__  =[]
      # Until we unindent, add backend objects to the list
      while line_index < len(_SCREAMING_SNAKE_CASE							) and len(lines[line_index]							) > 1:
        a__  =lines[line_index]
        a__  =_re_single_line_import.search(_SCREAMING_SNAKE_CASE							)
        if single_line_import_search is not None:
          objects.extend(single_line_import_search.groups()[0].split(''', '''							)							)
        elif line.startswith(''' ''' * 8							):
          objects.append(line[8:-2]							)
        line_index += 1

      if len(_SCREAMING_SNAKE_CASE							) > 0:
        a__  =objects
    else:
      line_index += 1

  return backend_specific_objects




def 			UpperCAmelCase__				(			_A      : int	,      _A      : Dict							):





  '''simple docstring'''







  if name.isupper():
    return DUMMY_CONSTANT.format(_SCREAMING_SNAKE_CASE							)
  elif name.islower():
    return DUMMY_FUNCTION.format(_SCREAMING_SNAKE_CASE	,      _SCREAMING_SNAKE_CASE							)
  else:
    return DUMMY_CLASS.format(_SCREAMING_SNAKE_CASE	,      _SCREAMING_SNAKE_CASE							)




def 			UpperCAmelCase__				(			_A      : Tuple=None							):





  '''simple docstring'''







  if backend_specific_objects is None:
    a__  =read_init()
  # For special correspondence backend to module name as used in the function requires_modulename
  a__  ={}

  for backend, objects in backend_specific_objects.items():
    a__  ='[' + ', '.join(F"""\"{b}\"""" for b in backend.split('''_and_'''							)							) + ']'
    a__  ='# This file is autogenerated by the command `make fix-copies`, do not edit.\n'
    dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
    dummy_file += "\n".join([create_dummy_object(_SCREAMING_SNAKE_CASE	,      _SCREAMING_SNAKE_CASE							) for o in objects]							)
    a__  =dummy_file

  return dummy_files




def 			UpperCAmelCase__				(			_A      : List[str]=False							):





  '''simple docstring'''







  a__  =create_dummy_files()
  # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
  a__  ={'torch': 'pt'}

  # Locate actual dummy modules and read their content.
  a__  =os.path.join(_SCREAMING_SNAKE_CASE	,      '''utils'''							)
  a__  ={
      backend: os.path.join(_SCREAMING_SNAKE_CASE	,      F"""dummy_{short_names.get(_SCREAMING_SNAKE_CASE	,      _SCREAMING_SNAKE_CASE							)}_objects.py"""							)
      for backend in dummy_files.keys()
  }

  a__  ={}
  for backend, file_path in dummy_file_paths.items():
    if os.path.isfile(_SCREAMING_SNAKE_CASE							):
      with open(_SCREAMING_SNAKE_CASE	,      '''r'''	,      encoding='''utf-8'''	,      newline='''\n'''							) as f:
        a__  =f.read()
    else:
      a__  =''

  for backend in dummy_files.keys():
    if dummy_files[backend] != actual_dummies[backend]:
      if overwrite:
        print(
            F"""Updating diffusers.utils.dummy_{short_names.get(_SCREAMING_SNAKE_CASE	,      _SCREAMING_SNAKE_CASE							)}_objects.py as the main """
            '''__init__ has new objects.'''							)
        with open(dummy_file_paths[backend]	,      '''w'''	,      encoding='''utf-8'''	,      newline='''\n'''							) as f:
          f.write(dummy_files[backend]							)
      else:
        raise ValueError(
            '''The main __init__ has objects that are not present in '''
            F"""diffusers.utils.dummy_{short_names.get(_SCREAMING_SNAKE_CASE	,      _SCREAMING_SNAKE_CASE							)}_objects.py. Run `make fix-copies` """
            '''to fix this.'''							)


if __name__ == "__main__":
       lowerCamelCase           =					argparse.ArgumentParser()
       parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
       lowerCamelCase           =					parser.parse_args()

       check_dummies(args.fix_and_overwrite)




'''simple docstring'''



import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch

import numpy as np
import pytest
from absl.testing import parameterized

import datasets
from datasets import load_metric

from .utils import for_all_test_methods, local, slow


# mark all tests as integration
__lowercase	:						Tuple       =	pytest.mark.integration


__lowercase	:						Optional[int]       =	{'comet'}
__lowercase	:						List[str]       =	importlib.util.find_spec('fairseq') is not None

__lowercase	:						str       =	{'code_eval'}
__lowercase	:						List[Any]       =	os.name == 'nt'

__lowercase	:						Optional[Any]       =	{'bertscore', 'frugalscore', 'perplexity'}
__lowercase	:						Optional[Any]       =	importlib.util.find_spec('transformers') is not None






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Dict   ):
					@wraps(_SCREAMING_SNAKE_CASE   )
					def wrapper(self      :   int						,      _SCREAMING_SNAKE_CASE      :   List[Any]   ):
										if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
															self.skipTest('"test requires Fairseq"'   )
										else:
															test_case(self						,      _SCREAMING_SNAKE_CASE   )

					return wrapper






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Union[str, Any]   ):
					@wraps(_SCREAMING_SNAKE_CASE   )
					def wrapper(self      :   Dict						,      _SCREAMING_SNAKE_CASE      :   Union[str, Any]   ):
										if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
															self.skipTest('"test requires transformers"'   )
										else:
															test_case(self						,      _SCREAMING_SNAKE_CASE   )

					return wrapper






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Dict   ):
					@wraps(_SCREAMING_SNAKE_CASE   )
					def wrapper(self      :   Optional[int]						,      _SCREAMING_SNAKE_CASE      :   Optional[Any]   ):
										if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
															self.skipTest('"test not supported on Windows"'   )
										else:
															test_case(self						,      _SCREAMING_SNAKE_CASE   )

					return wrapper






def   lowerCamelCase							():
					__a			:       List[Any]					    =  [metric_dir.split(os.sep   )[-2] for metric_dir in glob.glob('./metrics/*/'   )]
					return [{"testcase_name": x, "metric_name": x} for x in metrics if x != "gleu"]  # gleu is unfinished





@parameterized.named_parameters(get_local_metric_names()					)
@for_all_test_methods(
    lowerCAmelCase_		,      lowerCAmelCase_		,      lowerCAmelCase_					)
@local
class 							__UpperCamelCase				(		parameterized.TestCase					):
	A_				=    {}
	A_				=    None




	@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'							)
	@pytest.mark.filterwarnings('ignore:load_metric is deprecated:FutureWarning'							)
	def       __UpperCAmelCase							(   self						,				__a							):

						'''simple docstring'''





						__a			:       int					    =  '[...]'
						__a			:       Tuple					    =  importlib.import_module(
						    datasets.load.metric_module_factory(os.path.join('metrics'						,				__a							)							).module_path							)
						__a			:       Optional[Any]					    =  datasets.load.import_main_class(metric_module.__name__						,				dataset=__a							)
						# check parameters
						__a			:       Dict					    =  inspect.signature(metric._compute							).parameters
						self.assertTrue(all(p.kind != p.VAR_KEYWORD for p in parameters.values()							)							)  # no **kwargs
						# run doctest
						with self.patch_intensive_calls(__a						,				metric_module.__name__							):
											with self.use_local_metrics():
																try:
																					__a			:       str					    =  doctest.testmod(__a						,				verbose=__a						,				raise_on_error=__a							)
																except doctest.UnexpectedException as e:
																					raise e.exc_info[1]  # raise the exception that doctest caught
						self.assertEqual(results.failed						,				0							)
						self.assertGreater(results.attempted						,				1							)




	@slow
	def       __UpperCAmelCase							(   self						,				__a							):

						'''simple docstring'''





						__a			:       Tuple					    =  '[...]'
						__a			:       Optional[Any]					    =  importlib.import_module(
						    datasets.load.metric_module_factory(os.path.join('metrics'						,				__a							)							).module_path							)
						# run doctest
						with self.use_local_metrics():
											__a			:       List[Any]					    =  doctest.testmod(__a						,				verbose=__a						,				raise_on_error=__a							)
						self.assertEqual(results.failed						,				0							)
						self.assertGreater(results.attempted						,				1							)




	@contextmanager
	def       __UpperCAmelCase							(   self						,				__a						,				__a							):

						'''simple docstring'''





						if metric_name in self.INTENSIVE_CALLS_PATCHER:
											with self.INTENSIVE_CALLS_PATCHER[metric_name](__a							):
																yield
						else:
											yield




	@contextmanager
	def       __UpperCAmelCase							(   self							):

						'''simple docstring'''





						def load_local_metric(__a						,				*__a						,				**__a							):
											return load_metric(os.path.join('metrics'						,				__a							)						,				*__a						,				**__a							)

						with patch('datasets.load_metric'							) as mock_load_metric:
											__a			:       Dict					    =  load_local_metric
											yield





	@classmethod
	def       __UpperCAmelCase							(   cls						,				__a							):

						'''simple docstring'''





						def wrapper(__a							):
											__a			:       Optional[Any]					    =  contextmanager(__a							)
											__a			:       str					    =  patcher
											return patcher

						return wrapper






@LocalMetricTest.register_intensive_calls_patcher('bleurt'   )
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Dict   ):
					import tensorflow.compat.va as tf
					from bleurt.score import Predictor

					tf.flags.DEFINE_string('sv'						,      ''						,      ''   )  # handle pytest cli flags





					class 							__UpperCamelCase				(		lowerCAmelCase_					):




						def       __UpperCAmelCase							(   self						,				__a							):

											'''simple docstring'''





											assert len(input_dict['input_ids']							) == 2
											return np.array([1.03, 1.04]							)

    # mock predict_fn which is supposed to do a forward pass with a bleurt model
					with patch('bleurt.score._create_predictor'   ) as mock_create_predictor:
										__a			:       Dict					    =  MockedPredictor()
										yield






@LocalMetricTest.register_intensive_calls_patcher('bertscore'   )
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   str   ):
					import torch

					def bert_cos_score_idf(_SCREAMING_SNAKE_CASE      :   List[str]						,      _SCREAMING_SNAKE_CASE      :   str						,      *_SCREAMING_SNAKE_CASE      :   int						,      **_SCREAMING_SNAKE_CASE      :   Optional[int]   ):
										return torch.tensor([[1.0, 1.0, 1.0]] * len(_SCREAMING_SNAKE_CASE   )   )

					# mock get_model which is supposed to do download a bert model
					# mock bert_cos_score_idf which is supposed to do a forward pass with a bert model
					with patch('bert_score.scorer.get_model'   ), patch(
					    'bert_score.scorer.bert_cos_score_idf'   ) as mock_bert_cos_score_idf:
										__a			:       str					    =  bert_cos_score_idf
										yield






@LocalMetricTest.register_intensive_calls_patcher('comet'   )
def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Dict   ):
					def load_from_checkpoint(_SCREAMING_SNAKE_CASE      :   Optional[int]   ):





										class 							__UpperCamelCase				:




											def       __UpperCAmelCase							(   self						,				__a						,				*__a						,				**__a							):

																'''simple docstring'''





																assert len(__a							) == 2
																__a			:       Dict					    =  [0.19, 0.92]
																return scores, sum(__a							) / len(__a							)



										return Model()

					# mock load_from_checkpoint which is supposed to do download a bert model
					# mock load_from_checkpoint which is supposed to do download a bert model
					with patch('comet.download_model'   ) as mock_download_model:
										__a			:       str					    =  None
										with patch('comet.load_from_checkpoint'   ) as mock_load_from_checkpoint:
															__a			:       int					    =  load_from_checkpoint
															yield






def   lowerCamelCase							():
					__a			:       Optional[Any]					    =  load_metric(os.path.join('metrics'						,      'seqeval'   )   )
					__a			:       List[str]					    =  'ERROR'
					__a			:       List[str]					    =  F"""Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {wrong_scheme}"""
					with pytest.raises(_SCREAMING_SNAKE_CASE						,      match=re.escape(_SCREAMING_SNAKE_CASE   )   ):
										metric.compute(predictions=[]						,      references=[]						,      scheme=_SCREAMING_SNAKE_CASE   )



