



"""simple docstring"""







import argparse
import glob
import inspect
import os
import re
import unittest

from get_test_info import get_test_classes

from tests.test_pipeline_mixin import pipeline_test_mapping


A    =	{}
for task, _ in pipeline_test_mapping.items():
   A    =	{'pt': None, 'tf': None}


# DO **NOT** add item to this set (unless the reason is approved)
A    =	{
    'tests/models/esm/test_modeling_esmfold.py',  # The pipeline test mapping is added to `test_modeling_esm.py`
}

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       List[Any]   ):
      """simple docstring"""






      if "ModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
            return "pt"
      elif "TFModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
            return "tf"
      elif "FlaxModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
            return "flax"
      else:
            return None

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       List[str]    ,		lowerCamelCase_:       List[str]   ):
      """simple docstring"""






      if PIPELINE_TEST_MAPPING[task].get(lowerCamelCase_    ,		lowerCamelCase_   ) is not None:
            return PIPELINE_TEST_MAPPING[task][framework]

      snake_case      : List[str]							=   pipeline_test_mapping[task]["test"]
      snake_case      : Optional[Any]							=   None

      if framework == "pt":
            snake_case      : int							=   getattr(lowerCamelCase_    ,		"model_mapping"    ,		lowerCamelCase_   )
      elif framework == "tf":
            snake_case      : Dict							=   getattr(lowerCamelCase_    ,		"tf_model_mapping"    ,		lowerCamelCase_   )

      if mapping is not None:
            snake_case      : Union[str, Any]							=   dict(mapping.items()   )

      # cache the results
      snake_case      : List[str]							=   mapping
      return mapping

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       str    ,		lowerCamelCase_:       List[str]   ):
      """simple docstring"""






      snake_case      : int							=   get_framework(lowerCamelCase_   )
      if framework is None:
            return None
      snake_case      : Any							=   get_mapping_for_task(lowerCamelCase_    ,		lowerCamelCase_   )
      if mapping is None:
            return None

      snake_case      : str							=   list({model_class.config_class for model_class in test_class.all_model_classes}   )
      if len(lowerCamelCase_   ) != 1:
            raise ValueError("There should be exactly one configuration class from `test_class.all_model_classes`."   )

      # This could be a list/tuple of model classes, but it's rare.
      snake_case      : Tuple							=   mapping.get(config_classes[0]    ,		lowerCamelCase_   )
      if isinstance(lowerCamelCase_    ,		(tuple, list)   ):
            snake_case      : int							=   sorted(lowerCamelCase_    ,		key=lambda lowerCamelCase_   : x.__name__   )

      return model_class

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       Optional[Any]   ):
      """simple docstring"""






      snake_case      : int							=   [(task, get_model_for_pipeline_test(lowerCamelCase_    ,		lowerCamelCase_   )) for task in pipeline_test_mapping]
      snake_case      : Any							=   sorted([(task, model) for task, model in mapping if model is not None]    ,		key=lambda lowerCamelCase_   : x[0]   )

      return dict(lowerCamelCase_   )

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       Union[str, Any]   ):
      """simple docstring"""






      snake_case      : str							=   get_framework(lowerCamelCase_   )
      if framework == "pt":
            snake_case      : Optional[int]							=   "torch"
      snake_case      : List[str]							=   "{}"

      snake_case      : str							=   get_pipeline_model_mapping(lowerCamelCase_   )
      if len(lowerCamelCase_   ) == 0:
            return ""

      snake_case      : Union[str, Any]							=   []
      for task, model_classes in mapping.items():
            if isinstance(lowerCamelCase_    ,		(tuple, list)   ):
                  # A list/tuple of model classes
                  snake_case      : Union[str, Any]							=   "(" + ", ".join([x.__name__ for x in model_classes]   ) + ")"
            else:
                  # A single model class
                  snake_case      : List[str]							=   model_classes.__name__
            texts.append(f'''"{task}": {value}'''   )
      snake_case      : Optional[Any]							=   "{" + ", ".join(lowerCamelCase_   ) + "}"
      snake_case      : Tuple							=   f'''pipeline_model_mapping = {text} if is_{framework}_available() else {default_value}'''

      return text

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       List[Any]   ):
      """simple docstring"""






      snake_case      : List[str]							=   {"ModelTesterMixin", "TFModelTesterMixin", "FlaxModelTesterMixin"}
      if not issubclass(lowerCamelCase_    ,		unittest.TestCase   ):
            return False
      return len(base_class_names.intersection([x.__name__ for x in test_class.__bases__]   )   ) > 0

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       Optional[Any]   ):
      """simple docstring"""






      snake_case      : Optional[int]							=   [x for x in get_test_classes(lowerCamelCase_   ) if is_valid_test_class(lowerCamelCase_   )]

      snake_case      : List[str]							=   None
      for test_class in test_classes:
            # If a test class has defined `pipeline_model_mapping`, let's take it
            if getattr(lowerCamelCase_    ,		"pipeline_model_mapping"    ,		lowerCamelCase_   ) is not None:
                  snake_case      : Optional[int]							=   test_class
                  break
    # Take the test class with the shortest name (just a heuristic)
      if target_test_class is None and len(lowerCamelCase_   ) > 0:
            snake_case      : Tuple							=   sorted(lowerCamelCase_    ,		key=lambda lowerCamelCase_   : (len(x.__name__   ), x.__name__)   )[0]

      return target_test_class

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       Tuple    ,		lowerCamelCase_:       Dict    ,		lowerCamelCase_:       Union[str, Any]   ):
      """simple docstring"""






      snake_case      : str							=   start_idx
      for idx, line in enumerate(lines[start_idx:]   ):
            snake_case      : List[str]							=   len(lowerCamelCase_   ) - len(line.lstrip()   )
            if idx == 0 or indent > indent_level or (indent == indent_level and line.strip() == ")"):
                  snake_case      : Dict							=   start_idx + idx
            elif idx > 0 and indent <= indent_level:
                  # Outside the definition block of `pipeline_model_mapping`
                  break

      return end_idx

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       Dict    ,		lowerCamelCase_:       Any=False   ):
      """simple docstring"""






      if getattr(lowerCamelCase_    ,		"pipeline_model_mapping"    ,		lowerCamelCase_   ) is not None:
            if not overwrite:
                  return "", -1

      snake_case      : Optional[Any]							=   get_pipeline_model_mapping_string(lowerCamelCase_   )
      if len(lowerCamelCase_   ) == 0:
            return "", -1
      snake_case      : Dict							=   line_to_add + "\n"

      # The code defined the class `test_class`
      snake_case      : int							=   inspect.getsourcelines(lowerCamelCase_   )
      # `inspect` gives the code for an object, including decorator(s) if any.
      # We (only) need the exact line of the class definition.
      for idx, line in enumerate(lowerCamelCase_   ):
            if line.lstrip().startswith("class "   ):
                  snake_case      : str							=   class_lines[idx:]
                  class_start_line_no += idx
                  break
      snake_case      : Union[str, Any]							=   class_start_line_no + len(lowerCamelCase_   ) - 1

      # The index in `class_lines` that starts the definition of `all_model_classes`, `all_generative_model_classes` or
      # `pipeline_model_mapping`. This assumes they are defined in such order, and we take the start index of the last
      # block that appears in a `test_class`.
      snake_case      : List[Any]							=   None
      # The indent level of the line at `class_lines[start_idx]` (if defined)
      snake_case      : List[Any]							=   0
      # To record if `pipeline_model_mapping` is found in `test_class`.
      snake_case      : Optional[int]							=   None
      for idx, line in enumerate(lowerCamelCase_   ):
            if line.strip().startswith("all_model_classes = "   ):
                  snake_case      : List[Any]							=   len(lowerCamelCase_   ) - len(line.lstrip()   )
                  snake_case      : Union[str, Any]							=   idx
            elif line.strip().startswith("all_generative_model_classes = "   ):
                  snake_case      : List[str]							=   len(lowerCamelCase_   ) - len(line.lstrip()   )
                  snake_case      : List[Any]							=   idx
            elif line.strip().startswith("pipeline_model_mapping = "   ):
                  snake_case      : Dict							=   len(lowerCamelCase_   ) - len(line.lstrip()   )
                  snake_case      : Any							=   idx
                  snake_case      : List[str]							=   line
                  break

      if start_idx is None:
            return "", -1
      # Find the ending index (inclusive) of the above found block.
      snake_case      : Any							=   find_block_ending(lowerCamelCase_    ,		lowerCamelCase_    ,		lowerCamelCase_   )

      # Extract `is_xxx_available()` from existing blocks: some models require specific libraries like `timm` and use
      # `is_timm_available()` instead of `is_torch_available()`.
      # Keep leading and trailing whitespaces
      snake_case      : str							=   re.compile(r"\s(is_\S+?_available\(\))\s"   )
      for line in class_lines[start_idx : end_idx + 1]:
            snake_case      : str							=   r.search(lowerCamelCase_   )
            if backend_condition is not None:
                  # replace the leading and trailing whitespaces to the space character " ".
                  snake_case      : List[str]							=   " " + backend_condition[0][1:-1] + " "
                  snake_case      : Optional[Any]							=   r.sub(lowerCamelCase_    ,		lowerCamelCase_   )
                  break

      if def_line is None:
            # `pipeline_model_mapping` is not defined. The target index is set to the ending index (inclusive) of
            # `all_model_classes` or `all_generative_model_classes`.
            snake_case      : List[Any]							=   end_idx
      else:
            # `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
            snake_case      : int							=   start_idx - 1
            # mark the lines of the currently existing `pipeline_model_mapping` to be removed.
            for idx in range(lowerCamelCase_    ,		end_idx + 1   ):
                  # These lines are going to be removed before writing to the test file.
                  snake_case      : List[Any]							=   None  # noqa

    # Make sure the test class is a subclass of `PipelineTesterMixin`.
      snake_case      : Any							=   [x.__name__ for x in test_class.__bases__]
      if "PipelineTesterMixin" not in parent_classes:
            # Put `PipelineTesterMixin` just before `unittest.TestCase`
            snake_case      : Optional[int]							=   [x for x in parent_classes if x != "TestCase"] + ["PipelineTesterMixin"]
            if "TestCase" in parent_classes:
                  # Here we **assume** the original string is always with `unittest.TestCase`.
                  _parent_classes.append("unittest.TestCase"   )
            snake_case      : Any							=   ", ".join(_parent_classes   )
            for idx, line in enumerate(lowerCamelCase_   ):
                  # Find the ending of the declaration of `test_class`
                  if line.strip().endswith("):"   ):
                        # mark the lines of the declaration of `test_class` to be removed
                        for _idx in range(idx + 1   ):
                              snake_case      : Union[str, Any]							=   None  # noqa
                        break
        # Add the new, one-line, class declaration for `test_class`
            snake_case      : Optional[Any]							=   f'''class {test_class.__name__}({parent_classes}):\n'''

      # Add indentation
      snake_case      : str							=   " " * indent_level + line_to_add
      # Insert `pipeline_model_mapping` to `class_lines`.
      # (The line at `target_idx` should be kept by definition!)
      snake_case      : str							=   class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
      # Remove the lines that are marked to be removed
      snake_case      : List[str]							=   [x for x in class_lines if x is not None]

      # Move from test class to module (in order to write to the test file)
      snake_case      : List[Any]							=   inspect.getsourcelines(inspect.getmodule(lowerCamelCase_   )   )[0]
      # Be careful with the 1-off between line numbers and array indices
      snake_case      : Optional[Any]							=   module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
      snake_case      : Any							=   "".join(lowerCamelCase_   )

      snake_case      : List[str]							=   inspect.getsourcefile(lowerCamelCase_   )
      with open(lowerCamelCase_    ,		"w"    ,		encoding="UTF-8"    ,		newline="\n"   ) as fp:
            fp.write(lowerCamelCase_   )

      return line_to_add

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       Optional[Any]    ,		lowerCamelCase_:       List[str]=False   ):
      """simple docstring"""






      snake_case      : Any							=   find_test_class(lowerCamelCase_   )
      if test_class:
            add_pipeline_model_mapping(lowerCamelCase_    ,		overwrite=lowerCamelCase_   )


if __name__ == "__main__":
   A    =	argparse.ArgumentParser()
   parser.add_argument(
       '--test_file', type=str, help='A path to the test file, starting with the repository\'s `tests` directory.'
   )
   parser.add_argument(
       '--all',
       action='store_true',
       help='If to check and modify all test files.',
   )
   parser.add_argument(
       '--overwrite',
       action='store_true',
       help='If to overwrite a test class if it has already defined `pipeline_model_mapping`.',
   )
   A    =	parser.parse_args()

   if not args.all and not args.test_file:
      raise ValueError('Please specify either `test_file` or pass `--all` to check/modify all test files.')
   elif args.all and args.test_file:
      raise ValueError('Only one of `--test_file` and `--all` could be specified.')

   A    =	[]
   if args.test_file:
      A    =	[args.test_file]
   else:
      A    =	os.path.join('tests', 'models', '**', 'test_modeling_*.py')
      for test_file in glob.glob(pattern):
         # `Flax` is not concerned at this moment
         if not test_file.startswith('test_modeling_flax_'):
            test_files.append(test_file)

   for test_file in test_files:
      if test_file in TEST_FILE_TO_IGNORE:
         print(F'''[SKIPPED] {test_file} is skipped as it is in `TEST_FILE_TO_IGNORE` in the file {__file__}.''')
         continue
      add_pipeline_model_mapping_to_test_file(test_file, overwrite=args.overwrite)








"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A    =	{
    'configuration_camembert': ['CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CamembertConfig', 'CamembertOnnxConfig'],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			A    =	['CamembertTokenizer']

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			A    =	['CamembertTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			A    =	[
			    'CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CamembertForCausalLM',
			    'CamembertForMaskedLM',
			    'CamembertForMultipleChoice',
			    'CamembertForQuestionAnswering',
			    'CamembertForSequenceClassification',
			    'CamembertForTokenClassification',
			    'CamembertModel',
			    'CamembertPreTrainedModel',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			A    =	[
			    'TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'TFCamembertForCausalLM',
			    'TFCamembertForMaskedLM',
			    'TFCamembertForMultipleChoice',
			    'TFCamembertForQuestionAnswering',
			    'TFCamembertForSequenceClassification',
			    'TFCamembertForTokenClassification',
			    'TFCamembertModel',
			    'TFCamembertPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_camembert import CamembertTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_camembert_fast import CamembertTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_camembert import (
						    CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CamembertForCausalLM,
						    CamembertForMaskedLM,
						    CamembertForMultipleChoice,
						    CamembertForQuestionAnswering,
						    CamembertForSequenceClassification,
						    CamembertForTokenClassification,
						    CamembertModel,
						    CamembertPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_camembert import (
						    TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFCamembertForCausalLM,
						    TFCamembertForMaskedLM,
						    TFCamembertForMultipleChoice,
						    TFCamembertForQuestionAnswering,
						    TFCamembertForSequenceClassification,
						    TFCamembertForTokenClassification,
						    TFCamembertModel,
						    TFCamembertPreTrainedModel,
						)

else:
			import sys

			A    =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



