




import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('.')




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Union[str, Any]				)  ->							Optional[int]:
    UpperCAmelCase_										=					test_file.split(os.path.sep				)
    if components[0:2] != ["tests", "models"]:
        raise ValueError(
            '''`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '''
            f'{test_file} instead.'				)
    UpperCAmelCase_										=					components[-1]
    if not test_fn.endswith('''py'''				):
        raise ValueError(f'`test_file` should be a python file. Got {test_fn} instead.'				)
    if not test_fn.startswith('''test_modeling_'''				):
        raise ValueError(
            f'`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead.'				)

    UpperCAmelCase_										=					components[:-1] + [test_fn.replace('''.py'''	,					''''''				)]
    UpperCAmelCase_										=					""".""".join(__lowerCAmelCase				)

    return test_module_path




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[str]				)  ->							Any:
    UpperCAmelCase_										=					get_module_path(__lowerCAmelCase				)
    UpperCAmelCase_										=					importlib.import_module(__lowerCAmelCase				)

    return test_module




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						str				)  ->							Any:
    UpperCAmelCase_										=					[]
    UpperCAmelCase_										=					get_test_module(__lowerCAmelCase				)
    for attr in dir(__lowerCAmelCase				):
        if attr.endswith('''ModelTester'''				):
            tester_classes.append(getattr(__lowerCAmelCase	,					__lowerCAmelCase				)				)

    # sort with class names
    return sorted(__lowerCAmelCase	,					key=lambda __UpperCamelCase				: x.__name__				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[str]				)  ->							List[Any]:
    UpperCAmelCase_										=					[]
    UpperCAmelCase_										=					get_test_module(__lowerCAmelCase				)
    for attr in dir(__lowerCAmelCase				):
        UpperCAmelCase_										=					getattr(__lowerCAmelCase	,					__lowerCAmelCase				)
        # (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
        # `all_model_classes` is not empty (which also excludes other special classes).
        UpperCAmelCase_										=					getattr(__lowerCAmelCase	,					'''all_model_classes'''	,					[]				)
        if len(__lowerCAmelCase				) > 0:
            test_classes.append(__lowerCAmelCase				)

    # sort with class names
    return sorted(__lowerCAmelCase	,					key=lambda __UpperCamelCase				: x.__name__				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int				)  ->							Dict:
    UpperCAmelCase_										=					get_test_classes(__lowerCAmelCase				)
    UpperCAmelCase_										=					set()
    for test_class in test_classes:
        model_classes.update(test_class.all_model_classes				)

    # sort with class names
    return sorted(__lowerCAmelCase	,					key=lambda __UpperCamelCase				: x.__name__				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Dict				)  ->							Any:
    UpperCAmelCase_										=					test_class()
    if hasattr(__lowerCAmelCase	,					'''setUp'''				):
        test.setUp()

    UpperCAmelCase_										=					None
    if hasattr(__lowerCAmelCase	,					'''model_tester'''				):
        # `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
        if test.model_tester is not None:
            UpperCAmelCase_										=					test.model_tester.__class__

    return model_tester




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[Any]	,					__UpperCamelCase      :						Optional[int]				)  ->							List[str]:
    UpperCAmelCase_										=					get_test_classes(__lowerCAmelCase				)

    UpperCAmelCase_										=					[]
    for test_class in test_classes:
        if model_class in test_class.all_model_classes:
            target_test_classes.append(__lowerCAmelCase				)

    # sort with class names
    return sorted(__lowerCAmelCase	,					key=lambda __UpperCamelCase				: x.__name__				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[Any]	,					__UpperCamelCase      :						Optional[Any]				)  ->							Optional[Any]:
    UpperCAmelCase_										=					get_test_classes_for_model(__lowerCAmelCase	,					__lowerCAmelCase				)

    UpperCAmelCase_										=					[]
    for test_class in test_classes:
        UpperCAmelCase_										=					get_model_tester_from_test_class(__lowerCAmelCase				)
        if tester_class is not None:
            tester_classes.append(__lowerCAmelCase				)

    # sort with class names
    return sorted(__lowerCAmelCase	,					key=lambda __UpperCamelCase				: x.__name__				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[Any]				)  ->							int:
    UpperCAmelCase_										=					get_test_classes(__lowerCAmelCase				)
    UpperCAmelCase_										=					{test_class: get_model_tester_from_test_class(__lowerCAmelCase				) for test_class in test_classes}
    return test_tester_mapping




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Union[str, Any]				)  ->							Dict:
    UpperCAmelCase_										=					get_model_classes(__lowerCAmelCase				)
    UpperCAmelCase_										=					{
        model_class: get_test_classes_for_model(__lowerCAmelCase	,					__lowerCAmelCase				) for model_class in model_classes
    }
    return model_test_mapping




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[Any]				)  ->							Any:
    UpperCAmelCase_										=					get_model_classes(__lowerCAmelCase				)
    UpperCAmelCase_										=					{
        model_class: get_tester_classes_for_model(__lowerCAmelCase	,					__lowerCAmelCase				) for model_class in model_classes
    }
    return model_to_tester_mapping




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[Any]				)  ->							int:
    if isinstance(__lowerCAmelCase	,					__lowerCAmelCase				):
        return o
    elif isinstance(__lowerCAmelCase	,					__lowerCAmelCase				):
        return o.__name__
    elif isinstance(__lowerCAmelCase	,					(list, tuple)				):
        return [to_json(__lowerCAmelCase				) for x in o]
    elif isinstance(__lowerCAmelCase	,					__lowerCAmelCase				):
        return {to_json(__lowerCAmelCase				): to_json(__lowerCAmelCase				) for k, v in o.items()}
    else:
        return o











import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Union[str, Any]	,					__UpperCamelCase      :						int	,					__UpperCamelCase      :						Union[str, Any]	,					__UpperCamelCase      :						List[str]=5				)  ->							Dict:
    # Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub_interface.py
    assert masked_input.count('''<mask>'''				) == 1
    UpperCAmelCase_										=					torch.tensor(tokenizer.encode(__UpperCamelCase	,					add_special_tokens=__UpperCamelCase				)				).unsqueeze(0				)  # Batch size 1
    UpperCAmelCase_										=					model(__UpperCamelCase				)[0]  # The last hidden-state is the first element of the output tuple
    UpperCAmelCase_										=					(input_ids.squeeze() == tokenizer.mask_token_id).nonzero().item()
    UpperCAmelCase_										=					logits[0, masked_index, :]
    UpperCAmelCase_										=					logits.softmax(dim=0				)
    UpperCAmelCase_			,							UpperCAmelCase_										=					prob.topk(k=__UpperCamelCase	,					dim=0				)
    UpperCAmelCase_										=					''' '''.join(
        [tokenizer.convert_ids_to_tokens(indices[i].item()				) for i in range(len(__UpperCamelCase				)				)]				)
    UpperCAmelCase_										=					tokenizer.mask_token
    UpperCAmelCase_										=					[]
    for index, predicted_token_bpe in enumerate(topk_predicted_token_bpe.split(''' '''				)				):
        UpperCAmelCase_										=					predicted_token_bpe.replace('''\u2581'''	,					''' '''				)
        if " {0}".format(__UpperCamelCase				) in masked_input:
            topk_filled_outputs.append(
                (
                    masked_input.replace(''' {0}'''.format(__UpperCamelCase				)	,					__UpperCamelCase				),
                    values[index].item(),
                    predicted_token,
                )				)
        else:
            topk_filled_outputs.append(
                (
                    masked_input.replace(__UpperCamelCase	,					__UpperCamelCase				),
                    values[index].item(),
                    predicted_token,
                )				)
    return topk_filled_outputs


_lowerCamelCase      			=						CamembertTokenizer.from_pretrained('camembert-base')
_lowerCamelCase      			=						CamembertForMaskedLM.from_pretrained('camembert-base')
model.eval()

_lowerCamelCase      			=						'Le camembert est <mask> :)'


print(fill_mask(masked_input, model, tokenizer, topk=3))





