
"""simple docstring"""



import argparse

import torch
from torch import nn

from transformers import MBartConfig, MBartForConditionalGeneration
def 					lowerCamelCase   (     _snake_case ):
    UpperCAmelCase__	:      Optional[Any]     							=					[
        'encoder.version',
        'decoder.version',
        'model.encoder.version',
        'model.decoder.version',
        '_float_tensor',
        'decoder.output_projection.weight',
    ]
    for k in ignore_keys:
        state_dict.pop(_snake_case    ,_snake_case )
def 					lowerCamelCase   (     _snake_case ):
    UpperCAmelCase__							,							UpperCAmelCase__	:      Optional[int]     							=					emb.weight.shape
    UpperCAmelCase__	:      Optional[int]     							=					nn.Linear(_snake_case    ,_snake_case    ,bias=_snake_case )
    UpperCAmelCase__	:      Optional[Any]     							=					emb.weight.data
    return lin_layer
def 					lowerCamelCase   (     _snake_case    ,_snake_case="facebook/mbart-large-en-ro"    ,_snake_case=False    ,_snake_case=False ):
    UpperCAmelCase__	:      Union[str, Any]     							=					torch.load(_snake_case    ,map_location='cpu' )['model']
    remove_ignore_keys_(_snake_case )
    UpperCAmelCase__	:      int     							=					state_dict['encoder.embed_tokens.weight'].shape[0]

    UpperCAmelCase__	:      List[Any]     							=					MBartConfig.from_pretrained(_snake_case    ,vocab_size=_snake_case )
    if mbart_aa and finetuned:
        UpperCAmelCase__	:      Optional[int]     							=					'relu'

    UpperCAmelCase__	:      int     							=					state_dict['decoder.embed_tokens.weight']
    UpperCAmelCase__	:      Optional[int]     							=					MBartForConditionalGeneration(_snake_case )
    model.model.load_state_dict(_snake_case )

    if finetuned:
        UpperCAmelCase__	:      int     							=					make_linear_from_emb(model.model.shared )

    return model


if __name__ == "__main__":
    UpperCamelCase__          =	argparse.ArgumentParser()
    # Required parameters
    parser.add_argument(
        'fairseq_path', type=str, help='bart.large, bart.large.cnn or a path to a model.pt on local filesystem.'
    )
    parser.add_argument('pytorch_dump_folder_path', default=None, type=str, help='Path to the output PyTorch model.')
    parser.add_argument(
        '--hf_config',
        default='facebook/mbart-large-cc25',
        type=str,
        help='Which huggingface architecture to use: mbart-large',
    )
    parser.add_argument('--mbart_50', action='store_true', help='whether the model is mMART-50 checkpoint')
    parser.add_argument('--finetuned', action='store_true', help='whether the model is a fine-tuned checkpoint')
    UpperCamelCase__          =	parser.parse_args()
    UpperCamelCase__          =	convert_fairseq_mbart_checkpoint_from_disk(
        args.fairseq_path, hf_config_path=args.hf_config, finetuned=args.finetuned, mbart_aa=args.mbart_aa
    )
    model.save_pretrained(args.pytorch_dump_folder_path)


'''simple docstring'''






import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible







class lowercase_       (		unittest.TestCase			):







   """simple docstring"""

   def 	__UpperCAmelCase   (      self      :			Optional[Any]     )  ->			Dict:
        _A    		=  [
            'safety_checker/pytorch_model.bin',
            'safety_checker/model.safetensors',
            'vae/diffusion_pytorch_model.bin',
            'vae/diffusion_pytorch_model.safetensors',
            'text_encoder/pytorch_model.bin',
            'text_encoder/model.safetensors',
            'unet/diffusion_pytorch_model.bin',
            'unet/diffusion_pytorch_model.safetensors',
        ]
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			Union[str, Any]     )  ->			Optional[Any]:
        _A    		=  [
            'unet/diffusion_pytorch_model.bin',
            'unet/diffusion_pytorch_model.safetensors',
        ]
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			str     )  ->			Union[str, Any]:
        _A    		=  [
            'safety_checker/pytorch_model.bin',
            'safety_checker/model.safetensors',
            'vae/diffusion_pytorch_model.bin',
            'vae/diffusion_pytorch_model.safetensors',
            'text_encoder/pytorch_model.bin',
            'text_encoder/model.safetensors',
            'unet/diffusion_pytorch_model.bin',
            # Removed: 'unet/diffusion_pytorch_model.safetensors',
        ]
        self.assertFalse(is_safetensors_compatible(UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			int     )  ->			Dict:
        _A    		=  [
            'text_encoder/pytorch_model.bin',
            'text_encoder/model.safetensors',
        ]
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			Union[str, Any]     )  ->			str:
        _A    		=  [
            'safety_checker/pytorch_model.bin',
            'safety_checker/model.safetensors',
            'vae/diffusion_pytorch_model.bin',
            'vae/diffusion_pytorch_model.safetensors',
            'text_encoder/pytorch_model.bin',
            # Removed: 'text_encoder/model.safetensors',
            'unet/diffusion_pytorch_model.bin',
            'unet/diffusion_pytorch_model.safetensors',
        ]
        self.assertFalse(is_safetensors_compatible(UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			str     )  ->			Dict:
        _A    		=  [
            'safety_checker/pytorch_model.fp16.bin',
            'safety_checker/model.fp16.safetensors',
            'vae/diffusion_pytorch_model.fp16.bin',
            'vae/diffusion_pytorch_model.fp16.safetensors',
            'text_encoder/pytorch_model.fp16.bin',
            'text_encoder/model.fp16.safetensors',
            'unet/diffusion_pytorch_model.fp16.bin',
            'unet/diffusion_pytorch_model.fp16.safetensors',
        ]
        _A    		=  'fp16'
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__, variant=UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			Optional[int]     )  ->			List[str]:
        _A    		=  [
            'unet/diffusion_pytorch_model.fp16.bin',
            'unet/diffusion_pytorch_model.fp16.safetensors',
        ]
        _A    		=  'fp16'
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__, variant=UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			List[str]     )  ->			List[str]:
        # pass variant but use the non-variant filenames
        _A    		=  [
            'unet/diffusion_pytorch_model.bin',
            'unet/diffusion_pytorch_model.safetensors',
        ]
        _A    		=  'fp16'
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__, variant=UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			List[Any]     )  ->			Optional[Any]:
        _A    		=  [
            'safety_checker/pytorch_model.fp16.bin',
            'safety_checker/model.fp16.safetensors',
            'vae/diffusion_pytorch_model.fp16.bin',
            'vae/diffusion_pytorch_model.fp16.safetensors',
            'text_encoder/pytorch_model.fp16.bin',
            'text_encoder/model.fp16.safetensors',
            'unet/diffusion_pytorch_model.fp16.bin',
            # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
        ]
        _A    		=  'fp16'
        self.assertFalse(is_safetensors_compatible(UpperCamelCase__, variant=UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			Dict     )  ->			Union[str, Any]:
        _A    		=  [
            'text_encoder/pytorch_model.fp16.bin',
            'text_encoder/model.fp16.safetensors',
        ]
        _A    		=  'fp16'
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__, variant=UpperCamelCase__     )     )
   def 	__UpperCAmelCase   (      self      :			Tuple     )  ->			str:
        # pass variant but use the non-variant filenames
        _A    		=  [
            'text_encoder/pytorch_model.bin',
            'text_encoder/model.safetensors',
        ]
        _A    		=  'fp16'
        self.assertTrue(is_safetensors_compatible(UpperCamelCase__, variant=UpperCamelCase__     )     )

   def 	__UpperCAmelCase   (      self      :			List[Any]     )  ->			int:
        _A    		=  [
            'safety_checker/pytorch_model.fp16.bin',
            'safety_checker/model.fp16.safetensors',
            'vae/diffusion_pytorch_model.fp16.bin',
            'vae/diffusion_pytorch_model.fp16.safetensors',
            'text_encoder/pytorch_model.fp16.bin',
            # 'text_encoder/model.fp16.safetensors',
            'unet/diffusion_pytorch_model.fp16.bin',
            'unet/diffusion_pytorch_model.fp16.safetensors',
        ]
        _A    		=  'fp16'
        self.assertFalse(is_safetensors_compatible(UpperCamelCase__, variant=UpperCamelCase__     )     )



